From 6b532e30deb841833ffc6d35867099e20c62b8a6 Mon Sep 17 00:00:00 2001 From: v-yehl Date: Thu, 3 Oct 2019 18:55:35 +0800 Subject: [PATCH] Extract Feat --- ExtractFeat/datasets/__init__.py | 4 + ExtractFeat/datasets/data_loader.py | 50 ++ ExtractFeat/datasets/list_loader.py | 43 ++ .../efficientnet_b4_clipart/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_clipart/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_clipart/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_clipart/config.yml | 43 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_clipart/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_clipart/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_clipart/config.yml | 42 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../phase1/clipart/scripts/efficientnet_b4.sh | 11 + .../phase1/clipart/scripts/efficientnet_b5.sh | 11 + .../phase1/clipart/scripts/efficientnet_b6.sh | 11 + .../phase1/clipart/scripts/efficientnet_b7.sh | 11 + .../clipart/scripts/inceptionresnetv2.sh | 11 + .../phase1/clipart/scripts/inceptionv4.sh | 11 + .../phase1/clipart/scripts/pnasnet5large.sh | 11 + .../phase1/clipart/scripts/senet154.sh | 12 + .../senet154/senet154_clipart/config.yml | 43 ++ .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../clipart/senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_painting/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_painting/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_painting/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_painting/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_painting/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_painting/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_painting/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../painting/scripts/efficientnet_b4.sh | 12 + .../painting/scripts/efficientnet_b5.sh | 12 + .../painting/scripts/efficientnet_b6.sh | 11 + .../painting/scripts/efficientnet_b7.sh | 11 + .../painting/scripts/inceptionresnetv2.sh | 11 + .../phase1/painting/scripts/inceptionv4.sh | 12 + .../phase1/painting/scripts/pnasnet5large.sh | 11 + .../phase1/painting/scripts/senet154.sh | 12 + .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_painting/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ .../efficientnet_b4_clipart/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_clipart/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_clipart/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_clipart/config.yml | 43 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_clipart/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_clipart/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_clipart/config.yml | 42 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../phase2/clipart/scripts/efficientnet_b4.sh | 17 + .../phase2/clipart/scripts/efficientnet_b5.sh | 17 + .../phase2/clipart/scripts/efficientnet_b6.sh | 17 + .../phase2/clipart/scripts/efficientnet_b7.sh | 17 + .../clipart/scripts/inceptionresnetv2.sh | 17 + .../phase2/clipart/scripts/inceptionv4.sh | 17 + .../phase2/clipart/scripts/pnasnet5large.sh | 17 + .../phase2/clipart/scripts/senet154.sh | 17 + .../senet154/senet154_clipart/config.yml | 43 ++ .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../clipart/senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_painting/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_painting/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_painting/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_painting/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_painting/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_painting/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_painting/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../painting/scripts/efficientnet_b4.sh | 17 + .../painting/scripts/efficientnet_b5.sh | 17 + .../painting/scripts/efficientnet_b6.sh | 17 + .../painting/scripts/efficientnet_b7.sh | 17 + .../painting/scripts/inceptionresnetv2.sh | 17 + .../phase2/painting/scripts/inceptionv4.sh | 17 + .../phase2/painting/scripts/pnasnet5large.sh | 17 + .../phase2/painting/scripts/senet154.sh | 17 + .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_painting/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ .../efficientnet_b4_clipart/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_clipart/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_clipart/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_clipart/config.yml | 43 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_clipart/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_clipart/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_clipart/config.yml | 42 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../phase3/clipart/scripts/efficientnet_b4.sh | 17 + .../phase3/clipart/scripts/efficientnet_b5.sh | 17 + .../phase3/clipart/scripts/efficientnet_b6.sh | 17 + .../phase3/clipart/scripts/efficientnet_b7.sh | 17 + .../clipart/scripts/inceptionresnetv2.sh | 17 + .../phase3/clipart/scripts/inceptionv4.sh | 17 + .../phase3/clipart/scripts/pnasnet5large.sh | 17 + .../phase3/clipart/scripts/senet154.sh | 17 + .../senet154/senet154_clipart/config.yml | 43 ++ .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../clipart/senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_painting/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_painting/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_painting/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_painting/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_painting/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_painting/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_painting/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../painting/scripts/efficientnet_b4.sh | 17 + .../painting/scripts/efficientnet_b5.sh | 17 + .../painting/scripts/efficientnet_b6.sh | 17 + .../painting/scripts/efficientnet_b7.sh | 17 + .../painting/scripts/inceptionresnetv2.sh | 17 + .../phase3/painting/scripts/inceptionv4.sh | 17 + .../phase3/painting/scripts/pnasnet5large.sh | 17 + .../phase3/painting/scripts/senet154.sh | 17 + .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_painting/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ .../efficientnet_b4_clipart/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_clipart/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_clipart/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_clipart/config.yml | 44 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_clipart/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_clipart/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_clipart/config.yml | 42 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../phase4/clipart/scripts/efficientnet_b4.sh | 17 + .../phase4/clipart/scripts/efficientnet_b5.sh | 17 + .../phase4/clipart/scripts/efficientnet_b6.sh | 17 + .../phase4/clipart/scripts/efficientnet_b7.sh | 17 + .../clipart/scripts/inceptionresnetv2.sh | 17 + .../phase4/clipart/scripts/inceptionv4.sh | 17 + .../phase4/clipart/scripts/pnasnet5large.sh | 17 + .../phase4/clipart/scripts/senet154.sh | 17 + .../senet154/senet154_clipart/config.yml | 43 ++ .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../clipart/senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ .../efficientnet_b4_infograph/config.yml | 43 ++ .../efficientnet_b4_painting/config.yml | 43 ++ .../efficientnet_b4_quickdraw/config.yml | 43 ++ .../efficientnet_b4_real/config.yml | 43 ++ .../efficientnet_b4_sketch/config.yml | 43 ++ .../efficientnet_b5_infograph/config.yml | 43 ++ .../efficientnet_b5_painting/config.yml | 43 ++ .../efficientnet_b5_quickdraw/config.yml | 43 ++ .../efficientnet_b5_real/config.yml | 43 ++ .../efficientnet_b5_sketch/config.yml | 43 ++ .../efficientnet_b6_infograph/config.yml | 43 ++ .../efficientnet_b6_painting/config.yml | 43 ++ .../efficientnet_b6_quickdraw/config.yml | 43 ++ .../efficientnet_b6_real/config.yml | 43 ++ .../efficientnet_b6_sketch/config.yml | 43 ++ .../efficientnet_b7_infograph/config.yml | 43 ++ .../efficientnet_b7_painting/config.yml | 43 ++ .../efficientnet_b7_quickdraw/config.yml | 43 ++ .../efficientnet_b7_real/config.yml | 43 ++ .../efficientnet_b7_sketch/config.yml | 43 ++ .../inceptionresnetv2_infograph/config.yml | 43 ++ .../inceptionresnetv2_painting/config.yml | 43 ++ .../inceptionresnetv2_quickdraw/config.yml | 43 ++ .../inceptionresnetv2_real/config.yml | 43 ++ .../inceptionresnetv2_sketch/config.yml | 43 ++ .../inceptionv4_infograph/config.yml | 43 ++ .../inceptionv4_painting/config.yml | 43 ++ .../inceptionv4_quickdraw/config.yml | 43 ++ .../inceptionv4/inceptionv4_real/config.yml | 43 ++ .../inceptionv4/inceptionv4_sketch/config.yml | 43 ++ .../pnasnet5large_infograph/config.yml | 42 ++ .../pnasnet5large_painting/config.yml | 42 ++ .../pnasnet5large_quickdraw/config.yml | 42 ++ .../pnasnet5large_real/config.yml | 42 ++ .../pnasnet5large_sketch/config.yml | 42 ++ .../painting/scripts/efficientnet_b4.sh | 17 + .../painting/scripts/efficientnet_b5.sh | 17 + .../painting/scripts/efficientnet_b6.sh | 17 + .../painting/scripts/efficientnet_b7.sh | 17 + .../painting/scripts/inceptionresnetv2.sh | 17 + .../phase4/painting/scripts/inceptionv4.sh | 17 + .../phase4/painting/scripts/pnasnet5large.sh | 17 + .../phase4/painting/scripts/senet154.sh | 17 + .../senet154/senet154_infograph/config.yml | 43 ++ .../senet154/senet154_painting/config.yml | 43 ++ .../senet154/senet154_quickdraw/config.yml | 43 ++ .../senet154/senet154_real/config.yml | 43 ++ .../senet154/senet154_sketch/config.yml | 43 ++ ExtractFeat/lib/__init__.py | 4 + ExtractFeat/lib/config.py | 202 ++++++ ExtractFeat/lib/utils.py | 88 +++ ExtractFeat/main.py | 36 ++ ExtractFeat/models/__init__.py | 13 + ExtractFeat/models/classifier.py | 44 ++ ExtractFeat/models/dpn.py | 339 ++++++++++ ExtractFeat/models/efficientnet.py | 551 ++++++++++++++++ ExtractFeat/models/inceptionresnetv2.py | 390 +++++++++++ ExtractFeat/models/inceptionv4.py | 369 +++++++++++ ExtractFeat/models/pnasnet.py | 430 +++++++++++++ ExtractFeat/models/senet.py | 603 ++++++++++++++++++ ExtractFeat/trainer.py | 197 ++++++ 400 files changed, 18081 insertions(+) create mode 100644 ExtractFeat/datasets/__init__.py create mode 100644 ExtractFeat/datasets/data_loader.py create mode 100644 ExtractFeat/datasets/list_loader.py create mode 100644 ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml create mode 100644 ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml create mode 100644 ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml create mode 100644 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ExtractFeat/lib/utils.py create mode 100644 ExtractFeat/main.py create mode 100644 ExtractFeat/models/__init__.py create mode 100644 ExtractFeat/models/classifier.py create mode 100644 ExtractFeat/models/dpn.py create mode 100644 ExtractFeat/models/efficientnet.py create mode 100644 ExtractFeat/models/inceptionresnetv2.py create mode 100644 ExtractFeat/models/inceptionv4.py create mode 100644 ExtractFeat/models/pnasnet.py create mode 100644 ExtractFeat/models/senet.py create mode 100644 ExtractFeat/trainer.py diff --git a/ExtractFeat/datasets/__init__.py b/ExtractFeat/datasets/__init__.py new file mode 100644 index 0000000..158cdcb --- /dev/null +++ b/ExtractFeat/datasets/__init__.py @@ -0,0 +1,4 @@ +# -------------------------------------------------------- +# Domain Adaptation +# Written by VARMS +# -------------------------------------------------------- \ No newline at end of file diff --git a/ExtractFeat/datasets/data_loader.py b/ExtractFeat/datasets/data_loader.py new file mode 100644 index 0000000..1e0b41f --- /dev/null +++ b/ExtractFeat/datasets/data_loader.py @@ -0,0 +1,50 @@ +import os +import datasets.list_loader as list_loader +import torch +from torchvision import transforms +import lib.utils as utils +from lib.config import cfg +import torch.distributed as dist +from os.path import join as join + + +def get_transform(): + trans = [] + + if cfg.AUG.RESIZE[0] > 0 and cfg.AUG.RESIZE[1] > 0: + trans.append(transforms.Resize(cfg.AUG.RESIZE)) + if cfg.AUG.V_FLIP > 0: + trans.append(transforms.RandomVerticalFlip(p=cfg.AUG.V_FLIP)) + if cfg.AUG.H_FLIP > 0: + trans.append(transforms.RandomHorizontalFlip(p=cfg.AUG.H_FLIP)) + if cfg.AUG.ROTATION > 0: + trans.append(transforms.RandomRotation(cfg.AUG.ROTATION, expand=False)) + if cfg.AUG.BRIGHTNESS > 0 or cfg.AUG.CONTRAST > 0 or cfg.AUG.SATURATION > 0 or cfg.AUG.HUE > 0: + trans.append(transforms.ColorJitter(brightness=cfg.AUG.BRIGHTNESS, + contrast=cfg.AUG.CONTRAST, saturation=cfg.AUG.SATURATION, hue=cfg.AUG.HUE)) + if cfg.AUG.RND_CROP[0] > 0 and cfg.AUG.RND_CROP[1] > 0: + trans.append(transforms.RandomCrop(cfg.AUG.RND_CROP)) + + trans.append(transforms.ToTensor()) + trans.append(transforms.Normalize(cfg.MEAN, cfg.STD)) + return trans + + +def load_test(target_root, test_label, use_mirror = False): + if use_mirror: + transform = transforms.Compose([ + transforms.RandomHorizontalFlip(p=1.0), + transforms.Resize(cfg.AUG.TEST_CROP), + transforms.ToTensor(), + transforms.Normalize(cfg.MEAN, cfg.STD) + ]) + else: + transform = transforms.Compose([ + transforms.Resize(cfg.AUG.TEST_CROP), + transforms.ToTensor(), + transforms.Normalize(cfg.MEAN, cfg.STD) + ]) + image_set = list_loader.ListLoader(target_root, test_label, transform) + loader = torch.utils.data.DataLoader(image_set, batch_size=cfg.TEST.BATCH_SIZE, + shuffle=False, num_workers=cfg.DATA_LOADER.NUM_WORKERS) + return loader diff --git a/ExtractFeat/datasets/list_loader.py b/ExtractFeat/datasets/list_loader.py new file mode 100644 index 0000000..7eaa3f5 --- /dev/null +++ b/ExtractFeat/datasets/list_loader.py @@ -0,0 +1,43 @@ +import torch +import torch.utils.data as data +from PIL import Image +import os +import random +import numpy as np +from lib.config import cfg + + +def default_loader(path): + return Image.open(path).convert('RGB') + + +def make_dataset(root, list_path): + images = [] + listtxt = open(list_path) + for line in listtxt: + data = line.strip().split(' ') + path = os.path.join(root, data[0]) + label = int(data[1]) + item = (path, label) + images.append(item) + return images + + +class ListLoader(data.Dataset): + def __init__(self, root, list_path, transform=None, loader=default_loader): + imgs = make_dataset(root, list_path) + self.root = root + self.imgs = imgs + self.transform = transform + self.loader = loader + + def __getitem__(self, index): + path, target = self.imgs[index] + img = self.loader(path) + + if self.transform is not None: + img = self.transform(img) + return img, target + + def __len__(self): + return len(self.imgs) \ No newline at end of file diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml new file mode 100644 index 0000000..0ff18d1 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml new file mode 100644 index 0000000..ec9996a --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml new file mode 100644 index 0000000..ef0cd9b --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml new file mode 100644 index 0000000..c28e42b --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml new file mode 100644 index 0000000..c119666 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_clipart/config.yml new file mode 100644 index 0000000..6d28a67 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_clipart/config.yml new file mode 100644 index 0000000..bdfe00c --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_clipart/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..423f4da --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b4.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=20 +PHASE=1 + +DOMAIN=clipart +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..9d1f556 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b5.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=18 +PHASE=1 + +DOMAIN=clipart +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..f24ed5c --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b6.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=17 +PHASE=1 + +DOMAIN=clipart +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..004f65f --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/efficientnet_b7.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=17 +PHASE=1 + +DOMAIN=clipart +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase1/clipart/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..cbf9ae9 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/inceptionresnetv2.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=18 +PHASE=1 + +DOMAIN=clipart +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase1/clipart/scripts/inceptionv4.sh new file mode 100644 index 0000000..e17d05e --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/inceptionv4.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=18 +PHASE=1 + +DOMAIN=clipart +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase1/clipart/scripts/pnasnet5large.sh new file mode 100644 index 0000000..df4cc6c --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/pnasnet5large.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=19 +PHASE=1 + +DOMAIN=clipart +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/clipart/scripts/senet154.sh b/ExtractFeat/experiments/phase1/clipart/scripts/senet154.sh new file mode 100644 index 0000000..1b1b943 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/scripts/senet154.sh @@ -0,0 +1,12 @@ +GPUID=3 +RESUME=17 +PHASE=1 + +DOMAIN=clipart +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + diff --git a/ExtractFeat/experiments/phase1/clipart/senet154/senet154_clipart/config.yml b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_clipart/config.yml new file mode 100644 index 0000000..2d9b7f5 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/clipart/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase1/clipart/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_painting/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_painting/config.yml new file mode 100644 index 0000000..450ae3f --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_painting/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_painting/config.yml new file mode 100644 index 0000000..c825faa --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_painting/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_painting/config.yml new file mode 100644 index 0000000..055160c --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_painting/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_painting/config.yml new file mode 100644 index 0000000..d5f587a --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml new file mode 100644 index 0000000..0627b1d --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_painting/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_painting/config.yml new file mode 100644 index 0000000..487a217 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_painting/config.yml b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_painting/config.yml new file mode 100644 index 0000000..fbba59d --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_painting/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..80102b9 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b4.sh @@ -0,0 +1,12 @@ +GPUID=3 +RESUME=19 +PHASE=1 + +DOMAIN=painting +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + diff --git a/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..eeafcf1 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b5.sh @@ -0,0 +1,12 @@ +GPUID=3 +RESUME=17 +PHASE=1 + +DOMAIN=painting +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + diff --git a/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..bc8b6f9 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b6.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=17 +PHASE=1 + +DOMAIN=painting +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..6248f05 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/efficientnet_b7.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=18 +PHASE=1 + +DOMAIN=painting +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/painting/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase1/painting/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..dfbc575 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/inceptionresnetv2.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=18 +PHASE=1 + +DOMAIN=painting +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/painting/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase1/painting/scripts/inceptionv4.sh new file mode 100644 index 0000000..c3fc853 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/inceptionv4.sh @@ -0,0 +1,12 @@ +GPUID=3 +RESUME=18 +PHASE=1 + +DOMAIN=painting +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + diff --git a/ExtractFeat/experiments/phase1/painting/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase1/painting/scripts/pnasnet5large.sh new file mode 100644 index 0000000..206827b --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/pnasnet5large.sh @@ -0,0 +1,11 @@ +GPUID=3 +RESUME=18 +PHASE=1 + +DOMAIN=painting +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME diff --git a/ExtractFeat/experiments/phase1/painting/scripts/senet154.sh b/ExtractFeat/experiments/phase1/painting/scripts/senet154.sh new file mode 100644 index 0000000..209b21e --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/scripts/senet154.sh @@ -0,0 +1,12 @@ +GPUID=3 +RESUME=17 +PHASE=1 + +DOMAIN=painting +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + diff --git a/ExtractFeat/experiments/phase1/painting/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase1/painting/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/senet154/senet154_painting/config.yml b/ExtractFeat/experiments/phase1/painting/senet154/senet154_painting/config.yml new file mode 100644 index 0000000..d321488 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/senet154/senet154_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase1/painting/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase1/painting/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase1/painting/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase1/painting/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase1/painting/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml new file mode 100644 index 0000000..0ff18d1 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml new file mode 100644 index 0000000..ec9996a --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml new file mode 100644 index 0000000..ef0cd9b --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml new file mode 100644 index 0000000..c28e42b --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml new file mode 100644 index 0000000..c119666 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_clipart/config.yml new file mode 100644 index 0000000..6d28a67 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_clipart/config.yml new file mode 100644 index 0000000..bdfe00c --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_clipart/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..be5162c --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=2 + +DOMAIN=clipart +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..b958155 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b5.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=2 + +DOMAIN=clipart +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..5275fb1 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b6.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=2 + +DOMAIN=clipart +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..c1b538e --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/efficientnet_b7.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=2 + +DOMAIN=clipart +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase2/clipart/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..5bff87b --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/inceptionresnetv2.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=2 + +DOMAIN=clipart +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase2/clipart/scripts/inceptionv4.sh new file mode 100644 index 0000000..477f554 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/inceptionv4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=20 +PHASE=2 + +DOMAIN=clipart +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase2/clipart/scripts/pnasnet5large.sh new file mode 100644 index 0000000..dc41d8c --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/pnasnet5large.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=2 + +DOMAIN=clipart +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/scripts/senet154.sh b/ExtractFeat/experiments/phase2/clipart/scripts/senet154.sh new file mode 100644 index 0000000..7640af7 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/scripts/senet154.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=20 +PHASE=2 + +DOMAIN=clipart +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/clipart/senet154/senet154_clipart/config.yml b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_clipart/config.yml new file mode 100644 index 0000000..2d9b7f5 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/clipart/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase2/clipart/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_painting/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_painting/config.yml new file mode 100644 index 0000000..450ae3f --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_painting/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_painting/config.yml new file mode 100644 index 0000000..c825faa --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_painting/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_painting/config.yml new file mode 100644 index 0000000..055160c --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_painting/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_painting/config.yml new file mode 100644 index 0000000..d5f587a --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml new file mode 100644 index 0000000..0627b1d --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_painting/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_painting/config.yml new file mode 100644 index 0000000..487a217 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_painting/config.yml b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_painting/config.yml new file mode 100644 index 0000000..fbba59d --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_painting/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..c615b2d --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=2 + +DOMAIN=painting +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..f304875 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b5.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=2 + +DOMAIN=painting +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..506800a --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b6.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=2 + +DOMAIN=painting +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..f2cbd23 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/efficientnet_b7.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=2 + +DOMAIN=painting +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase2/painting/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..2f7dd38 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/inceptionresnetv2.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=2 + +DOMAIN=painting +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase2/painting/scripts/inceptionv4.sh new file mode 100644 index 0000000..6f20f0e --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/inceptionv4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=2 + +DOMAIN=painting +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase2/painting/scripts/pnasnet5large.sh new file mode 100644 index 0000000..74c4794 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/pnasnet5large.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=2 + +DOMAIN=painting +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/scripts/senet154.sh b/ExtractFeat/experiments/phase2/painting/scripts/senet154.sh new file mode 100644 index 0000000..76a5110 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/scripts/senet154.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=2 + +DOMAIN=painting +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase2/painting/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase2/painting/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/senet154/senet154_painting/config.yml b/ExtractFeat/experiments/phase2/painting/senet154/senet154_painting/config.yml new file mode 100644 index 0000000..d321488 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/senet154/senet154_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase2/painting/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase2/painting/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase2/painting/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase2/painting/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase2/painting/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml new file mode 100644 index 0000000..0ff18d1 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml new file mode 100644 index 0000000..ec9996a --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml new file mode 100644 index 0000000..ef0cd9b --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml new file mode 100644 index 0000000..c28e42b --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml new file mode 100644 index 0000000..c119666 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_clipart/config.yml new file mode 100644 index 0000000..6d28a67 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_clipart/config.yml new file mode 100644 index 0000000..bdfe00c --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_clipart/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..5f87587 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=3 + +DOMAIN=clipart +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..6b76f80 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b5.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=3 + +DOMAIN=clipart +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..ba03f7f --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b6.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=3 + +DOMAIN=clipart +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..dba61b9 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/efficientnet_b7.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=3 + +DOMAIN=clipart +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase3/clipart/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..486ea6a --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/inceptionresnetv2.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=15 +PHASE=3 + +DOMAIN=clipart +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase3/clipart/scripts/inceptionv4.sh new file mode 100644 index 0000000..0c44160 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/inceptionv4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=clipart +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase3/clipart/scripts/pnasnet5large.sh new file mode 100644 index 0000000..40c87d7 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/pnasnet5large.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=clipart +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/scripts/senet154.sh b/ExtractFeat/experiments/phase3/clipart/scripts/senet154.sh new file mode 100644 index 0000000..621dc5e --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/scripts/senet154.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=3 + +DOMAIN=clipart +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/clipart/senet154/senet154_clipart/config.yml b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_clipart/config.yml new file mode 100644 index 0000000..2d9b7f5 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/clipart/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase3/clipart/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_painting/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_painting/config.yml new file mode 100644 index 0000000..450ae3f --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_painting/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_painting/config.yml new file mode 100644 index 0000000..c825faa --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_painting/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_painting/config.yml new file mode 100644 index 0000000..055160c --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_painting/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_painting/config.yml new file mode 100644 index 0000000..d5f587a --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml new file mode 100644 index 0000000..0627b1d --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_painting/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_painting/config.yml new file mode 100644 index 0000000..487a217 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_painting/config.yml b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_painting/config.yml new file mode 100644 index 0000000..fbba59d --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_painting/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..48785e1 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=painting +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..e3ab4e6 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b5.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=painting +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..67611a5 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b6.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=painting +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..3eda562 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/efficientnet_b7.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=3 + +DOMAIN=painting +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase3/painting/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..075c514 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/inceptionresnetv2.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=painting +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase3/painting/scripts/inceptionv4.sh new file mode 100644 index 0000000..a70a614 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/inceptionv4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=painting +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase3/painting/scripts/pnasnet5large.sh new file mode 100644 index 0000000..c88f140 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/pnasnet5large.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=3 + +DOMAIN=painting +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/scripts/senet154.sh b/ExtractFeat/experiments/phase3/painting/scripts/senet154.sh new file mode 100644 index 0000000..20410e8 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/scripts/senet154.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=3 + +DOMAIN=painting +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase3/painting/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase3/painting/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/senet154/senet154_painting/config.yml b/ExtractFeat/experiments/phase3/painting/senet154/senet154_painting/config.yml new file mode 100644 index 0000000..d321488 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/senet154/senet154_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase3/painting/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase3/painting/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase3/painting/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase3/painting/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase3/painting/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml new file mode 100644 index 0000000..0ff18d1 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml new file mode 100644 index 0000000..ec9996a --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml new file mode 100644 index 0000000..ef0cd9b --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml new file mode 100644 index 0000000..7f1eee9 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_clipart/config.yml @@ -0,0 +1,44 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + #TEST_CROP: [352, 352] + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml new file mode 100644 index 0000000..c119666 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_clipart/config.yml new file mode 100644 index 0000000..6d28a67 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_clipart/config.yml new file mode 100644 index 0000000..bdfe00c --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_clipart/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..fcb7a04 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=4 + +DOMAIN=clipart +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..01b71db --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b5.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=4 + +DOMAIN=clipart +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..a3b2197 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b6.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=4 + +DOMAIN=clipart +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..93b6dbd --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/efficientnet_b7.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=4 + +DOMAIN=clipart +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase4/clipart/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..00e60dc --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/inceptionresnetv2.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=4 + +DOMAIN=clipart +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase4/clipart/scripts/inceptionv4.sh new file mode 100644 index 0000000..bba60a2 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/inceptionv4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=4 + +DOMAIN=clipart +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase4/clipart/scripts/pnasnet5large.sh new file mode 100644 index 0000000..736aee9 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/pnasnet5large.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=4 + +DOMAIN=clipart +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/scripts/senet154.sh b/ExtractFeat/experiments/phase4/clipart/scripts/senet154.sh new file mode 100644 index 0000000..274999d --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/scripts/senet154.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=4 + +DOMAIN=clipart +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/clipart/senet154/senet154_clipart/config.yml b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_clipart/config.yml new file mode 100644 index 0000000..2d9b7f5 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_clipart/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'clipart' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/clipart/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase4/clipart/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml new file mode 100644 index 0000000..486edcd --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_painting/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_painting/config.yml new file mode 100644 index 0000000..450ae3f --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml new file mode 100644 index 0000000..9d5587b --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_real/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_real/config.yml new file mode 100644 index 0000000..6d88750 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml new file mode 100644 index 0000000..1f62375 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b4/efficientnet_b4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b4' + IN_DIM: 1792 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml new file mode 100644 index 0000000..7f576bf --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_painting/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_painting/config.yml new file mode 100644 index 0000000..c825faa --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml new file mode 100644 index 0000000..6b4bf1a --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_real/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_real/config.yml new file mode 100644 index 0000000..9bfc9c0 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml new file mode 100644 index 0000000..e9c56d7 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b5/efficientnet_b5_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b5' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml new file mode 100644 index 0000000..e73b923 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_painting/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_painting/config.yml new file mode 100644 index 0000000..055160c --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml new file mode 100644 index 0000000..1a0f016 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_real/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_real/config.yml new file mode 100644 index 0000000..de52001 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml new file mode 100644 index 0000000..cd9b319 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b6/efficientnet_b6_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b6' + IN_DIM: 2304 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml new file mode 100644 index 0000000..81c0fb5 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_painting/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_painting/config.yml new file mode 100644 index 0000000..d5f587a --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml new file mode 100644 index 0000000..98dc46b --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_real/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_real/config.yml new file mode 100644 index 0000000..e831d15 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml new file mode 100644 index 0000000..a33b949 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/efficientnet_b7/efficientnet_b7_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'efficientnet_b7' + IN_DIM: 2560 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml new file mode 100644 index 0000000..48d89d4 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml new file mode 100644 index 0000000..0627b1d --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml new file mode 100644 index 0000000..7c2b46a --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml new file mode 100644 index 0000000..cf797a6 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml new file mode 100644 index 0000000..d210a60 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionresnetv2/inceptionresnetv2_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionresnetv2' + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_infograph/config.yml new file mode 100644 index 0000000..0b41360 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_painting/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_painting/config.yml new file mode 100644 index 0000000..487a217 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_quickdraw/config.yml new file mode 100644 index 0000000..4eae99d --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_real/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_real/config.yml new file mode 100644 index 0000000..0606d51 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_sketch/config.yml new file mode 100644 index 0000000..94b7f68 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/inceptionv4/inceptionv4_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [395, 395] + #TEST_CROP: [363, 363] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'inceptionv4' # se_resnext50_32x4d, se_resnext101_32x4d + IN_DIM: 1536 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_infograph/config.yml new file mode 100644 index 0000000..5667e52 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_infograph/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_painting/config.yml b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_painting/config.yml new file mode 100644 index 0000000..fbba59d --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_painting/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml new file mode 100644 index 0000000..2c09945 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_quickdraw/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_real/config.yml b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_real/config.yml new file mode 100644 index 0000000..abf26c5 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_real/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_sketch/config.yml new file mode 100644 index 0000000..f0673f1 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/pnasnet5large/pnasnet5large_sketch/config.yml @@ -0,0 +1,42 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.5, 0.5, 0.5] +STD: [0.5, 0.5, 0.5] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'pnasnet5large' + IN_DIM: 4320 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b4.sh b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b4.sh new file mode 100644 index 0000000..0fa08e3 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=4 + +DOMAIN=painting +NET=efficientnet_b4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b5.sh b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b5.sh new file mode 100644 index 0000000..1a6fa38 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b5.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=4 + +DOMAIN=painting +NET=efficientnet_b5 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b6.sh b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b6.sh new file mode 100644 index 0000000..67611a5 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b6.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=19 +PHASE=3 + +DOMAIN=painting +NET=efficientnet_b6 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b7.sh b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b7.sh new file mode 100644 index 0000000..3eda562 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/efficientnet_b7.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=3 + +DOMAIN=painting +NET=efficientnet_b7 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/scripts/inceptionresnetv2.sh b/ExtractFeat/experiments/phase4/painting/scripts/inceptionresnetv2.sh new file mode 100644 index 0000000..6ec9148 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/inceptionresnetv2.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=4 + +DOMAIN=painting +NET=inceptionresnetv2 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/scripts/inceptionv4.sh b/ExtractFeat/experiments/phase4/painting/scripts/inceptionv4.sh new file mode 100644 index 0000000..7daa63b --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/inceptionv4.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=17 +PHASE=4 + +DOMAIN=painting +NET=inceptionv4 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/scripts/pnasnet5large.sh b/ExtractFeat/experiments/phase4/painting/scripts/pnasnet5large.sh new file mode 100644 index 0000000..c88f140 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/pnasnet5large.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=3 + +DOMAIN=painting +NET=pnasnet5large +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/scripts/senet154.sh b/ExtractFeat/experiments/phase4/painting/scripts/senet154.sh new file mode 100644 index 0000000..7d9bc08 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/scripts/senet154.sh @@ -0,0 +1,17 @@ +GPUID=3 +RESUME=18 +PHASE=4 + +DOMAIN=painting +NET=senet154 +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME + +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_real --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_quickdraw --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_infograph --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_sketch --resume $RESUME --mirror +CUDA_VISIBLE_DEVICES=$GPUID python3 main.py --folder ./experiments/phase$PHASE/${DOMAIN}/$NET/${NET}_${DOMAIN} --resume $RESUME --mirror diff --git a/ExtractFeat/experiments/phase4/painting/senet154/senet154_infograph/config.yml b/ExtractFeat/experiments/phase4/painting/senet154/senet154_infograph/config.yml new file mode 100644 index 0000000..ce18e3c --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/senet154/senet154_infograph/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'infograph' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/senet154/senet154_painting/config.yml b/ExtractFeat/experiments/phase4/painting/senet154/senet154_painting/config.yml new file mode 100644 index 0000000..d321488 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/senet154/senet154_painting/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'painting' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/senet154/senet154_quickdraw/config.yml b/ExtractFeat/experiments/phase4/painting/senet154/senet154_quickdraw/config.yml new file mode 100644 index 0000000..58c73a8 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/senet154/senet154_quickdraw/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'quickdraw' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/senet154/senet154_real/config.yml b/ExtractFeat/experiments/phase4/painting/senet154/senet154_real/config.yml new file mode 100644 index 0000000..b9626ee --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/senet154/senet154_real/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'real' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/experiments/phase4/painting/senet154/senet154_sketch/config.yml b/ExtractFeat/experiments/phase4/painting/senet154/senet154_sketch/config.yml new file mode 100644 index 0000000..3ed1a68 --- /dev/null +++ b/ExtractFeat/experiments/phase4/painting/senet154/senet154_sketch/config.yml @@ -0,0 +1,43 @@ +LOGGER_NAME: 'log' +SEED: 1546884941.160048 +############################ TRAIN ############################ +TRAIN: + FIX_TWO: True + +############################ TEST ############################ +TEST: + BATCH_SIZE: 32 + +############################ DATA_LOADER ############################ +DATA_LOADER: + NUM_WORKERS: 4 + SHUFFLE: True + DATA_ROOT: '../dataset/visda2019' + LIST: 'list' + FOLDER: 'sketch' + +############################ AUG ############################ +AUG: + TEST_CROP: [320, 320] + #TEST_CROP: [288, 288] + RESIZE: [0, 0] + RND_CROP: [0, 0] + + V_FLIP: 0.0 + H_FLIP: 0.5 + ROTATION: 0.0 + BRIGHTNESS: 0.0 + CONTRAST: 0.0 + SATURATION: 0.0 + HUE: 0.0 + MULTI_CROP_SIZE: 0 + +MEAN: [0.485, 0.456, 0.406] +STD: [0.229, 0.224, 0.225] + +############################ MODEL ############################ +MODEL: + CLASS_NUM: 345 + NET: 'senet154' + IN_DIM: 2048 + EMBED_DIM: 1000 diff --git a/ExtractFeat/lib/__init__.py b/ExtractFeat/lib/__init__.py new file mode 100644 index 0000000..158cdcb --- /dev/null +++ b/ExtractFeat/lib/__init__.py @@ -0,0 +1,4 @@ +# -------------------------------------------------------- +# Domain Adaptation +# Written by VARMS +# -------------------------------------------------------- \ No newline at end of file diff --git a/ExtractFeat/lib/config.py b/ExtractFeat/lib/config.py new file mode 100644 index 0000000..10d9b3c --- /dev/null +++ b/ExtractFeat/lib/config.py @@ -0,0 +1,202 @@ +import os +import os.path as osp +import numpy as np + +from easydict import EasyDict as edict + +__C = edict() +# Consumers can get config by: +# from fast_rcnn_config import cfg +cfg = __C + +# ---------------------------------------------------------------------------- # +# Training options +# ---------------------------------------------------------------------------- # +__C.TRAIN = edict() + +# Minibatch size +__C.TRAIN.BATCH_SIZE = 56 + +# Fix first two layers +__C.TRAIN.FIX_TWO = True + +__C.TRAIN.FIX_BN = False + +__C.TRAIN.FIX_ALL = False + +# ---------------------------------------------------------------------------- # +# Inference ('test') options +# ---------------------------------------------------------------------------- # +__C.TEST = edict() + +# Minibatch size +__C.TEST.BATCH_SIZE = 24 + + +# ---------------------------------------------------------------------------- # +# Data loader options +# ---------------------------------------------------------------------------- # +__C.DATA_LOADER = edict() + +# Data directory +__C.DATA_LOADER.NUM_WORKERS = 4 + +__C.DATA_LOADER.PIN_MEMORY = True + +__C.DATA_LOADER.DROP_LAST = True + +__C.DATA_LOADER.SHUFFLE = True + +__C.DATA_LOADER.DATA_ROOT = '/export1/dataset/visda2019' + +__C.DATA_LOADER.LIST = 'list' + +__C.DATA_LOADER.FOLDER = 'sketch' + +# ---------------------------------------------------------------------------- # +# Model options +# ---------------------------------------------------------------------------- # +__C.MODEL = edict() + +__C.MODEL.CLASS_NUM = 345 + +__C.MODEL.NET = 'se_resnext50_32x4d' + +__C.MODEL.IN_DIM = 2048 + +__C.MODEL.EMBED_DIM = 1000 + +# ---------------------------------------------------------------------------- # +# Augmentation options +# ---------------------------------------------------------------------------- # +__C.AUG = edict() + +# Crop Size at testing +__C.AUG.TEST_CROP = [160, 160] + +# Resize the input PIL Image to the given size +# size (sequence or int) - Desired output size. If size is a sequence +# like (h, w), output size will be matched to this. If size is an int, +# smaller edge of the image will be matched to this number. i.e, +# if height > width, then image will be rescaled to (size * height / width, size) +__C.AUG.RESIZE = [176, 176] # None + +# size (sequence or self.args.root_folderDesired output size of the crop. If size is an +# int instead of seqself.args.root_folderike (h, w), a square crop (size, size) is made. +__C.AUG.RND_CROP = [160, 160] # None + +# Vertically flip thself.args.root_folder PIL Image randomly with a given probability. +__C.AUG.V_FLIP = 0.0 + +# Horizontally flip self.args.root_folderen PIL Image randomly with a given probability. +__C.AUG.H_FLIP = 0.5 + +# degrees (sequence or float or int) - Range of degrees to select from. +# If degrees is a number instead of sequence like (min, max), the range +# of degrees will be (-degrees, +degrees) +__C.AUG.ROTATION = 0.0 + +# https://github.com/facebook/fb.resnet.torch/blob/master/datasets/imagenet.lua +# brightness (float) - How much to jitter brightness. brightness_factor +# is chosen uniformly from [max(0, 1 - brightness), 1 + brightness] +__C.AUG.BRIGHTNESS = 0.0 + +# contrast (float) - How much to jitter contrast. contrast_factor +# is chosen uniformly from [max(0, 1 - contrast), 1 + contrast] +__C.AUG.CONTRAST = 0.0 + +# saturation (float) - How much to jitter saturation. saturation_factor +# is chosen uniformly from [max(0, 1 - saturation), 1 + saturation] +__C.AUG.SATURATION = 0.0 + +# hue (float) - How much to jitter hue. hue_factor +# is chosen uniformly from [-hue, hue]. Should be >=0 and <= 0.5 +__C.AUG.HUE = 0.0 + +# Custom_transforms +__C.AUG.SCALE_RATIOS = [1, 0.875, 0.75, 0.66] +__C.AUG.MAX_DISTORT = 1 +__C.AUG.MULTI_CROP_SIZE = 0 # 0 + +# ---------------------------------------------------------------------------- # +# Misc options +# ---------------------------------------------------------------------------- # +# A small number that's used many times +__C.EPS = 1e-14 + +# Root directory of project +__C.ROOT_DIR = os.getcwd() + +# Logger name +__C.LOGGER_NAME = 'log' + +# Image Mean +__C.MEAN = [0.485, 0.456, 0.406] + +# Image std +__C.STD = [0.229, 0.224, 0.225] + +__C.SEED = -1.0 + +def _merge_a_into_b(a, b): + """Merge config dictionary a into config dictionary b, clobbering the + options in b whenever they are also specified in a. + """ + if type(a) is not edict: + return + + #for k, v in a.iteritems(): + for k, v in a.items(): # python3 + # a must specify keys that are in b + if not k in b: + raise KeyError('{} is not a valid config key'.format(k)) + + # the types must match, too + old_type = type(b[k]) + if old_type is not type(v): + if isinstance(b[k], np.ndarray): + v = np.array(v, dtype=b[k].dtype) + else: + raise ValueError(('Type mismatch ({} vs. {}) ' + 'for config key: {}').format(type(b[k]), + type(v), k)) + + # recursively merge dicts + if type(v) is edict: + try: + _merge_a_into_b(a[k], b[k]) + except: + print('Error under config key: {}'.format(k)) + raise + else: + b[k] = v + +def cfg_from_file(filename): + """Load a config file and merge it into the default options.""" + import yaml + with open(filename, 'r') as f: + yaml_cfg = edict(yaml.load(f)) + + _merge_a_into_b(yaml_cfg, __C) + +def cfg_from_list(cfg_list): + """Set config keys via list (e.g., from command line).""" + from ast import literal_eval + assert len(cfg_list) % 2 == 0 + for k, v in zip(cfg_list[0::2], cfg_list[1::2]): + key_list = k.split('.') + d = __C + for subkey in key_list[:-1]: + assert d.has_key(subkey) + d = d[subkey] + subkey = key_list[-1] + assert d.has_key(subkey) + try: + value = literal_eval(v) + except: + # handle the case when v is a string literal + value = v + assert type(value) == type(d[subkey]), \ + 'type {} does not match original type {}'.format( + type(value), type(d[subkey])) + d[subkey] = value diff --git a/ExtractFeat/lib/utils.py b/ExtractFeat/lib/utils.py new file mode 100644 index 0000000..98b221f --- /dev/null +++ b/ExtractFeat/lib/utils.py @@ -0,0 +1,88 @@ +import os +import copy +import pickle +import numpy as np +import torch +import torch.nn.functional as F +import torch.distributed as dist +from lib.config import cfg + + +def loadlines(path): + paths = [] + labels = [] + with open(path, 'r') as fid: + for line in fid: + data = line.strip().split(' ') + paths.append(data[0]) + labels.append(int(data[1])) + return paths, labels + + +def sync_labels(label): + g_labels = [torch.ones_like(label) for _ in range(dist.get_world_size())] + torch.distributed.all_gather(g_labels, label) + gf_labels = torch.cat(g_labels, dim=0) + return gf_labels + + +def sync_tensor(vec): + g_vec = [torch.ones_like(vec) for _ in range(dist.get_world_size())] + torch.distributed.all_gather(g_vec, vec) + gf_vec = vec + + for i in range(0, dist.get_rank()): + gf_vec = torch.cat((g_vec[dist.get_rank() - i - 1].detach(), gf_vec), dim=0) + + for i in range(dist.get_rank()+1, dist.get_world_size()): + gf_vec = torch.cat((gf_vec, g_vec[i].detach()), dim=0) + return gf_vec + + +def sync_tuple_tensor(vec): + g0_vec = [torch.ones_like(vec[0]) for _ in range(dist.get_world_size())] + torch.distributed.all_gather(g0_vec, vec[0]) + gf0_vec = vec[0] + + for i in range(0, dist.get_rank()): + gf0_vec = torch.cat((g0_vec[dist.get_rank() - i - 1].detach(), gf0_vec), dim=0) + + for i in range(dist.get_rank() + 1, dist.get_world_size()): + gf0_vec = torch.cat((gf0_vec, g0_vec[i].detach()), dim=0) + + g1_vec = [torch.ones_like(vec[1]) for _ in range(dist.get_world_size())] + torch.distributed.all_gather(g1_vec, vec[1]) + gf1_vec = vec[1] + + for i in range(0, dist.get_rank()): + gf1_vec = torch.cat((g1_vec[dist.get_rank() - i - 1].detach(), gf1_vec), dim=0) + + for i in range(dist.get_rank() + 1, dist.get_world_size()): + gf1_vec = torch.cat((gf1_vec, g1_vec[i].detach()), dim=0) + return (gf0_vec, gf1_vec) + + +def broadcast_tensor(vec): + torch.distributed.broadcast(vec, 0) + vec = vec.data.cpu().numpy() + return vec + + +def broadcast_numpy(vec): + vec = torch.tensor(vec, device="cuda") + torch.distributed.broadcast(vec, 0) + vec = vec.data.cpu().numpy() + return vec + + +def load_trg_plabels(): + if len(cfg.DATA_LOADER.TRG_PSEUDOLABELS) == 0: + return None, None + else: + pdata = pickle.load(open(cfg.DATA_LOADER.TRG_PSEUDOLABELS, 'rb'), encoding='bytes') + probs = pdata['probs'] + plabels = pdata['labels'] + return probs, plabels + + + diff --git a/ExtractFeat/main.py b/ExtractFeat/main.py new file mode 100644 index 0000000..941fc5a --- /dev/null +++ b/ExtractFeat/main.py @@ -0,0 +1,36 @@ +import os +import sys +import argparse +from lib.config import cfg, cfg_from_file, cfg_from_list +from trainer import Trainer + +def parse_args(): + """ + Parse input arguments + """ + parser = argparse.ArgumentParser(description='Domain Adaptation') + parser.add_argument('--folder', dest='folder', default=None, type=str) + parser.add_argument("--local_rank", type=int, default=0) + parser.add_argument("--resume", type=int, default=-1) + parser.add_argument("--mirror", action='store_true', default=False) + + if len(sys.argv) == 1: + parser.print_help() + sys.exit(1) + + args = parser.parse_args() + return args + + +if __name__ == '__main__': + args = parse_args() + print('Called with args:') + print(args) + + if args.folder is not None: + cfg_from_file(os.path.join(args.folder, 'config.yml')) + cfg.ROOT_DIR = args.folder + + trainer = Trainer(args) + + trainer.train() diff --git a/ExtractFeat/models/__init__.py b/ExtractFeat/models/__init__.py new file mode 100644 index 0000000..54ae602 --- /dev/null +++ b/ExtractFeat/models/__init__.py @@ -0,0 +1,13 @@ +# -------------------------------------------------------- +# Domain Adaptation +# Written by VARMS +# -------------------------------------------------------- + +from .classifier import * +from .senet import * +from .pnasnet import * +from .inceptionresnetv2 import * +from .inceptionv4 import * +from .efficientnet import * +from .dpn import * + diff --git a/ExtractFeat/models/classifier.py b/ExtractFeat/models/classifier.py new file mode 100644 index 0000000..ae534b8 --- /dev/null +++ b/ExtractFeat/models/classifier.py @@ -0,0 +1,44 @@ +import numpy as np +import torch +import torch.nn as nn +import torchvision +from torchvision import models +from torch.autograd import Function +import torch.nn.functional as F +import math +from lib.config import cfg + + +class FC(nn.Module): + def __init__(self, in_dim, out_dim, distributed): + super(FC, self).__init__() + self.fc = nn.Linear(in_dim, out_dim) + self.bn = nn.BatchNorm1d(out_dim, affine=True) + self.relu = nn.ReLU(inplace=True) + self.drop = nn.Dropout() + self.distributed = distributed + + def forward(self, x): + x = self.fc(x) + #if self.distributed: + # x = x.unsqueeze(-1) + x = self.bn(x) + x = self.relu(x) + x = self.drop(x) + #if self.distributed: + # x = x.squeeze(-1) + return x + + +class Classifier(nn.Module): + def __init__(self, class_num=345, distributed=False): + super(Classifier, self).__init__() + self.fc1 = FC(cfg.MODEL.IN_DIM, cfg.MODEL.EMBED_DIM, distributed) + self.fc2 = FC(cfg.MODEL.EMBED_DIM, cfg.MODEL.EMBED_DIM, distributed) + self.fc3 = nn.Linear(cfg.MODEL.EMBED_DIM, class_num) + + def forward(self, x): + fc1 = self.fc1(x) + fc2 = self.fc2(fc1) + cls_logit = self.fc3(fc2) + return fc2, cls_logit diff --git a/ExtractFeat/models/dpn.py b/ExtractFeat/models/dpn.py new file mode 100644 index 0000000..d1e72e0 --- /dev/null +++ b/ExtractFeat/models/dpn.py @@ -0,0 +1,339 @@ +""" +Code gently borrowed from +https://github.com/Cadene/pretrained-models.pytorch +""" + +""" PyTorch implementation of DualPathNetworks +Ported to PyTorch by [Ross Wightman](https://github.com/rwightman/pytorch-dpn-pretrained) +Based on original MXNet implementation https://github.com/cypw/DPNs with +many ideas from another PyTorch implementation https://github.com/oyam/pytorch-DPNs. +This implementation is compatible with the pretrained weights +from cypw's MXNet implementation. +""" +from __future__ import print_function, division, absolute_import +import os +import torch +import torch.nn as nn +import torch.nn.functional as F +import torch.utils.model_zoo as model_zoo +from collections import OrderedDict +from lib.config import cfg + +__all__ = ['DPN', 'dpn131'] + +pretrained_settings = { + 'dpn131': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/dpn131-7af84be88.pth', + 'input_space': 'RGB', + 'input_size': [3, 224, 224], + 'input_range': [0, 1], + 'mean': [124 / 255, 117 / 255, 104 / 255], + 'std': [1 / (.0167 * 255)] * 3, + 'num_classes': 1000 + } + } +} + +class CatBnAct(nn.Module): + def __init__(self, in_chs, activation_fn=nn.ReLU(inplace=True)): + super(CatBnAct, self).__init__() + self.bn = nn.BatchNorm2d(in_chs, eps=0.001) + self.act = activation_fn + + def forward(self, x): + x = torch.cat(x, dim=1) if isinstance(x, tuple) else x + return self.act(self.bn(x)) + + +class BnActConv2d(nn.Module): + def __init__(self, in_chs, out_chs, kernel_size, stride, + padding=0, groups=1, activation_fn=nn.ReLU(inplace=True)): + super(BnActConv2d, self).__init__() + self.bn = nn.BatchNorm2d(in_chs, eps=0.001) + self.act = activation_fn + self.conv = nn.Conv2d(in_chs, out_chs, kernel_size, stride, padding, groups=groups, bias=False) + + def forward(self, x): + return self.conv(self.act(self.bn(x))) + + +class InputBlock(nn.Module): + def __init__(self, num_init_features, kernel_size=7, + padding=3, activation_fn=nn.ReLU(inplace=True)): + super(InputBlock, self).__init__() + self.conv = nn.Conv2d( + 3, num_init_features, kernel_size=kernel_size, stride=2, padding=padding, bias=False) + self.bn = nn.BatchNorm2d(num_init_features, eps=0.001) + self.act = activation_fn + self.pool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1) + + def forward(self, x): + x = self.conv(x) + x = self.bn(x) + x = self.act(x) + x = self.pool(x) + return x + + +class DualPathBlock(nn.Module): + def __init__( + self, in_chs, num_1x1_a, num_3x3_b, num_1x1_c, inc, groups, block_type='normal', b=False): + super(DualPathBlock, self).__init__() + self.num_1x1_c = num_1x1_c + self.inc = inc + self.b = b + if block_type is 'proj': + self.key_stride = 1 + self.has_proj = True + elif block_type is 'down': + self.key_stride = 2 + self.has_proj = True + else: + assert block_type is 'normal' + self.key_stride = 1 + self.has_proj = False + + if self.has_proj: + # Using different member names here to allow easier parameter key matching for conversion + if self.key_stride == 2: + self.c1x1_w_s2 = BnActConv2d( + in_chs=in_chs, out_chs=num_1x1_c + 2 * inc, kernel_size=1, stride=2) + else: + self.c1x1_w_s1 = BnActConv2d( + in_chs=in_chs, out_chs=num_1x1_c + 2 * inc, kernel_size=1, stride=1) + self.c1x1_a = BnActConv2d(in_chs=in_chs, out_chs=num_1x1_a, kernel_size=1, stride=1) + self.c3x3_b = BnActConv2d( + in_chs=num_1x1_a, out_chs=num_3x3_b, kernel_size=3, + stride=self.key_stride, padding=1, groups=groups) + if b: + self.c1x1_c = CatBnAct(in_chs=num_3x3_b) + self.c1x1_c1 = nn.Conv2d(num_3x3_b, num_1x1_c, kernel_size=1, bias=False) + self.c1x1_c2 = nn.Conv2d(num_3x3_b, inc, kernel_size=1, bias=False) + else: + self.c1x1_c = BnActConv2d(in_chs=num_3x3_b, out_chs=num_1x1_c + inc, kernel_size=1, stride=1) + + def forward(self, x): + x_in = torch.cat(x, dim=1) if isinstance(x, tuple) else x + if self.has_proj: + if self.key_stride == 2: + x_s = self.c1x1_w_s2(x_in) + else: + x_s = self.c1x1_w_s1(x_in) + x_s1 = x_s[:, :self.num_1x1_c, :, :] + x_s2 = x_s[:, self.num_1x1_c:, :, :] + else: + x_s1 = x[0] + x_s2 = x[1] + x_in = self.c1x1_a(x_in) + x_in = self.c3x3_b(x_in) + if self.b: + x_in = self.c1x1_c(x_in) + out1 = self.c1x1_c1(x_in) + out2 = self.c1x1_c2(x_in) + else: + x_in = self.c1x1_c(x_in) + out1 = x_in[:, :self.num_1x1_c, :, :] + out2 = x_in[:, self.num_1x1_c:, :, :] + resid = x_s1 + out1 + dense = torch.cat([x_s2, out2], dim=1) + return resid, dense + + +class DPN(nn.Module): + def __init__(self, small=False, num_init_features=64, k_r=96, groups=32, + b=False, k_sec=(3, 4, 20, 3), inc_sec=(16, 32, 24, 128)): + super(DPN, self).__init__() + self.b = b + bw_factor = 1 if small else 4 + + blocks = OrderedDict() + + # conv1 + if small: + blocks['conv1_1'] = InputBlock(num_init_features, kernel_size=3, padding=1) + else: + blocks['conv1_1'] = InputBlock(num_init_features, kernel_size=7, padding=3) + + # conv2 + bw = 64 * bw_factor + inc = inc_sec[0] + r = (k_r * bw) // (64 * bw_factor) + blocks['conv2_1'] = DualPathBlock(num_init_features, r, r, bw, inc, groups, 'proj', b) + in_chs = bw + 3 * inc + for i in range(2, k_sec[0] + 1): + blocks['conv2_' + str(i)] = DualPathBlock(in_chs, r, r, bw, inc, groups, 'normal', b) + in_chs += inc + + # conv3 + bw = 128 * bw_factor + inc = inc_sec[1] + r = (k_r * bw) // (64 * bw_factor) + blocks['conv3_1'] = DualPathBlock(in_chs, r, r, bw, inc, groups, 'down', b) + in_chs = bw + 3 * inc + for i in range(2, k_sec[1] + 1): + blocks['conv3_' + str(i)] = DualPathBlock(in_chs, r, r, bw, inc, groups, 'normal', b) + in_chs += inc + + # conv4 + bw = 256 * bw_factor + inc = inc_sec[2] + r = (k_r * bw) // (64 * bw_factor) + blocks['conv4_1'] = DualPathBlock(in_chs, r, r, bw, inc, groups, 'down', b) + in_chs = bw + 3 * inc + for i in range(2, k_sec[2] + 1): + blocks['conv4_' + str(i)] = DualPathBlock(in_chs, r, r, bw, inc, groups, 'normal', b) + in_chs += inc + + # conv5 + bw = 512 * bw_factor + inc = inc_sec[3] + r = (k_r * bw) // (64 * bw_factor) + blocks['conv5_1'] = DualPathBlock(in_chs, r, r, bw, inc, groups, 'down', b) + in_chs = bw + 3 * inc + for i in range(2, k_sec[3] + 1): + blocks['conv5_' + str(i)] = DualPathBlock(in_chs, r, r, bw, inc, groups, 'normal', b) + in_chs += inc + blocks['conv5_bn_ac'] = CatBnAct(in_chs) + + self.features = nn.Sequential(blocks) + self.avg_pool = nn.AdaptiveAvgPool2d((1,1)) + + if cfg.TRAIN.FIX_TWO: + self._freeze_backbone() + + if cfg.TRAIN.FIX_BN: + self._freeze_bn_param() + + if cfg.TRAIN.FIX_ALL: + self._freeze_all() + + def freeze_bn(self): + '''Freeze BatchNorm layers.''' + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.eval() + + def _freeze_backbone(self): + m = self.features[0] + for p in m.parameters(): + p.requires_grad = False + #m = self.features[1] + #for p in m.parameters(): + # p.requires_grad = False + + def _freeze_all(self): + for p in self.parameters(): + p.requires_grad = False + + def _freeze_bn_param(self): + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.weight.requires_grad = False + layer.bias.requires_grad = False + + + def forward(self, input): + res5c = self.features(input) + x = self.avg_pool(res5c).view(res5c.size(0), -1) + return res5c, x + + +""" PyTorch selectable adaptive pooling +Adaptive pooling with the ability to select the type of pooling from: + * 'avg' - Average pooling + * 'max' - Max pooling + * 'avgmax' - Sum of average and max pooling re-scaled by 0.5 + * 'avgmaxc' - Concatenation of average and max pooling along feature dim, doubles feature dim +Both a functional and a nn.Module version of the pooling is provided. +Author: Ross Wightman (rwightman) +""" + +def pooling_factor(pool_type='avg'): + return 2 if pool_type == 'avgmaxc' else 1 + + +def adaptive_avgmax_pool2d(x, pool_type='avg', padding=0, count_include_pad=False): + """Selectable global pooling function with dynamic input kernel size + """ + if pool_type == 'avgmaxc': + x = torch.cat([ + F.avg_pool2d( + x, kernel_size=(x.size(2), x.size(3)), padding=padding, count_include_pad=count_include_pad), + F.max_pool2d(x, kernel_size=(x.size(2), x.size(3)), padding=padding) + ], dim=1) + elif pool_type == 'avgmax': + x_avg = F.avg_pool2d( + x, kernel_size=(x.size(2), x.size(3)), padding=padding, count_include_pad=count_include_pad) + x_max = F.max_pool2d(x, kernel_size=(x.size(2), x.size(3)), padding=padding) + x = 0.5 * (x_avg + x_max) + elif pool_type == 'max': + x = F.max_pool2d(x, kernel_size=(x.size(2), x.size(3)), padding=padding) + else: + if pool_type != 'avg': + print('Invalid pool type %s specified. Defaulting to average pooling.' % pool_type) + x = F.avg_pool2d( + x, kernel_size=(x.size(2), x.size(3)), padding=padding, count_include_pad=count_include_pad) + return x + + +class AdaptiveAvgMaxPool2d(torch.nn.Module): + """Selectable global pooling layer with dynamic input kernel size + """ + def __init__(self, output_size=1, pool_type='avg'): + super(AdaptiveAvgMaxPool2d, self).__init__() + self.output_size = output_size + self.pool_type = pool_type + if pool_type == 'avgmaxc' or pool_type == 'avgmax': + self.pool = nn.ModuleList([nn.AdaptiveAvgPool2d(output_size), nn.AdaptiveMaxPool2d(output_size)]) + elif pool_type == 'max': + self.pool = nn.AdaptiveMaxPool2d(output_size) + else: + if pool_type != 'avg': + print('Invalid pool type %s specified. Defaulting to average pooling.' % pool_type) + self.pool = nn.AdaptiveAvgPool2d(output_size) + + def forward(self, x): + if self.pool_type == 'avgmaxc': + x = torch.cat([p(x) for p in self.pool], dim=1) + elif self.pool_type == 'avgmax': + x = 0.5 * torch.sum(torch.stack([p(x) for p in self.pool]), 0).squeeze(dim=0) + else: + x = self.pool(x) + return x + + def factor(self): + return pooling_factor(self.pool_type) + + def __repr__(self): + return self.__class__.__name__ + ' (' \ + + 'output_size=' + str(self.output_size) \ + + ', pool_type=' + self.pool_type + ')' + + +def initialize_pretrained_model(model, settings): + state_dict = model_zoo.load_url(settings['url']) + current_state = model.state_dict() + keys = list(state_dict.keys()) + + for key in keys: + if not key.startswith('last_linear.'): + current_state[key] = state_dict[key] + + model.load_state_dict(current_state) + + model.input_space = settings['input_space'] + model.input_size = settings['input_size'] + model.input_range = settings['input_range'] + model.mean = settings['mean'] + model.std = settings['std'] + + +def dpn131(pretrained=False, **kwargs): + model = DPN( + num_init_features=128, k_r=160, groups=40, + k_sec=(4, 8, 28, 3), inc_sec=(16, 32, 32, 128)) + if pretrained == True: + settings = pretrained_settings['dpn131']['imagenet'] + initialize_pretrained_model(model, settings) + return model diff --git a/ExtractFeat/models/efficientnet.py b/ExtractFeat/models/efficientnet.py new file mode 100644 index 0000000..cc4198c --- /dev/null +++ b/ExtractFeat/models/efficientnet.py @@ -0,0 +1,551 @@ +""" +Code gently borrowed from +https://github.com/lukemelas/EfficientNet-PyTorch +""" + +import re +import math +import collections +from functools import partial +import torch +from torch.utils import model_zoo +from torch import nn +from torch.nn import functional as F +from lib.config import cfg + +__all__ = ['efficientnet_b7', 'efficientnet_b6', 'efficientnet_b5', 'efficientnet_b4', 'efficientnet_b3', 'efficientnet_b2', 'efficientnet_b1', 'efficientnet_b0'] + +url_map = { + 'efficientnet-b0': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b0-355c32eb.pth', + 'efficientnet-b1': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b1-f1951068.pth', + 'efficientnet-b2': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b2-8bb594d6.pth', + 'efficientnet-b3': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b3-5fb5a3c3.pth', + 'efficientnet-b4': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b4-6ed6700e.pth', + 'efficientnet-b5': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b5-b6417697.pth', + 'efficientnet-b6': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b6-c76e70fd.pth', + 'efficientnet-b7': 'http://storage.googleapis.com/public-models/efficientnet/efficientnet-b7-dcc49843.pth', +} + +# Parameters for the entire model (stem, all blocks, and head) +GlobalParams = collections.namedtuple('GlobalParams', [ + 'batch_norm_momentum', 'batch_norm_epsilon', 'dropout_rate', + 'num_classes', 'width_coefficient', 'depth_coefficient', + 'depth_divisor', 'min_depth', 'drop_connect_rate', 'image_size']) + + +# Parameters for an individual model block +BlockArgs = collections.namedtuple('BlockArgs', [ + 'kernel_size', 'num_repeat', 'input_filters', 'output_filters', + 'expand_ratio', 'id_skip', 'stride', 'se_ratio']) + + +# Change namedtuple defaults +GlobalParams.__new__.__defaults__ = (None,) * len(GlobalParams._fields) +BlockArgs.__new__.__defaults__ = (None,) * len(BlockArgs._fields) + + +def relu_fn(x): + """ Swish activation function """ + return x * torch.sigmoid(x) + +def round_filters(filters, global_params): + """ Calculate and round number of filters based on depth multiplier. """ + multiplier = global_params.width_coefficient + if not multiplier: + return filters + divisor = global_params.depth_divisor + min_depth = global_params.min_depth + filters *= multiplier + min_depth = min_depth or divisor + new_filters = max(min_depth, int(filters + divisor / 2) // divisor * divisor) + if new_filters < 0.9 * filters: # prevent rounding by more than 10% + new_filters += divisor + return int(new_filters) + +def round_repeats(repeats, global_params): + """ Round number of filters based on depth multiplier. """ + multiplier = global_params.depth_coefficient + if not multiplier: + return repeats + return int(math.ceil(multiplier * repeats)) + +def drop_connect(inputs, p, training): + """ Drop connect. """ + if not training: return inputs + batch_size = inputs.shape[0] + keep_prob = 1 - p + random_tensor = keep_prob + random_tensor += torch.rand([batch_size, 1, 1, 1], dtype=inputs.dtype, device=inputs.device) + binary_tensor = torch.floor(random_tensor) + output = inputs / keep_prob * binary_tensor + return output + +class Conv2dDynamicSamePadding(nn.Conv2d): + """ 2D Convolutions like TensorFlow, for a dynamic image size """ + def __init__(self, in_channels, out_channels, kernel_size, stride=1, dilation=1, groups=1, bias=True): + super().__init__(in_channels, out_channels, kernel_size, stride, 0, dilation, groups, bias) + self.stride = self.stride if len(self.stride) == 2 else [self.stride[0]]*2 + + def forward(self, x): + ih, iw = x.size()[-2:] + kh, kw = self.weight.size()[-2:] + sh, sw = self.stride + oh, ow = math.ceil(ih / sh), math.ceil(iw / sw) + pad_h = max((oh - 1) * self.stride[0] + (kh - 1) * self.dilation[0] + 1 - ih, 0) + pad_w = max((ow - 1) * self.stride[1] + (kw - 1) * self.dilation[1] + 1 - iw, 0) + if pad_h > 0 or pad_w > 0: + x = F.pad(x, [pad_w//2, pad_w - pad_w//2, pad_h//2, pad_h - pad_h//2]) + return F.conv2d(x, self.weight, self.bias, self.stride, self.padding, self.dilation, self.groups) + + +class Conv2dStaticSamePadding(nn.Conv2d): + """ 2D Convolutions like TensorFlow, for a fixed image size""" + def __init__(self, in_channels, out_channels, kernel_size, image_size=None, **kwargs): + super().__init__(in_channels, out_channels, kernel_size, **kwargs) + self.stride = self.stride if len(self.stride) == 2 else [self.stride[0]] * 2 + + # Calculate padding based on image size and save it + assert image_size is not None + ih, iw = image_size if type(image_size) == list else [image_size, image_size] + kh, kw = self.weight.size()[-2:] + sh, sw = self.stride + oh, ow = math.ceil(ih / sh), math.ceil(iw / sw) + pad_h = max((oh - 1) * self.stride[0] + (kh - 1) * self.dilation[0] + 1 - ih, 0) + pad_w = max((ow - 1) * self.stride[1] + (kw - 1) * self.dilation[1] + 1 - iw, 0) + if pad_h > 0 or pad_w > 0: + self.static_padding = nn.ZeroPad2d((pad_w // 2, pad_w - pad_w // 2, pad_h // 2, pad_h - pad_h // 2)) + else: + self.static_padding = Identity() + + def forward(self, x): + x = self.static_padding(x) + x = F.conv2d(x, self.weight, self.bias, self.stride, self.padding, self.dilation, self.groups) + return x + +def get_same_padding_conv2d(image_size=None): + """ Chooses static padding if you have specified an image size, and dynamic padding otherwise. + Static padding is necessary for ONNX exporting of models. """ + if image_size is None: + return Conv2dDynamicSamePadding + else: + return partial(Conv2dStaticSamePadding, image_size=image_size) + +def get_model_params(model_name, override_params): + """ Get the block args and global params for a given model """ + if model_name.startswith('efficientnet'): + w, d, s, p = efficientnet_params(model_name) + # note: all models have drop connect rate = 0.2 + blocks_args, global_params = efficientnet( + width_coefficient=w, depth_coefficient=d, dropout_rate=p, image_size=s) + else: + raise NotImplementedError('model name is not pre-defined: %s' % model_name) + if override_params: + # ValueError will be raised here if override_params has fields not included in global_params. + global_params = global_params._replace(**override_params) + return blocks_args, global_params + +def efficientnet_params(model_name): + """ Map EfficientNet model name to parameter coefficients. """ + params_dict = { + # Coefficients: width,depth,res,dropout + 'efficientnet-b0': (1.0, 1.0, 224, 0.2), + 'efficientnet-b1': (1.0, 1.1, 240, 0.2), + 'efficientnet-b2': (1.1, 1.2, 260, 0.3), + 'efficientnet-b3': (1.2, 1.4, 300, 0.3), + 'efficientnet-b4': (1.4, 1.8, 380, 0.4), + 'efficientnet-b5': (1.6, 2.2, 456, 0.4), + 'efficientnet-b6': (1.8, 2.6, 528, 0.5), + 'efficientnet-b7': (2.0, 3.1, 600, 0.5), + } + return params_dict[model_name] + +def load_pretrained_weights(model, model_name, load_fc=True): + load_fc = False + """ Loads pretrained weights, and downloads if loading for the first time. """ + state_dict = model_zoo.load_url(url_map[model_name]) + if load_fc: + model.load_state_dict(state_dict) + else: + state_dict.pop('_fc.weight') + state_dict.pop('_fc.bias') + res = model.load_state_dict(state_dict, strict=False) + #assert str(res.missing_keys) == str(['_fc.weight', '_fc.bias']), 'issue loading pretrained weights' + print('Loaded pretrained weights for {}'.format(model_name)) + +class BlockDecoder(object): + """ Block Decoder for readability, straight from the official TensorFlow repository """ + + @staticmethod + def _decode_block_string(block_string): + """ Gets a block through a string notation of arguments. """ + assert isinstance(block_string, str) + + ops = block_string.split('_') + options = {} + for op in ops: + splits = re.split(r'(\d.*)', op) + if len(splits) >= 2: + key, value = splits[:2] + options[key] = value + + # Check stride + assert (('s' in options and len(options['s']) == 1) or + (len(options['s']) == 2 and options['s'][0] == options['s'][1])) + + return BlockArgs( + kernel_size=int(options['k']), + num_repeat=int(options['r']), + input_filters=int(options['i']), + output_filters=int(options['o']), + expand_ratio=int(options['e']), + id_skip=('noskip' not in block_string), + se_ratio=float(options['se']) if 'se' in options else None, + stride=[int(options['s'][0])]) + + @staticmethod + def _encode_block_string(block): + """Encodes a block to a string.""" + args = [ + 'r%d' % block.num_repeat, + 'k%d' % block.kernel_size, + 's%d%d' % (block.strides[0], block.strides[1]), + 'e%s' % block.expand_ratio, + 'i%d' % block.input_filters, + 'o%d' % block.output_filters + ] + if 0 < block.se_ratio <= 1: + args.append('se%s' % block.se_ratio) + if block.id_skip is False: + args.append('noskip') + return '_'.join(args) + + @staticmethod + def decode(string_list): + """ + Decodes a list of string notations to specify blocks inside the network. + + :param string_list: a list of strings, each string is a notation of block + :return: a list of BlockArgs namedtuples of block args + """ + assert isinstance(string_list, list) + blocks_args = [] + for block_string in string_list: + blocks_args.append(BlockDecoder._decode_block_string(block_string)) + return blocks_args + + @staticmethod + def encode(blocks_args): + """ + Encodes a list of BlockArgs to a list of strings. + + :param blocks_args: a list of BlockArgs namedtuples of block args + :return: a list of strings, each string is a notation of block + """ + block_strings = [] + for block in blocks_args: + block_strings.append(BlockDecoder._encode_block_string(block)) + return block_strings + +class Identity(nn.Module): + def __init__(self,): + super(Identity, self).__init__() + + def forward(self, input): + return input + +def efficientnet(width_coefficient=None, depth_coefficient=None, dropout_rate=0.2, + drop_connect_rate=0.2, image_size=None, num_classes=1000): + """ Creates a efficientnet model. """ + + blocks_args = [ + 'r1_k3_s11_e1_i32_o16_se0.25', 'r2_k3_s22_e6_i16_o24_se0.25', + 'r2_k5_s22_e6_i24_o40_se0.25', 'r3_k3_s22_e6_i40_o80_se0.25', + 'r3_k5_s11_e6_i80_o112_se0.25', 'r4_k5_s22_e6_i112_o192_se0.25', + 'r1_k3_s11_e6_i192_o320_se0.25', + ] + blocks_args = BlockDecoder.decode(blocks_args) + + global_params = GlobalParams( + batch_norm_momentum=0.99, + batch_norm_epsilon=1e-3, + dropout_rate=dropout_rate, + drop_connect_rate=drop_connect_rate, + # data_format='channels_last', # removed, this is always true in PyTorch + num_classes=num_classes, + width_coefficient=width_coefficient, + depth_coefficient=depth_coefficient, + depth_divisor=8, + min_depth=None, + image_size=image_size, + ) + + return blocks_args, global_params + + + +class MBConvBlock(nn.Module): + """ + Mobile Inverted Residual Bottleneck Block + + Args: + block_args (namedtuple): BlockArgs, see above + global_params (namedtuple): GlobalParam, see above + + Attributes: + has_se (bool): Whether the block contains a Squeeze and Excitation layer. + """ + + def __init__(self, block_args, global_params): + super().__init__() + self._block_args = block_args + self._bn_mom = 1 - global_params.batch_norm_momentum + self._bn_eps = global_params.batch_norm_epsilon + self.has_se = (self._block_args.se_ratio is not None) and (0 < self._block_args.se_ratio <= 1) + self.id_skip = block_args.id_skip # skip connection and drop connect + + # Get static or dynamic convolution depending on image size + Conv2d = get_same_padding_conv2d(image_size=global_params.image_size) + + # Expansion phase + inp = self._block_args.input_filters # number of input channels + oup = self._block_args.input_filters * self._block_args.expand_ratio # number of output channels + if self._block_args.expand_ratio != 1: + self._expand_conv = Conv2d(in_channels=inp, out_channels=oup, kernel_size=1, bias=False) + self._bn0 = nn.BatchNorm2d(num_features=oup, momentum=self._bn_mom, eps=self._bn_eps) + + # Depthwise convolution phase + k = self._block_args.kernel_size + s = self._block_args.stride + self._depthwise_conv = Conv2d( + in_channels=oup, out_channels=oup, groups=oup, # groups makes it depthwise + kernel_size=k, stride=s, bias=False) + self._bn1 = nn.BatchNorm2d(num_features=oup, momentum=self._bn_mom, eps=self._bn_eps) + + # Squeeze and Excitation layer, if desired + if self.has_se: + num_squeezed_channels = max(1, int(self._block_args.input_filters * self._block_args.se_ratio)) + self._se_reduce = Conv2d(in_channels=oup, out_channels=num_squeezed_channels, kernel_size=1) + self._se_expand = Conv2d(in_channels=num_squeezed_channels, out_channels=oup, kernel_size=1) + + # Output phase + final_oup = self._block_args.output_filters + self._project_conv = Conv2d(in_channels=oup, out_channels=final_oup, kernel_size=1, bias=False) + self._bn2 = nn.BatchNorm2d(num_features=final_oup, momentum=self._bn_mom, eps=self._bn_eps) + + def forward(self, inputs, drop_connect_rate=None): + """ + :param inputs: input tensor + :param drop_connect_rate: drop connect rate (float, between 0 and 1) + :return: output of block + """ + + # Expansion and Depthwise Convolution + x = inputs + if self._block_args.expand_ratio != 1: + x = relu_fn(self._bn0(self._expand_conv(inputs))) + x = relu_fn(self._bn1(self._depthwise_conv(x))) + + # Squeeze and Excitation + if self.has_se: + x_squeezed = F.adaptive_avg_pool2d(x, 1) + x_squeezed = self._se_expand(relu_fn(self._se_reduce(x_squeezed))) + x = torch.sigmoid(x_squeezed) * x + + x = self._bn2(self._project_conv(x)) + + # Skip connection and drop connect + input_filters, output_filters = self._block_args.input_filters, self._block_args.output_filters + if self.id_skip and self._block_args.stride == 1 and input_filters == output_filters: + if drop_connect_rate: + x = drop_connect(x, p=drop_connect_rate, training=self.training) + x = x + inputs # skip connection + return x + + +class EfficientNet(nn.Module): + """ + An EfficientNet model. Most easily loaded with the .from_name or .from_pretrained methods + + Args: + blocks_args (list): A list of BlockArgs to construct blocks + global_params (namedtuple): A set of GlobalParams shared between blocks + + Example: + model = EfficientNet.from_pretrained('efficientnet-b0') + + """ + + def __init__(self, blocks_args=None, global_params=None): + super().__init__() + assert isinstance(blocks_args, list), 'blocks_args should be a list' + assert len(blocks_args) > 0, 'block args must be greater than 0' + self._global_params = global_params + self._blocks_args = blocks_args + + # Get static or dynamic convolution depending on image size + Conv2d = get_same_padding_conv2d(image_size=global_params.image_size) + + # Batch norm parameters + bn_mom = 1 - self._global_params.batch_norm_momentum + bn_eps = self._global_params.batch_norm_epsilon + + # Stem + in_channels = 3 # rgb + out_channels = round_filters(32, self._global_params) # number of output channels + self._conv_stem = Conv2d(in_channels, out_channels, kernel_size=3, stride=2, bias=False) + self._bn0 = nn.BatchNorm2d(num_features=out_channels, momentum=bn_mom, eps=bn_eps) + + # Build blocks + self._blocks = nn.ModuleList([]) + for block_args in self._blocks_args: + + # Update block input and output filters based on depth multiplier. + block_args = block_args._replace( + input_filters=round_filters(block_args.input_filters, self._global_params), + output_filters=round_filters(block_args.output_filters, self._global_params), + num_repeat=round_repeats(block_args.num_repeat, self._global_params) + ) + + # The first block needs to take care of stride and filter size increase. + self._blocks.append(MBConvBlock(block_args, self._global_params)) + if block_args.num_repeat > 1: + block_args = block_args._replace(input_filters=block_args.output_filters, stride=1) + for _ in range(block_args.num_repeat - 1): + self._blocks.append(MBConvBlock(block_args, self._global_params)) + + # Head + in_channels = block_args.output_filters # output of final block + out_channels = round_filters(1280, self._global_params) + self._conv_head = Conv2d(in_channels, out_channels, kernel_size=1, bias=False) + self._bn1 = nn.BatchNorm2d(num_features=out_channels, momentum=bn_mom, eps=bn_eps) + + # Final linear layer + #self._dropout = self._global_params.dropout_rate + #self._fc = nn.Linear(out_channels, self._global_params.num_classes) + + if cfg.TRAIN.FIX_TWO: + self._freeze_backbone() + + if cfg.TRAIN.FIX_BN: + self._freeze_bn_param() + + if cfg.TRAIN.FIX_ALL: + self._freeze_all() + + def freeze_bn(self): + '''Freeze BatchNorm layers.''' + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.eval() + + def _freeze_backbone(self): + m = getattr(self, "_conv_stem") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "_bn0") + for p in m.parameters(): + p.requires_grad = False + m = self._blocks[0] + for p in m.parameters(): + p.requires_grad = False + + def _freeze_all(self): + for p in self.parameters(): + p.requires_grad = False + + def _freeze_bn_param(self): + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.weight.requires_grad = False + layer.bias.requires_grad = False + + def extract_features(self, inputs): + """ Returns output of the final convolution layer """ + + # Stem + x = relu_fn(self._bn0(self._conv_stem(inputs))) + + # Blocks + for idx, block in enumerate(self._blocks): + drop_connect_rate = self._global_params.drop_connect_rate + if drop_connect_rate: + drop_connect_rate *= float(idx) / len(self._blocks) + x = block(x, drop_connect_rate=drop_connect_rate) + + # Head + x = relu_fn(self._bn1(self._conv_head(x))) + + return x + + def forward(self, inputs): + """ Calls extract_features to extract features, applies final linear layer, and returns logits. """ + + # Convolution layers + res5c = self.extract_features(inputs) + + ## Pooling and final linear layer + x = F.adaptive_avg_pool2d(res5c, 1).squeeze(-1).squeeze(-1) + #if self._dropout: + # x = F.dropout(x, p=self._dropout, training=self.training) + #x = self._fc(x) + return res5c, x + + @classmethod + def from_name(cls, model_name, override_params=None): + cls._check_model_name_is_valid(model_name) + blocks_args, global_params = get_model_params(model_name, override_params) + return EfficientNet(blocks_args, global_params) + + @classmethod + def from_pretrained(cls, model_name, num_classes=1000): + model = EfficientNet.from_name(model_name, override_params={'num_classes': num_classes}) + load_pretrained_weights(model, model_name, load_fc=(num_classes == 1000)) + return model + + @classmethod + def get_image_size(cls, model_name): + cls._check_model_name_is_valid(model_name) + _, _, res, _ = efficientnet_params(model_name) + return res + + @classmethod + def _check_model_name_is_valid(cls, model_name, also_need_pretrained_weights=False): + """ Validates model name. None that pretrained weights are only available for + the first four models (efficientnet-b{i} for i in 0,1,2,3) at the moment. """ + num_models = 4 if also_need_pretrained_weights else 8 + valid_models = ['efficientnet_b'+str(i) for i in range(num_models)] + if model_name.replace('-','_') not in valid_models: + raise ValueError('model_name should be one of: ' + ', '.join(valid_models)) + + +def efficientnet_b7(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b7') + return model + +def efficientnet_b6(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b6') + return model + +def efficientnet_b5(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b5') + return model + +def efficientnet_b4(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b4') + return model + +def efficientnet_b3(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b3') + return model + +def efficientnet_b2(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b2') + return model + +def efficientnet_b1(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b1') + return model + +def efficientnet_b0(pretrained=False, **kwargs): + model = EfficientNet.from_pretrained('efficientnet-b0') + return model diff --git a/ExtractFeat/models/inceptionresnetv2.py b/ExtractFeat/models/inceptionresnetv2.py new file mode 100644 index 0000000..5718a5e --- /dev/null +++ b/ExtractFeat/models/inceptionresnetv2.py @@ -0,0 +1,390 @@ +""" +Code gently borrowed from +https://github.com/Cadene/pretrained-models.pytorch +""" + +from __future__ import print_function, division, absolute_import +import torch +import torch.nn as nn +import torch.utils.model_zoo as model_zoo +import os +import sys +from lib.config import cfg + +__all__ = ['InceptionResNetV2', 'inceptionresnetv2'] + +pretrained_settings = { + 'inceptionresnetv2': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/inceptionresnetv2-520b38e4.pth', + 'input_space': 'RGB', + 'input_size': [3, 299, 299], + 'input_range': [0, 1], + 'mean': [0.5, 0.5, 0.5], + 'std': [0.5, 0.5, 0.5], + 'num_classes': 1000 + }, + 'imagenet+background': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/inceptionresnetv2-520b38e4.pth', + 'input_space': 'RGB', + 'input_size': [3, 299, 299], + 'input_range': [0, 1], + 'mean': [0.5, 0.5, 0.5], + 'std': [0.5, 0.5, 0.5], + 'num_classes': 1001 + } + } +} + + +class BasicConv2d(nn.Module): + + def __init__(self, in_planes, out_planes, kernel_size, stride, padding=0): + super(BasicConv2d, self).__init__() + self.conv = nn.Conv2d(in_planes, out_planes, + kernel_size=kernel_size, stride=stride, + padding=padding, bias=False) # verify bias false + self.bn = nn.BatchNorm2d(out_planes, + eps=0.001, # value found in tensorflow + momentum=0.1, # default pytorch value + affine=True) + self.relu = nn.ReLU(inplace=False) + + def forward(self, x): + x = self.conv(x) + x = self.bn(x) + x = self.relu(x) + return x + + +class Mixed_5b(nn.Module): + + def __init__(self): + super(Mixed_5b, self).__init__() + + self.branch0 = BasicConv2d(192, 96, kernel_size=1, stride=1) + + self.branch1 = nn.Sequential( + BasicConv2d(192, 48, kernel_size=1, stride=1), + BasicConv2d(48, 64, kernel_size=5, stride=1, padding=2) + ) + + self.branch2 = nn.Sequential( + BasicConv2d(192, 64, kernel_size=1, stride=1), + BasicConv2d(64, 96, kernel_size=3, stride=1, padding=1), + BasicConv2d(96, 96, kernel_size=3, stride=1, padding=1) + ) + + self.branch3 = nn.Sequential( + nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False), + BasicConv2d(192, 64, kernel_size=1, stride=1) + ) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + x3 = self.branch3(x) + out = torch.cat((x0, x1, x2, x3), 1) + return out + + +class Block35(nn.Module): + + def __init__(self, scale=1.0): + super(Block35, self).__init__() + + self.scale = scale + + self.branch0 = BasicConv2d(320, 32, kernel_size=1, stride=1) + + self.branch1 = nn.Sequential( + BasicConv2d(320, 32, kernel_size=1, stride=1), + BasicConv2d(32, 32, kernel_size=3, stride=1, padding=1) + ) + + self.branch2 = nn.Sequential( + BasicConv2d(320, 32, kernel_size=1, stride=1), + BasicConv2d(32, 48, kernel_size=3, stride=1, padding=1), + BasicConv2d(48, 64, kernel_size=3, stride=1, padding=1) + ) + + self.conv2d = nn.Conv2d(128, 320, kernel_size=1, stride=1) + self.relu = nn.ReLU(inplace=False) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + out = torch.cat((x0, x1, x2), 1) + out = self.conv2d(out) + out = out * self.scale + x + out = self.relu(out) + return out + + +class Mixed_6a(nn.Module): + + def __init__(self): + super(Mixed_6a, self).__init__() + + self.branch0 = BasicConv2d(320, 384, kernel_size=3, stride=2) + + self.branch1 = nn.Sequential( + BasicConv2d(320, 256, kernel_size=1, stride=1), + BasicConv2d(256, 256, kernel_size=3, stride=1, padding=1), + BasicConv2d(256, 384, kernel_size=3, stride=2) + ) + + self.branch2 = nn.MaxPool2d(3, stride=2) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + out = torch.cat((x0, x1, x2), 1) + return out + + +class Block17(nn.Module): + + def __init__(self, scale=1.0): + super(Block17, self).__init__() + + self.scale = scale + + self.branch0 = BasicConv2d(1088, 192, kernel_size=1, stride=1) + + self.branch1 = nn.Sequential( + BasicConv2d(1088, 128, kernel_size=1, stride=1), + BasicConv2d(128, 160, kernel_size=(1,7), stride=1, padding=(0,3)), + BasicConv2d(160, 192, kernel_size=(7,1), stride=1, padding=(3,0)) + ) + + self.conv2d = nn.Conv2d(384, 1088, kernel_size=1, stride=1) + self.relu = nn.ReLU(inplace=False) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + out = torch.cat((x0, x1), 1) + out = self.conv2d(out) + out = out * self.scale + x + out = self.relu(out) + return out + + +class Mixed_7a(nn.Module): + + def __init__(self): + super(Mixed_7a, self).__init__() + + self.branch0 = nn.Sequential( + BasicConv2d(1088, 256, kernel_size=1, stride=1), + BasicConv2d(256, 384, kernel_size=3, stride=2) + ) + + self.branch1 = nn.Sequential( + BasicConv2d(1088, 256, kernel_size=1, stride=1), + BasicConv2d(256, 288, kernel_size=3, stride=2) + ) + + self.branch2 = nn.Sequential( + BasicConv2d(1088, 256, kernel_size=1, stride=1), + BasicConv2d(256, 288, kernel_size=3, stride=1, padding=1), + BasicConv2d(288, 320, kernel_size=3, stride=2) + ) + + self.branch3 = nn.MaxPool2d(3, stride=2) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + x3 = self.branch3(x) + out = torch.cat((x0, x1, x2, x3), 1) + return out + + +class Block8(nn.Module): + + def __init__(self, scale=1.0, noReLU=False): + super(Block8, self).__init__() + + self.scale = scale + self.noReLU = noReLU + + self.branch0 = BasicConv2d(2080, 192, kernel_size=1, stride=1) + + self.branch1 = nn.Sequential( + BasicConv2d(2080, 192, kernel_size=1, stride=1), + BasicConv2d(192, 224, kernel_size=(1,3), stride=1, padding=(0,1)), + BasicConv2d(224, 256, kernel_size=(3,1), stride=1, padding=(1,0)) + ) + + self.conv2d = nn.Conv2d(448, 2080, kernel_size=1, stride=1) + if not self.noReLU: + self.relu = nn.ReLU(inplace=False) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + out = torch.cat((x0, x1), 1) + out = self.conv2d(out) + out = out * self.scale + x + if not self.noReLU: + out = self.relu(out) + return out + + +class InceptionResNetV2(nn.Module): + + def __init__(self): + super(InceptionResNetV2, self).__init__() + # Special attributs + self.input_space = None + self.input_size = (299, 299, 3) + self.mean = None + self.std = None + # Modules + self.conv2d_1a = BasicConv2d(3, 32, kernel_size=3, stride=2) + self.conv2d_2a = BasicConv2d(32, 32, kernel_size=3, stride=1) + self.conv2d_2b = BasicConv2d(32, 64, kernel_size=3, stride=1, padding=1) + self.maxpool_3a = nn.MaxPool2d(3, stride=2) + self.conv2d_3b = BasicConv2d(64, 80, kernel_size=1, stride=1) + self.conv2d_4a = BasicConv2d(80, 192, kernel_size=3, stride=1) + self.maxpool_5a = nn.MaxPool2d(3, stride=2) + self.mixed_5b = Mixed_5b() + self.repeat = nn.Sequential( + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17), + Block35(scale=0.17) + ) + self.mixed_6a = Mixed_6a() + self.repeat_1 = nn.Sequential( + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10), + Block17(scale=0.10) + ) + self.mixed_7a = Mixed_7a() + self.repeat_2 = nn.Sequential( + Block8(scale=0.20), + Block8(scale=0.20), + Block8(scale=0.20), + Block8(scale=0.20), + Block8(scale=0.20), + Block8(scale=0.20), + Block8(scale=0.20), + Block8(scale=0.20), + Block8(scale=0.20) + ) + self.block8 = Block8(noReLU=True) + self.conv2d_7b = BasicConv2d(2080, 1536, kernel_size=1, stride=1) + self.avg_pool = nn.AdaptiveAvgPool2d((1,1)) + + if cfg.TRAIN.FIX_TWO: + self._freeze_backbone() + + if cfg.TRAIN.FIX_BN: + self._freeze_bn_param() + + if cfg.TRAIN.FIX_ALL: + self._freeze_all() + + def freeze_bn(self): + '''Freeze BatchNorm layers.''' + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.eval() + + def _freeze_backbone(self): + m = getattr(self, "conv2d_1a") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "conv2d_2a") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "conv2d_2b") + for p in m.parameters(): + p.requires_grad = False + + def _freeze_all(self): + for p in self.parameters(): + p.requires_grad = False + + def _freeze_bn_param(self): + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.weight.requires_grad = False + layer.bias.requires_grad = False + + def features(self, input): + x = self.conv2d_1a(input) + x = self.conv2d_2a(x) + x = self.conv2d_2b(x) + x = self.maxpool_3a(x) + x = self.conv2d_3b(x) + x = self.conv2d_4a(x) + x = self.maxpool_5a(x) + x = self.mixed_5b(x) + x = self.repeat(x) + x = self.mixed_6a(x) + x = self.repeat_1(x) + x = self.mixed_7a(x) + x = self.repeat_2(x) + x = self.block8(x) + x = self.conv2d_7b(x) + return x + + def forward(self, input): + res5c = self.features(input) + x = self.avg_pool(res5c).view(res5c.size(0), -1) + return res5c, x + +def initialize_pretrained_model(model, settings): + state_dict = model_zoo.load_url(settings['url']) + current_state = model.state_dict() + keys = list(state_dict.keys()) + + for key in keys: + if not key.startswith('last_linear.'): + current_state[key] = state_dict[key] + + model.load_state_dict(current_state) + + model.input_space = settings['input_space'] + model.input_size = settings['input_size'] + model.input_range = settings['input_range'] + model.mean = settings['mean'] + model.std = settings['std'] + +def inceptionresnetv2(pretrained=False, **kwargs): + model = InceptionResNetV2() + if pretrained == True: + settings = pretrained_settings['inceptionresnetv2']['imagenet'] + initialize_pretrained_model(model, settings) + return model diff --git a/ExtractFeat/models/inceptionv4.py b/ExtractFeat/models/inceptionv4.py new file mode 100644 index 0000000..36c8aa8 --- /dev/null +++ b/ExtractFeat/models/inceptionv4.py @@ -0,0 +1,369 @@ +""" +Code gently borrowed from +https://github.com/Cadene/pretrained-models.pytorch +""" + +from __future__ import print_function, division, absolute_import +import torch +import torch.nn as nn +import torch.utils.model_zoo as model_zoo +import os +import sys +from lib.config import cfg + +__all__ = ['InceptionV4', 'inceptionv4'] + +pretrained_settings = { + 'inceptionv4': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/inceptionv4-8e4777a0.pth', + 'input_space': 'RGB', + 'input_size': [3, 299, 299], + 'input_range': [0, 1], + 'mean': [0.5, 0.5, 0.5], + 'std': [0.5, 0.5, 0.5], + 'num_classes': 1000 + }, + 'imagenet+background': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/inceptionv4-8e4777a0.pth', + 'input_space': 'RGB', + 'input_size': [3, 299, 299], + 'input_range': [0, 1], + 'mean': [0.5, 0.5, 0.5], + 'std': [0.5, 0.5, 0.5], + 'num_classes': 1001 + } + } +} + + +class BasicConv2d(nn.Module): + + def __init__(self, in_planes, out_planes, kernel_size, stride, padding=0): + super(BasicConv2d, self).__init__() + self.conv = nn.Conv2d(in_planes, out_planes, + kernel_size=kernel_size, stride=stride, + padding=padding, bias=False) # verify bias false + self.bn = nn.BatchNorm2d(out_planes, + eps=0.001, # value found in tensorflow + momentum=0.1, # default pytorch value + affine=True) + self.relu = nn.ReLU(inplace=True) + + def forward(self, x): + x = self.conv(x) + x = self.bn(x) + x = self.relu(x) + return x + + +class Mixed_3a(nn.Module): + + def __init__(self): + super(Mixed_3a, self).__init__() + self.maxpool = nn.MaxPool2d(3, stride=2) + self.conv = BasicConv2d(64, 96, kernel_size=3, stride=2) + + def forward(self, x): + x0 = self.maxpool(x) + x1 = self.conv(x) + out = torch.cat((x0, x1), 1) + return out + + +class Mixed_4a(nn.Module): + + def __init__(self): + super(Mixed_4a, self).__init__() + + self.branch0 = nn.Sequential( + BasicConv2d(160, 64, kernel_size=1, stride=1), + BasicConv2d(64, 96, kernel_size=3, stride=1) + ) + + self.branch1 = nn.Sequential( + BasicConv2d(160, 64, kernel_size=1, stride=1), + BasicConv2d(64, 64, kernel_size=(1,7), stride=1, padding=(0,3)), + BasicConv2d(64, 64, kernel_size=(7,1), stride=1, padding=(3,0)), + BasicConv2d(64, 96, kernel_size=(3,3), stride=1) + ) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + out = torch.cat((x0, x1), 1) + return out + + +class Mixed_5a(nn.Module): + + def __init__(self): + super(Mixed_5a, self).__init__() + self.conv = BasicConv2d(192, 192, kernel_size=3, stride=2) + self.maxpool = nn.MaxPool2d(3, stride=2) + + def forward(self, x): + x0 = self.conv(x) + x1 = self.maxpool(x) + out = torch.cat((x0, x1), 1) + return out + + +class Inception_A(nn.Module): + + def __init__(self): + super(Inception_A, self).__init__() + self.branch0 = BasicConv2d(384, 96, kernel_size=1, stride=1) + + self.branch1 = nn.Sequential( + BasicConv2d(384, 64, kernel_size=1, stride=1), + BasicConv2d(64, 96, kernel_size=3, stride=1, padding=1) + ) + + self.branch2 = nn.Sequential( + BasicConv2d(384, 64, kernel_size=1, stride=1), + BasicConv2d(64, 96, kernel_size=3, stride=1, padding=1), + BasicConv2d(96, 96, kernel_size=3, stride=1, padding=1) + ) + + self.branch3 = nn.Sequential( + nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False), + BasicConv2d(384, 96, kernel_size=1, stride=1) + ) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + x3 = self.branch3(x) + out = torch.cat((x0, x1, x2, x3), 1) + return out + + +class Reduction_A(nn.Module): + + def __init__(self): + super(Reduction_A, self).__init__() + self.branch0 = BasicConv2d(384, 384, kernel_size=3, stride=2) + + self.branch1 = nn.Sequential( + BasicConv2d(384, 192, kernel_size=1, stride=1), + BasicConv2d(192, 224, kernel_size=3, stride=1, padding=1), + BasicConv2d(224, 256, kernel_size=3, stride=2) + ) + + self.branch2 = nn.MaxPool2d(3, stride=2) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + out = torch.cat((x0, x1, x2), 1) + return out + + +class Inception_B(nn.Module): + + def __init__(self): + super(Inception_B, self).__init__() + self.branch0 = BasicConv2d(1024, 384, kernel_size=1, stride=1) + + self.branch1 = nn.Sequential( + BasicConv2d(1024, 192, kernel_size=1, stride=1), + BasicConv2d(192, 224, kernel_size=(1,7), stride=1, padding=(0,3)), + BasicConv2d(224, 256, kernel_size=(7,1), stride=1, padding=(3,0)) + ) + + self.branch2 = nn.Sequential( + BasicConv2d(1024, 192, kernel_size=1, stride=1), + BasicConv2d(192, 192, kernel_size=(7,1), stride=1, padding=(3,0)), + BasicConv2d(192, 224, kernel_size=(1,7), stride=1, padding=(0,3)), + BasicConv2d(224, 224, kernel_size=(7,1), stride=1, padding=(3,0)), + BasicConv2d(224, 256, kernel_size=(1,7), stride=1, padding=(0,3)) + ) + + self.branch3 = nn.Sequential( + nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False), + BasicConv2d(1024, 128, kernel_size=1, stride=1) + ) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + x3 = self.branch3(x) + out = torch.cat((x0, x1, x2, x3), 1) + return out + + +class Reduction_B(nn.Module): + + def __init__(self): + super(Reduction_B, self).__init__() + + self.branch0 = nn.Sequential( + BasicConv2d(1024, 192, kernel_size=1, stride=1), + BasicConv2d(192, 192, kernel_size=3, stride=2) + ) + + self.branch1 = nn.Sequential( + BasicConv2d(1024, 256, kernel_size=1, stride=1), + BasicConv2d(256, 256, kernel_size=(1,7), stride=1, padding=(0,3)), + BasicConv2d(256, 320, kernel_size=(7,1), stride=1, padding=(3,0)), + BasicConv2d(320, 320, kernel_size=3, stride=2) + ) + + self.branch2 = nn.MaxPool2d(3, stride=2) + + def forward(self, x): + x0 = self.branch0(x) + x1 = self.branch1(x) + x2 = self.branch2(x) + out = torch.cat((x0, x1, x2), 1) + return out + + +class Inception_C(nn.Module): + + def __init__(self): + super(Inception_C, self).__init__() + + self.branch0 = BasicConv2d(1536, 256, kernel_size=1, stride=1) + + self.branch1_0 = BasicConv2d(1536, 384, kernel_size=1, stride=1) + self.branch1_1a = BasicConv2d(384, 256, kernel_size=(1,3), stride=1, padding=(0,1)) + self.branch1_1b = BasicConv2d(384, 256, kernel_size=(3,1), stride=1, padding=(1,0)) + + self.branch2_0 = BasicConv2d(1536, 384, kernel_size=1, stride=1) + self.branch2_1 = BasicConv2d(384, 448, kernel_size=(3,1), stride=1, padding=(1,0)) + self.branch2_2 = BasicConv2d(448, 512, kernel_size=(1,3), stride=1, padding=(0,1)) + self.branch2_3a = BasicConv2d(512, 256, kernel_size=(1,3), stride=1, padding=(0,1)) + self.branch2_3b = BasicConv2d(512, 256, kernel_size=(3,1), stride=1, padding=(1,0)) + + self.branch3 = nn.Sequential( + nn.AvgPool2d(3, stride=1, padding=1, count_include_pad=False), + BasicConv2d(1536, 256, kernel_size=1, stride=1) + ) + + def forward(self, x): + x0 = self.branch0(x) + + x1_0 = self.branch1_0(x) + x1_1a = self.branch1_1a(x1_0) + x1_1b = self.branch1_1b(x1_0) + x1 = torch.cat((x1_1a, x1_1b), 1) + + x2_0 = self.branch2_0(x) + x2_1 = self.branch2_1(x2_0) + x2_2 = self.branch2_2(x2_1) + x2_3a = self.branch2_3a(x2_2) + x2_3b = self.branch2_3b(x2_2) + x2 = torch.cat((x2_3a, x2_3b), 1) + + x3 = self.branch3(x) + + out = torch.cat((x0, x1, x2, x3), 1) + return out + + +class InceptionV4(nn.Module): + + def __init__(self): + super(InceptionV4, self).__init__() + # Special attributs + self.input_space = None + self.input_size = (299, 299, 3) + self.mean = None + self.std = None + # Modules + self.features = nn.Sequential( + BasicConv2d(3, 32, kernel_size=3, stride=2), + BasicConv2d(32, 32, kernel_size=3, stride=1), + BasicConv2d(32, 64, kernel_size=3, stride=1, padding=1), + Mixed_3a(), + Mixed_4a(), + Mixed_5a(), + Inception_A(), + Inception_A(), + Inception_A(), + Inception_A(), + Reduction_A(), # Mixed_6a + Inception_B(), + Inception_B(), + Inception_B(), + Inception_B(), + Inception_B(), + Inception_B(), + Inception_B(), + Reduction_B(), # Mixed_7a + Inception_C(), + Inception_C(), + Inception_C() + ) + self.avg_pool = nn.AdaptiveAvgPool2d((1,1)) + + if cfg.TRAIN.FIX_TWO: + self._freeze_backbone() + + if cfg.TRAIN.FIX_BN: + self._freeze_bn_param() + + if cfg.TRAIN.FIX_ALL: + self._freeze_all() + + def freeze_bn(self): + '''Freeze BatchNorm layers.''' + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.eval() + + def _freeze_backbone(self): + m = self.features[0] + for p in m.parameters(): + p.requires_grad = False + m = self.features[1] + for p in m.parameters(): + p.requires_grad = False + m = self.features[2] + for p in m.parameters(): + p.requires_grad = False + + def _freeze_all(self): + for p in self.parameters(): + p.requires_grad = False + + def _freeze_bn_param(self): + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.weight.requires_grad = False + layer.bias.requires_grad = False + + def forward(self, input): + res5c = self.features(input) + x = self.avg_pool(res5c).view(res5c.size(0), -1) + return res5c, x + +def initialize_pretrained_model(model, settings): + state_dict = model_zoo.load_url(settings['url']) + current_state = model.state_dict() + keys = list(state_dict.keys()) + + for key in keys: + if not key.startswith('last_linear.'): + current_state[key] = state_dict[key] + + model.load_state_dict(current_state) + + model.input_space = settings['input_space'] + model.input_size = settings['input_size'] + model.input_range = settings['input_range'] + model.mean = settings['mean'] + model.std = settings['std'] + + +def inceptionv4(pretrained=False, **kwargs): + model = InceptionV4() + if pretrained == True: + settings = pretrained_settings['inceptionv4']['imagenet'] + initialize_pretrained_model(model, settings) + return model \ No newline at end of file diff --git a/ExtractFeat/models/pnasnet.py b/ExtractFeat/models/pnasnet.py new file mode 100644 index 0000000..252f886 --- /dev/null +++ b/ExtractFeat/models/pnasnet.py @@ -0,0 +1,430 @@ +""" +Code gently borrowed from +https://github.com/Cadene/pretrained-models.pytorch +""" + +from __future__ import print_function, division, absolute_import +from collections import OrderedDict + +import torch +import torch.nn as nn +import torch.utils.model_zoo as model_zoo +from lib.config import cfg + +__all__ = ['pnasnet5large'] + +pretrained_settings = { + 'pnasnet5large': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/pnasnet5large-bf079911.pth', + 'input_space': 'RGB', + 'input_size': [3, 331, 331], + 'input_range': [0, 1], + 'mean': [0.5, 0.5, 0.5], + 'std': [0.5, 0.5, 0.5], + 'num_classes': 1000 + }, + 'imagenet+background': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/pnasnet5large-bf079911.pth', + 'input_space': 'RGB', + 'input_size': [3, 331, 331], + 'input_range': [0, 1], + 'mean': [0.5, 0.5, 0.5], + 'std': [0.5, 0.5, 0.5], + 'num_classes': 1001 + } + } +} + + +class MaxPool(nn.Module): + + def __init__(self, kernel_size, stride=1, padding=1, zero_pad=False): + super(MaxPool, self).__init__() + self.zero_pad = nn.ZeroPad2d((1, 0, 1, 0)) if zero_pad else None + self.pool = nn.MaxPool2d(kernel_size, stride=stride, padding=padding) + + def forward(self, x): + if self.zero_pad: + x = self.zero_pad(x) + x = self.pool(x) + if self.zero_pad: + x = x[:, :, 1:, 1:] + return x + + +class SeparableConv2d(nn.Module): + + def __init__(self, in_channels, out_channels, dw_kernel_size, dw_stride, + dw_padding): + super(SeparableConv2d, self).__init__() + self.depthwise_conv2d = nn.Conv2d(in_channels, in_channels, + kernel_size=dw_kernel_size, + stride=dw_stride, padding=dw_padding, + groups=in_channels, bias=False) + self.pointwise_conv2d = nn.Conv2d(in_channels, out_channels, + kernel_size=1, bias=False) + + def forward(self, x): + x = self.depthwise_conv2d(x) + x = self.pointwise_conv2d(x) + return x + + +class BranchSeparables(nn.Module): + + def __init__(self, in_channels, out_channels, kernel_size, stride=1, + stem_cell=False, zero_pad=False): + super(BranchSeparables, self).__init__() + padding = kernel_size // 2 + middle_channels = out_channels if stem_cell else in_channels + self.zero_pad = nn.ZeroPad2d((1, 0, 1, 0)) if zero_pad else None + self.relu_1 = nn.ReLU() + self.separable_1 = SeparableConv2d(in_channels, middle_channels, + kernel_size, dw_stride=stride, + dw_padding=padding) + self.bn_sep_1 = nn.BatchNorm2d(middle_channels, eps=0.001) + self.relu_2 = nn.ReLU() + self.separable_2 = SeparableConv2d(middle_channels, out_channels, + kernel_size, dw_stride=1, + dw_padding=padding) + self.bn_sep_2 = nn.BatchNorm2d(out_channels, eps=0.001) + + def forward(self, x): + x = self.relu_1(x) + if self.zero_pad: + x = self.zero_pad(x) + x = self.separable_1(x) + if self.zero_pad: + x = x[:, :, 1:, 1:].contiguous() + x = self.bn_sep_1(x) + x = self.relu_2(x) + x = self.separable_2(x) + x = self.bn_sep_2(x) + return x + + +class ReluConvBn(nn.Module): + + def __init__(self, in_channels, out_channels, kernel_size, stride=1): + super(ReluConvBn, self).__init__() + self.relu = nn.ReLU() + self.conv = nn.Conv2d(in_channels, out_channels, + kernel_size=kernel_size, stride=stride, + bias=False) + self.bn = nn.BatchNorm2d(out_channels, eps=0.001) + + def forward(self, x): + x = self.relu(x) + x = self.conv(x) + x = self.bn(x) + return x + + +class FactorizedReduction(nn.Module): + + def __init__(self, in_channels, out_channels): + super(FactorizedReduction, self).__init__() + self.relu = nn.ReLU() + self.path_1 = nn.Sequential(OrderedDict([ + ('avgpool', nn.AvgPool2d(1, stride=2, count_include_pad=False)), + ('conv', nn.Conv2d(in_channels, out_channels // 2, + kernel_size=1, bias=False)), + ])) + self.path_2 = nn.Sequential(OrderedDict([ + ('pad', nn.ZeroPad2d((0, 1, 0, 1))), + ('avgpool', nn.AvgPool2d(1, stride=2, count_include_pad=False)), + ('conv', nn.Conv2d(in_channels, out_channels // 2, + kernel_size=1, bias=False)), + ])) + self.final_path_bn = nn.BatchNorm2d(out_channels, eps=0.001) + + def forward(self, x): + x = self.relu(x) + + x_path1 = self.path_1(x) + + x_path2 = self.path_2.pad(x) + x_path2 = x_path2[:, :, 1:, 1:] + x_path2 = self.path_2.avgpool(x_path2) + x_path2 = self.path_2.conv(x_path2) + + out = self.final_path_bn(torch.cat([x_path1, x_path2], 1)) + return out + + +class CellBase(nn.Module): + + def cell_forward(self, x_left, x_right): + x_comb_iter_0_left = self.comb_iter_0_left(x_left) + x_comb_iter_0_right = self.comb_iter_0_right(x_left) + x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right + + x_comb_iter_1_left = self.comb_iter_1_left(x_right) + x_comb_iter_1_right = self.comb_iter_1_right(x_right) + x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right + + x_comb_iter_2_left = self.comb_iter_2_left(x_right) + x_comb_iter_2_right = self.comb_iter_2_right(x_right) + x_comb_iter_2 = x_comb_iter_2_left + x_comb_iter_2_right + + x_comb_iter_3_left = self.comb_iter_3_left(x_comb_iter_2) + x_comb_iter_3_right = self.comb_iter_3_right(x_right) + x_comb_iter_3 = x_comb_iter_3_left + x_comb_iter_3_right + + x_comb_iter_4_left = self.comb_iter_4_left(x_left) + if self.comb_iter_4_right: + x_comb_iter_4_right = self.comb_iter_4_right(x_right) + else: + x_comb_iter_4_right = x_right + x_comb_iter_4 = x_comb_iter_4_left + x_comb_iter_4_right + + x_out = torch.cat( + [x_comb_iter_0, x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, + x_comb_iter_4], 1) + return x_out + + +class CellStem0(CellBase): + + def __init__(self, in_channels_left, out_channels_left, in_channels_right, + out_channels_right): + super(CellStem0, self).__init__() + self.conv_1x1 = ReluConvBn(in_channels_right, out_channels_right, + kernel_size=1) + self.comb_iter_0_left = BranchSeparables(in_channels_left, + out_channels_left, + kernel_size=5, stride=2, + stem_cell=True) + self.comb_iter_0_right = nn.Sequential(OrderedDict([ + ('max_pool', MaxPool(3, stride=2)), + ('conv', nn.Conv2d(in_channels_left, out_channels_left, + kernel_size=1, bias=False)), + ('bn', nn.BatchNorm2d(out_channels_left, eps=0.001)), + ])) + self.comb_iter_1_left = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=7, stride=2) + self.comb_iter_1_right = MaxPool(3, stride=2) + self.comb_iter_2_left = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=5, stride=2) + self.comb_iter_2_right = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=3, stride=2) + self.comb_iter_3_left = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=3) + self.comb_iter_3_right = MaxPool(3, stride=2) + self.comb_iter_4_left = BranchSeparables(in_channels_right, + out_channels_right, + kernel_size=3, stride=2, + stem_cell=True) + self.comb_iter_4_right = ReluConvBn(out_channels_right, + out_channels_right, + kernel_size=1, stride=2) + + def forward(self, x_left): + x_right = self.conv_1x1(x_left) + x_out = self.cell_forward(x_left, x_right) + return x_out + + +class Cell(CellBase): + + def __init__(self, in_channels_left, out_channels_left, in_channels_right, + out_channels_right, is_reduction=False, zero_pad=False, + match_prev_layer_dimensions=False): + super(Cell, self).__init__() + + # If `is_reduction` is set to `True` stride 2 is used for + # convolutional and pooling layers to reduce the spatial size of + # the output of a cell approximately by a factor of 2. + stride = 2 if is_reduction else 1 + + # If `match_prev_layer_dimensions` is set to `True` + # `FactorizedReduction` is used to reduce the spatial size + # of the left input of a cell approximately by a factor of 2. + self.match_prev_layer_dimensions = match_prev_layer_dimensions + if match_prev_layer_dimensions: + self.conv_prev_1x1 = FactorizedReduction(in_channels_left, + out_channels_left) + else: + self.conv_prev_1x1 = ReluConvBn(in_channels_left, + out_channels_left, kernel_size=1) + + self.conv_1x1 = ReluConvBn(in_channels_right, out_channels_right, + kernel_size=1) + self.comb_iter_0_left = BranchSeparables(out_channels_left, + out_channels_left, + kernel_size=5, stride=stride, + zero_pad=zero_pad) + self.comb_iter_0_right = MaxPool(3, stride=stride, zero_pad=zero_pad) + self.comb_iter_1_left = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=7, stride=stride, + zero_pad=zero_pad) + self.comb_iter_1_right = MaxPool(3, stride=stride, zero_pad=zero_pad) + self.comb_iter_2_left = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=5, stride=stride, + zero_pad=zero_pad) + self.comb_iter_2_right = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=3, stride=stride, + zero_pad=zero_pad) + self.comb_iter_3_left = BranchSeparables(out_channels_right, + out_channels_right, + kernel_size=3) + self.comb_iter_3_right = MaxPool(3, stride=stride, zero_pad=zero_pad) + self.comb_iter_4_left = BranchSeparables(out_channels_left, + out_channels_left, + kernel_size=3, stride=stride, + zero_pad=zero_pad) + if is_reduction: + self.comb_iter_4_right = ReluConvBn(out_channels_right, + out_channels_right, + kernel_size=1, stride=stride) + else: + self.comb_iter_4_right = None + + def forward(self, x_left, x_right): + x_left = self.conv_prev_1x1(x_left) + x_right = self.conv_1x1(x_right) + x_out = self.cell_forward(x_left, x_right) + return x_out + + +class PNASNet5Large(nn.Module): + def __init__(self): + super(PNASNet5Large, self).__init__() + self.conv_0 = nn.Sequential(OrderedDict([ + ('conv', nn.Conv2d(3, 96, kernel_size=3, stride=2, bias=False)), + ('bn', nn.BatchNorm2d(96, eps=0.001)) + ])) + self.cell_stem_0 = CellStem0(in_channels_left=96, out_channels_left=54, + in_channels_right=96, + out_channels_right=54) + self.cell_stem_1 = Cell(in_channels_left=96, out_channels_left=108, + in_channels_right=270, out_channels_right=108, + match_prev_layer_dimensions=True, + is_reduction=True) + self.cell_0 = Cell(in_channels_left=270, out_channels_left=216, + in_channels_right=540, out_channels_right=216, + match_prev_layer_dimensions=True) + self.cell_1 = Cell(in_channels_left=540, out_channels_left=216, + in_channels_right=1080, out_channels_right=216) + self.cell_2 = Cell(in_channels_left=1080, out_channels_left=216, + in_channels_right=1080, out_channels_right=216) + self.cell_3 = Cell(in_channels_left=1080, out_channels_left=216, + in_channels_right=1080, out_channels_right=216) + self.cell_4 = Cell(in_channels_left=1080, out_channels_left=432, + in_channels_right=1080, out_channels_right=432, + is_reduction=True, zero_pad=True) + self.cell_5 = Cell(in_channels_left=1080, out_channels_left=432, + in_channels_right=2160, out_channels_right=432, + match_prev_layer_dimensions=True) + self.cell_6 = Cell(in_channels_left=2160, out_channels_left=432, + in_channels_right=2160, out_channels_right=432) + self.cell_7 = Cell(in_channels_left=2160, out_channels_left=432, + in_channels_right=2160, out_channels_right=432) + self.cell_8 = Cell(in_channels_left=2160, out_channels_left=864, + in_channels_right=2160, out_channels_right=864, + is_reduction=True) + self.cell_9 = Cell(in_channels_left=2160, out_channels_left=864, + in_channels_right=4320, out_channels_right=864, + match_prev_layer_dimensions=True) + self.cell_10 = Cell(in_channels_left=4320, out_channels_left=864, + in_channels_right=4320, out_channels_right=864) + self.cell_11 = Cell(in_channels_left=4320, out_channels_left=864, + in_channels_right=4320, out_channels_right=864) + self.relu = nn.ReLU() + self.avg_pool = nn.AdaptiveAvgPool2d((1,1)) + + if cfg.TRAIN.FIX_TWO: + self._freeze_backbone() + + if cfg.TRAIN.FIX_BN: + self._freeze_bn_param() + + if cfg.TRAIN.FIX_ALL: + self._freeze_all() + + def freeze_bn(self): + '''Freeze BatchNorm layers.''' + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.eval() + + def _freeze_backbone(self): + m = getattr(self, "conv_0") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "cell_stem_0") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "cell_stem_1") + for p in m.parameters(): + p.requires_grad = False + + def _freeze_all(self): + for p in self.parameters(): + p.requires_grad = False + + def _freeze_bn_param(self): + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.weight.requires_grad = False + layer.bias.requires_grad = False + + def features(self, x): + x_conv_0 = self.conv_0(x) + x_stem_0 = self.cell_stem_0(x_conv_0) + x_stem_1 = self.cell_stem_1(x_conv_0, x_stem_0) + x_cell_0 = self.cell_0(x_stem_0, x_stem_1) + x_cell_1 = self.cell_1(x_stem_1, x_cell_0) + x_cell_2 = self.cell_2(x_cell_0, x_cell_1) + x_cell_3 = self.cell_3(x_cell_1, x_cell_2) + x_cell_4 = self.cell_4(x_cell_2, x_cell_3) + x_cell_5 = self.cell_5(x_cell_3, x_cell_4) + x_cell_6 = self.cell_6(x_cell_4, x_cell_5) + x_cell_7 = self.cell_7(x_cell_5, x_cell_6) + x_cell_8 = self.cell_8(x_cell_6, x_cell_7) + x_cell_9 = self.cell_9(x_cell_7, x_cell_8) + x_cell_10 = self.cell_10(x_cell_8, x_cell_9) + x_cell_11 = self.cell_11(x_cell_9, x_cell_10) + return x_cell_11 + + def forward(self, input): + x = self.features(input) + res5c = self.relu(x) + x = self.avg_pool(res5c).view(res5c.size(0), -1) + return res5c, x + +def initialize_pretrained_model(model, settings): + state_dict = model_zoo.load_url(settings['url']) + current_state = model.state_dict() + keys = list(state_dict.keys()) + + for key in keys: + if not key.startswith('last_linear.'): + current_state[key] = state_dict[key] + + model.load_state_dict(current_state) + + model.input_space = settings['input_space'] + model.input_size = settings['input_size'] + model.input_range = settings['input_range'] + model.mean = settings['mean'] + model.std = settings['std'] + +def pnasnet5large(pretrained=False, **kwargs): + r"""PNASNet-5 model architecture from the + `"Progressive Neural Architecture Search" + `_ paper. + """ + model = PNASNet5Large() + if pretrained == True: + settings = pretrained_settings['pnasnet5large']['imagenet'] + initialize_pretrained_model(model, settings) + return model diff --git a/ExtractFeat/models/senet.py b/ExtractFeat/models/senet.py new file mode 100644 index 0000000..00cdcca --- /dev/null +++ b/ExtractFeat/models/senet.py @@ -0,0 +1,603 @@ +""" +Code gently borrowed from +https://github.com/Cadene/pretrained-models.pytorch +""" + +""" +ResNet code gently borrowed from +https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py +""" + +from collections import OrderedDict +import math + +import torch.nn as nn +from torch.utils import model_zoo +import torchvision.models.resnet as resnet +from lib.config import cfg + + +__all__ = ['SENet', 'senet154', 'se_resnet50', 'se_resnet101', 'se_resnet152', + 'se_resnext50_32x4d', 'se_resnext101_32x4d', 'resnet50', 'resnet101', 'resnet152', 'inceptionresnetv2'] + +pretrained_settings = { + 'inceptionresnetv2': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/inceptionresnetv2-520b38e4.pth', + 'input_space': 'RGB', + 'input_size': [3, 299, 299], + 'input_range': [0, 1], + 'mean': [0.5, 0.5, 0.5], + 'std': [0.5, 0.5, 0.5], + 'num_classes': 1000 + } + }, + 'senet154': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/senet154-c7b49a05.pth', + 'input_space': 'RGB', + 'input_size': [3, 224, 224], + 'input_range': [0, 1], + 'mean': [0.485, 0.456, 0.406], + 'std': [0.229, 0.224, 0.225], + 'num_classes': 1000 + } + }, + 'se_resnet50': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/se_resnet50-ce0d4300.pth', + 'input_space': 'RGB', + 'input_size': [3, 224, 224], + 'input_range': [0, 1], + 'mean': [0.485, 0.456, 0.406], + 'std': [0.229, 0.224, 0.225], + 'num_classes': 1000 + } + }, + 'se_resnet101': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/se_resnet101-7e38fcc6.pth', + 'input_space': 'RGB', + 'input_size': [3, 224, 224], + 'input_range': [0, 1], + 'mean': [0.485, 0.456, 0.406], + 'std': [0.229, 0.224, 0.225], + 'num_classes': 1000 + } + }, + 'se_resnet152': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/se_resnet152-d17c99b7.pth', + 'input_space': 'RGB', + 'input_size': [3, 224, 224], + 'input_range': [0, 1], + 'mean': [0.485, 0.456, 0.406], + 'std': [0.229, 0.224, 0.225], + 'num_classes': 1000 + } + }, + 'se_resnext50_32x4d': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/se_resnext50_32x4d-a260b3a4.pth', + 'input_space': 'RGB', + 'input_size': [3, 224, 224], + 'input_range': [0, 1], + 'mean': [0.485, 0.456, 0.406], + 'std': [0.229, 0.224, 0.225], + 'num_classes': 1000 + } + }, + 'se_resnext101_32x4d': { + 'imagenet': { + 'url': 'http://data.lip6.fr/cadene/pretrainedmodels/se_resnext101_32x4d-3b2fe3d8.pth', + 'input_space': 'RGB', + 'input_size': [3, 224, 224], + 'input_range': [0, 1], + 'mean': [0.485, 0.456, 0.406], + 'std': [0.229, 0.224, 0.225], + 'num_classes': 1000 + } + }, +} + + +class SEModule(nn.Module): + + def __init__(self, channels, reduction): + super(SEModule, self).__init__() + self.avg_pool = nn.AdaptiveAvgPool2d(1) + self.fc1 = nn.Conv2d(channels, channels // reduction, kernel_size=1, + padding=0) + self.relu = nn.ReLU(inplace=True) + self.fc2 = nn.Conv2d(channels // reduction, channels, kernel_size=1, + padding=0) + self.sigmoid = nn.Sigmoid() + + def forward(self, x): + module_input = x + x = self.avg_pool(x) + x = self.fc1(x) + x = self.relu(x) + x = self.fc2(x) + x = self.sigmoid(x) + return module_input * x + + +class Bottleneck(nn.Module): + """ + Base class for bottlenecks that implements `forward()` method. + """ + def forward(self, x): + residual = x + + out = self.conv1(x) + out = self.bn1(out) + out = self.relu(out) + + out = self.conv2(out) + out = self.bn2(out) + out = self.relu(out) + + out = self.conv3(out) + out = self.bn3(out) + + if self.downsample is not None: + residual = self.downsample(x) + + out = self.se_module(out) + residual + out = self.relu(out) + + return out + + +class SEBottleneck(Bottleneck): + """ + Bottleneck for SENet154. + """ + expansion = 4 + + def __init__(self, inplanes, planes, groups, reduction, stride=1, + downsample=None): + super(SEBottleneck, self).__init__() + self.conv1 = nn.Conv2d(inplanes, planes * 2, kernel_size=1, bias=False) + self.bn1 = nn.BatchNorm2d(planes * 2) + self.conv2 = nn.Conv2d(planes * 2, planes * 4, kernel_size=3, + stride=stride, padding=1, groups=groups, + bias=False) + self.bn2 = nn.BatchNorm2d(planes * 4) + self.conv3 = nn.Conv2d(planes * 4, planes * 4, kernel_size=1, + bias=False) + self.bn3 = nn.BatchNorm2d(planes * 4) + self.relu = nn.ReLU(inplace=True) + self.se_module = SEModule(planes * 4, reduction=reduction) + self.downsample = downsample + self.stride = stride + + +class SEResNetBottleneck(Bottleneck): + """ + ResNet bottleneck with a Squeeze-and-Excitation module. It follows Caffe + implementation and uses `stride=stride` in `conv1` and not in `conv2` + (the latter is used in the torchvision implementation of ResNet). + """ + expansion = 4 + + def __init__(self, inplanes, planes, groups, reduction, stride=1, + downsample=None): + super(SEResNetBottleneck, self).__init__() + self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=1, bias=False, + stride=stride) + self.bn1 = nn.BatchNorm2d(planes) + self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, padding=1, + groups=groups, bias=False) + self.bn2 = nn.BatchNorm2d(planes) + self.conv3 = nn.Conv2d(planes, planes * 4, kernel_size=1, bias=False) + self.bn3 = nn.BatchNorm2d(planes * 4) + self.relu = nn.ReLU(inplace=True) + self.se_module = SEModule(planes * 4, reduction=reduction) + self.downsample = downsample + self.stride = stride + + +class SEResNeXtBottleneck(Bottleneck): + """ + ResNeXt bottleneck type C with a Squeeze-and-Excitation module. + """ + expansion = 4 + + def __init__(self, inplanes, planes, groups, reduction, stride=1, + downsample=None, base_width=4): + super(SEResNeXtBottleneck, self).__init__() + width = int(math.floor(planes * (base_width / 64.0)) * groups) + self.conv1 = nn.Conv2d(inplanes, width, kernel_size=1, bias=False, + stride=1) + self.bn1 = nn.BatchNorm2d(width) + self.conv2 = nn.Conv2d(width, width, kernel_size=3, stride=stride, + padding=1, groups=groups, bias=False) + self.bn2 = nn.BatchNorm2d(width) + self.conv3 = nn.Conv2d(width, planes * 4, kernel_size=1, bias=False) + self.bn3 = nn.BatchNorm2d(planes * 4) + self.relu = nn.ReLU(inplace=True) + self.se_module = SEModule(planes * 4, reduction=reduction) + self.downsample = downsample + self.stride = stride + + +class SENet(nn.Module): + + def __init__(self, block, layers, groups, reduction, dropout_p=0.2, + inplanes=128, input_3x3=True, downsample_kernel_size=3, + downsample_padding=1): + """ + Parameters + ---------- + block (nn.Module): Bottleneck class. + - For SENet154: SEBottleneck + - For SE-ResNet models: SEResNetBottleneck + - For SE-ResNeXt models: SEResNeXtBottleneck + layers (list of ints): Number of residual blocks for 4 layers of the + network (layer1...layer4). + groups (int): Number of groups for the 3x3 convolution in each + bottleneck block. + - For SENet154: 64 + - For SE-ResNet models: 1 + - For SE-ResNeXt models: 32 + reduction (int): Reduction ratio for Squeeze-and-Excitation modules. + - For all models: 16 + dropout_p (float or None): Drop probability for the Dropout layer. + If `None` the Dropout layer is not used. + - For SENet154: 0.2 + - For SE-ResNet models: None + - For SE-ResNeXt models: None + inplanes (int): Number of input channels for layer1. + - For SENet154: 128 + - For SE-ResNet models: 64 + - For SE-ResNeXt models: 64 + input_3x3 (bool): If `True`, use three 3x3 convolutions instead of + a single 7x7 convolution in layer0. + - For SENet154: True + - For SE-ResNet models: False + - For SE-ResNeXt models: False + downsample_kernel_size (int): Kernel size for downsampling convolutions + in layer2, layer3 and layer4. + - For SENet154: 3 + - For SE-ResNet models: 1 + - For SE-ResNeXt models: 1 + downsample_padding (int): Padding for downsampling convolutions in + layer2, layer3 and layer4. + - For SENet154: 1 + - For SE-ResNet models: 0 + - For SE-ResNeXt models: 0 + num_classes (int): Number of outputs in `last_linear` layer. + - For all models: 1000 + """ + super(SENet, self).__init__() + self.inplanes = inplanes + if input_3x3: + layer0_modules = [ + ('conv1', nn.Conv2d(3, 64, 3, stride=2, padding=1, + bias=False)), + ('bn1', nn.BatchNorm2d(64)), + ('relu1', nn.ReLU(inplace=True)), + ('conv2', nn.Conv2d(64, 64, 3, stride=1, padding=1, + bias=False)), + ('bn2', nn.BatchNorm2d(64)), + ('relu2', nn.ReLU(inplace=True)), + ('conv3', nn.Conv2d(64, inplanes, 3, stride=1, padding=1, + bias=False)), + ('bn3', nn.BatchNorm2d(inplanes)), + ('relu3', nn.ReLU(inplace=True)), + ] + else: + layer0_modules = [ + ('conv1', nn.Conv2d(3, inplanes, kernel_size=7, stride=2, + padding=3, bias=False)), + ('bn1', nn.BatchNorm2d(inplanes)), + ('relu1', nn.ReLU(inplace=True)), + ] + # To preserve compatibility with Caffe weights `ceil_mode=True` + # is used instead of `padding=1`. + layer0_modules.append(('pool', nn.MaxPool2d(3, stride=2, + ceil_mode=True))) + self.layer0 = nn.Sequential(OrderedDict(layer0_modules)) + self.layer1 = self._make_layer( + block, + planes=64, + blocks=layers[0], + groups=groups, + reduction=reduction, + downsample_kernel_size=1, + downsample_padding=0 + ) + self.layer2 = self._make_layer( + block, + planes=128, + blocks=layers[1], + stride=2, + groups=groups, + reduction=reduction, + downsample_kernel_size=downsample_kernel_size, + downsample_padding=downsample_padding + ) + self.layer3 = self._make_layer( + block, + planes=256, + blocks=layers[2], + stride=2, + groups=groups, + reduction=reduction, + downsample_kernel_size=downsample_kernel_size, + downsample_padding=downsample_padding + ) + self.layer4 = self._make_layer( + block, + planes=512, + blocks=layers[3], + stride=2, + groups=groups, + reduction=reduction, + downsample_kernel_size=downsample_kernel_size, + downsample_padding=downsample_padding + ) + self.avg_pool = nn.AdaptiveAvgPool2d((1, 1)) + + if cfg.TRAIN.FIX_TWO: + self._freeze_backbone() + + def freeze_bn(self): + '''Freeze BatchNorm layers.''' + for layer in self.modules(): + if isinstance(layer, nn.BatchNorm2d): + layer.eval() + + def _freeze_backbone(self): + m = getattr(self, "layer0") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "layer1") + for p in m.parameters(): + p.requires_grad = False + + def _make_layer(self, block, planes, blocks, groups, reduction, stride=1, + downsample_kernel_size=1, downsample_padding=0): + downsample = None + if stride != 1 or self.inplanes != planes * block.expansion: + downsample = nn.Sequential( + nn.Conv2d(self.inplanes, planes * block.expansion, + kernel_size=downsample_kernel_size, stride=stride, + padding=downsample_padding, bias=False), + nn.BatchNorm2d(planes * block.expansion), + ) + + layers = [] + layers.append(block(self.inplanes, planes, groups, reduction, stride, + downsample)) + self.inplanes = planes * block.expansion + for i in range(1, blocks): + layers.append(block(self.inplanes, planes, groups, reduction)) + + return nn.Sequential(*layers) + + def forward(self, x): + x = self.layer0(x) + x = self.layer1(x) + x = self.layer2(x) + x = self.layer3(x) + res5c = self.layer4(x) + x = self.avg_pool(res5c).view(res5c.size(0), -1) + return res5c, x + + +class ResNet(nn.Module): + def __init__(self, block, layers, avgpool_size=7): + self.inplanes = 64 + super(ResNet, self).__init__() + self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, + bias=False) + self.bn1 = nn.BatchNorm2d(64) + self.relu = nn.ReLU(inplace=True) + self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1) + self.layer1 = self._make_layer(block, 64, layers[0]) + self.layer2 = self._make_layer(block, 128, layers[1], stride=2) + self.layer3 = self._make_layer(block, 256, layers[2], stride=2) + self.layer4 = self._make_layer(block, 512, layers[3], stride=2) + self.avg_pool = nn.AdaptiveAvgPool2d((1, 1)) + + bn_layers = [] + for m in self.modules(): + if isinstance(m, nn.Conv2d): + n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels + m.weight.data.normal_(0, math.sqrt(2. / n)) + elif isinstance(m, nn.BatchNorm2d): + m.weight.data.fill_(1) + m.bias.data.zero_() + bn_layers.append(m) + + if cfg.TRAIN.FIX_TWO: + self._freeze_backbone() + + def _freeze_backbone(self): + m = getattr(self, "conv1") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "bn1") + for p in m.parameters(): + p.requires_grad = False + m = getattr(self, "layer1") + for p in m.parameters(): + p.requires_grad = False + + def _make_layer(self, block, planes, blocks, stride=1): + downsample = None + if stride != 1 or self.inplanes != planes * block.expansion: + downsample = nn.Sequential( + nn.Conv2d(self.inplanes, planes * block.expansion, + kernel_size=1, stride=stride, bias=False), + nn.BatchNorm2d(planes * block.expansion), + ) + + layers = [] + layers.append(block(self.inplanes, planes, stride, downsample)) + self.inplanes = planes * block.expansion + for i in range(1, blocks): + layers.append(block(self.inplanes, planes)) + + return nn.Sequential(*layers) + + def forward(self, x): + x = self.conv1(x) + x = self.bn1(x) + x = self.relu(x) + x = self.maxpool(x) + + x = self.layer1(x) + x = self.layer2(x) + x = self.layer3(x) + res5c = self.layer4(x) + x = self.avg_pool(res5c).view(res5c.size(0), -1) + return res5c, x + + +def initialize_pretrained_model(model, settings): + state_dict = model_zoo.load_url(settings['url']) + + current_state = model.state_dict() + keys = list(state_dict.keys()) + for key in keys: + if not key.startswith('last_linear.'): + current_state[key] = state_dict[key] + model.load_state_dict(current_state) + + #model.load_state_dict(model_zoo.load_url(settings['url'])) + model.input_space = settings['input_space'] + model.input_size = settings['input_size'] + model.input_range = settings['input_range'] + model.mean = settings['mean'] + model.std = settings['std'] + + +def senet154(pretrained=True, **kwargs): + model = SENet(SEBottleneck, [3, 8, 36, 3], groups=64, reduction=16, + dropout_p=0.2, **kwargs) + if pretrained is not False: + settings = pretrained_settings['senet154']['imagenet'] + initialize_pretrained_model(model, settings) + return model + + +def se_resnet50(pretrained=True, **kwargs): + model = SENet(SEResNetBottleneck, [3, 4, 6, 3], groups=1, reduction=16, + dropout_p=None, inplanes=64, input_3x3=False, + downsample_kernel_size=1, downsample_padding=0, + **kwargs) + if pretrained is not None: + settings = pretrained_settings['se_resnet50']['imagenet'] + initialize_pretrained_model(model, settings) + return model + + +def se_resnet101(pretrained=True, **kwargs): + model = SENet(SEResNetBottleneck, [3, 4, 23, 3], groups=1, reduction=16, + dropout_p=None, inplanes=64, input_3x3=False, + downsample_kernel_size=1, downsample_padding=0, + **kwargs) + if pretrained is not None: + settings = pretrained_settings['se_resnet101']['imagenet'] + initialize_pretrained_model(model, settings) + return model + + +def se_resnet152(pretrained=True, **kwargs): + model = SENet(SEResNetBottleneck, [3, 8, 36, 3], groups=1, reduction=16, + dropout_p=None, inplanes=64, input_3x3=False, + downsample_kernel_size=1, downsample_padding=0, + **kwargs) + if pretrained is not None: + settings = pretrained_settings['se_resnet152']['imagenet'] + initialize_pretrained_model(model, settings) + return model + + +def se_resnext50_32x4d(pretrained=True, **kwargs): + model = SENet(SEResNeXtBottleneck, [3, 4, 6, 3], groups=32, reduction=16, + dropout_p=None, inplanes=64, input_3x3=False, + downsample_kernel_size=1, downsample_padding=0, + **kwargs) + if pretrained == True: + settings = pretrained_settings['se_resnext50_32x4d']['imagenet'] + initialize_pretrained_model(model, settings) + return model + + +def se_resnext101_32x4d(pretrained=True, **kwargs): + model = SENet(SEResNeXtBottleneck, [3, 4, 23, 3], groups=32, reduction=16, + dropout_p=None, inplanes=64, input_3x3=False, + downsample_kernel_size=1, downsample_padding=0, + **kwargs) + if pretrained is not None: + settings = pretrained_settings['se_resnext101_32x4d']['imagenet'] + initialize_pretrained_model(model, settings) + return model + + +def resnet50(pretrained=True, **kwargs): + """Constructs a ResNet-50 model. + + Args: + pretrained (bool): If True, returns a model pre-trained on ImageNet + """ + model = ResNet(resnet.Bottleneck, [3, 4, 6, 3], avgpool_size=cfg.AUG.RND_CROP[0] // 32) + + if pretrained: + state_dict = resnet.model_zoo.load_url(resnet.model_urls['resnet50']) + + current_state = model.state_dict() + keys = list(state_dict.keys()) + for key in keys: + if not key.startswith('fc.'): + current_state[key] = state_dict[key] + + model.load_state_dict(current_state) + return model + + +def resnet101(pretrained=True, **kwargs): + """Constructs a ResNet-101 model. + + Args: + pretrained (bool): If True, returns a model pre-trained on ImageNet + """ + model = ResNet(resnet.Bottleneck, [3, 4, 23, 3], avgpool_size=cfg.AUG.RND_CROP[0] // 32) + + if pretrained: + state_dict = resnet.model_zoo.load_url(resnet.model_urls['resnet101']) + + current_state = model.state_dict() + keys = list(state_dict.keys()) + for key in keys: + if not key.startswith('fc.'): + current_state[key] = state_dict[key] + + model.load_state_dict(current_state) + return model + + +def resnet152(pretrained=True, **kwargs): + """Constructs a ResNet-152 model. + + Args: + pretrained (bool): If True, returns a model pre-trained on ImageNet + """ + model = ResNet(resnet.Bottleneck, [3, 8, 36, 3], avgpool_size=cfg.AUG.RND_CROP[0] // 32) + + if pretrained: + state_dict = resnet.model_zoo.load_url(resnet.model_urls['resnet152']) + + current_state = model.state_dict() + keys = list(state_dict.keys()) + for key in keys: + if not key.startswith('fc.'): + current_state[key] = state_dict[key] + + model.load_state_dict(current_state) + return model diff --git a/ExtractFeat/trainer.py b/ExtractFeat/trainer.py new file mode 100644 index 0000000..b17841e --- /dev/null +++ b/ExtractFeat/trainer.py @@ -0,0 +1,197 @@ +import os +import sys +from os.path import join as join +import pickle +import pprint +import random +import tqdm +import copy +import logging +import numpy as np +import torch +import torch.nn as nn +import torch.nn.functional as F +from torchvision import transforms +from torch.autograd import Variable +import lib.utils as utils +from lib.config import cfg +from collections import OrderedDict +import datasets.data_loader as data_loader + +import models +import torch.multiprocessing as mp +import torch.distributed as dist +from os.path import join as join + + +class Trainer(object): + def __init__(self, args): + super(Trainer, self).__init__() + self.args = args + self.num_gpus = torch.cuda.device_count() + self.distributed = self.num_gpus > 1 + if self.distributed: + torch.cuda.set_device(args.local_rank) + torch.distributed.init_process_group( + backend="nccl", init_method="env://" + ) + self.device = torch.device("cuda") + + if cfg.SEED > 0: + random.seed(cfg.SEED) + torch.manual_seed(cfg.SEED) + torch.cuda.manual_seed_all(cfg.SEED) + + def setup_logging(self): + self.logger = logging.getLogger(cfg.LOGGER_NAME) + self.logger.setLevel(logging.INFO) + if self.distributed and dist.get_rank() > 0: + return + + ch = logging.StreamHandler(stream=sys.stdout) + ch.setLevel(logging.INFO) + formatter = logging.Formatter("[%(levelname)s: %(asctime)s] %(message)s") + ch.setFormatter(formatter) + self.logger.addHandler(ch) + + if not os.path.exists(cfg.ROOT_DIR): + os.makedirs(cfg.ROOT_DIR) + + fh = logging.FileHandler(os.path.join(cfg.ROOT_DIR, cfg.LOGGER_NAME + '.txt')) + fh.setLevel(logging.INFO) + fh.setFormatter(formatter) + self.logger.addHandler(fh) + + self.logger.info('Training with config:') + self.logger.info(pprint.pformat(cfg)) + + def setup_loader(self): + self.train_loader = data_loader.load_test(cfg.DATA_LOADER.DATA_ROOT, + join(cfg.DATA_LOADER.DATA_ROOT, cfg.DATA_LOADER.LIST, cfg.DATA_LOADER.FOLDER + '_train.txt'), + use_mirror=self.args.mirror) + + self.test_loader = data_loader.load_test(cfg.DATA_LOADER.DATA_ROOT, + join(cfg.DATA_LOADER.DATA_ROOT, cfg.DATA_LOADER.LIST, cfg.DATA_LOADER.FOLDER + '_test.txt'), + use_mirror=self.args.mirror) + + def snapshot_path(self, name, epoch): + path = cfg.ROOT_DIR + pos = path.rfind('/') + path = path[0:pos] + snapshot_folder = join(path, 'snapshot') + return join(snapshot_folder, name + "_" + str(epoch) + ".pth") + + def load_checkpoint(self, netG, netE): + if self.args.resume > 0: + netG_dict = torch.load(self.snapshot_path("netG", self.args.resume), map_location=lambda storage, loc: storage) + current_state = netG.state_dict() + keys = list(current_state.keys()) + for key in keys: + + current_state[key] = netG_dict['module.' + key] + netG.load_state_dict(current_state) + + netE_dict = torch.load(self.snapshot_path("netE", self.args.resume), map_location=lambda storage, loc: storage) + current_state = netE.state_dict() + keys = list(current_state.keys()) + for key in keys: + current_state[key] = netE_dict['module.' + key] + netE.load_state_dict(current_state) + + def init_network(self): + netG = models.__dict__[cfg.MODEL.NET](pretrained=True) + netE = models.classifier.Classifier(class_num=cfg.MODEL.CLASS_NUM, distributed=self.distributed).cuda() + + self.load_checkpoint(netG, netE) + if self.distributed: + sync_netG = netG #nn.SyncBatchNorm.convert_sync_batchnorm(netG) + sync_netE = netE #nn.SyncBatchNorm.convert_sync_batchnorm(netE) + self.netG = torch.nn.parallel.DistributedDataParallel(sync_netG.to(self.device), + device_ids=[self.args.local_rank], output_device=self.args.local_rank) + self.netE = torch.nn.parallel.DistributedDataParallel(sync_netE.to(self.device), + device_ids=[self.args.local_rank], output_device=self.args.local_rank) + else: + self.netG = torch.nn.DataParallel(netG).cuda() + self.netE = torch.nn.DataParallel(netE).cuda() + + def display_dim(self, train_feats, train_labels, test_feats, test_labels): + if (self.distributed == True) and (dist.get_rank() != 0): + return + self.logger.info('shape info train_feats: {}, train_labels: {}'.format(train_feats.shape, train_labels.shape)) + self.logger.info('shape info test_feats: {}, test_labels: {}'.format(test_feats.shape, test_labels.shape)) + + def eval(self, data_loader): + self.netG.eval() + self.netE.eval() + + correct = 0 + tick = 0 + subclasses_correct = np.zeros(cfg.MODEL.CLASS_NUM) + subclasses_tick = np.zeros(cfg.MODEL.CLASS_NUM) + + # data set + n_samples = data_loader.dataset.__len__() + feats = torch.zeros(n_samples, cfg.MODEL.IN_DIM).cuda() + labels = np.zeros((n_samples,), dtype='int') + + probs = torch.zeros(n_samples, cfg.MODEL.CLASS_NUM) + preds = np.zeros((n_samples,), dtype='int') + + with torch.no_grad(): + index = 0 + for imgs, gtlabels in tqdm.tqdm(data_loader): + batch_size = imgs.size(0) + imgs = Variable(imgs.cuda()) + _, _unsup_pool5_out = self.netG(imgs) + _, _unsup_logits_out = self.netE(_unsup_pool5_out) + prob = F.softmax(_unsup_logits_out, dim=1) + pred = prob.data.cpu().numpy().argmax(axis=1) + + feats[index:index + batch_size, :] = _unsup_pool5_out.data + labels[index:index + batch_size] = gtlabels.data.cpu().numpy() + probs[index:index + batch_size, :] = prob.data + preds[index:index + batch_size] = pred + + index += batch_size + gtlabels = gtlabels.numpy() + for i in range(pred.size): + subclasses_tick[gtlabels[i]] += 1 + if pred[i] == gtlabels[i]: + correct += 1 + subclasses_correct[pred[i]] += 1 + tick += 1 + + feats = feats.data.cpu().numpy() + probs = probs.data.cpu().numpy() + + #correct = correct * 1.0 / tick + #subclasses_result = np.divide(subclasses_correct, subclasses_tick) + #mean_class_acc = subclasses_result.mean() + #zeors_num = subclasses_result[subclasses_result == 0].shape[0] + #mean_acc_str = "*** mean class acc = {:.2%}, overall = {:.2%}, missing = {:d}".format(mean_class_acc, correct, zeors_num) + #print(mean_acc_str) + + return feats, labels, probs, preds + + def compute_feats(self): + train_feats, train_labels, train_probs, train_preds = self.eval(self.train_loader) + test_feats, test_labels, _, _ = self.eval(self.test_loader) + + self.display_dim(train_feats, train_labels, test_feats, test_labels) + + if (self.distributed == False) or (dist.get_rank() == 0): + if self.args.mirror == False: + result_folder = os.path.join(cfg.ROOT_DIR, 'result') + else: + result_folder = os.path.join(cfg.ROOT_DIR, 'result_mirror') + if not os.path.exists(result_folder): + os.mkdir(result_folder) + pickle.dump({'feats': train_feats, 'labels': train_labels}, open(join(result_folder, cfg.DATA_LOADER.FOLDER + '_train.pkl'), 'wb')) + pickle.dump({'feats': test_feats, 'labels': test_labels}, open(join(result_folder, cfg.DATA_LOADER.FOLDER + '_test.pkl'), 'wb')) + pickle.dump({'probs': train_probs, 'labels': train_preds }, open(join(result_folder, cfg.DATA_LOADER.FOLDER + '_probs.pkl'), 'wb')) + + def train(self): + self.setup_logging() + self.setup_loader() + self.init_network() + self.compute_feats()