Skip to content

Latest commit

 

History

History
60 lines (46 loc) · 5.46 KB

MODEL_ZOO.md

File metadata and controls

60 lines (46 loc) · 5.46 KB
Raw

MODEL ZOO

MSCOCO dataset

Model Backbone Detector Input Size AP Speed Download Config Training Log
Simple Baseline ResNet50 YOLOv3 256x192 70.6 2.94 iter/s model cfg log
Fast Pose ResNet50 YOLOv3 256x192 72.0 3.54 iter/s model cfg log
Fast Pose (DUC) ResNet50 - unshuffle YOLOv3 256x192 72.4 2.91 iter/s model cfg log
HRNet HRNet-W32 YOLOv3 256x192 72.5 2.13 iter/s model cfg log
Fast Pose (DCN) ResNet50 - dcn YOLOv3 256x192 72.8 2.94 iter/s model cfg log
Fast Pose (DUC) ResNet152 YOLOv3 256x192 73.3 1.62 iter/s model cfg log

Notes

  • All models are trained on keypoint train 2017 images which contains at least one human with keypoint annotations (64115 images).
  • The evaluation is done on COCO keypoint val 2017 (5000 images).
  • Flip test is used by default.
  • One TITAN XP is used for speed test, with batch_size=64 in each iteration.
  • Offline human detection results are used in speed test.
  • FastPose is our own network design. Paper coming soon!

Halpe dataset (26 keypoints)

Model Backbone Detector Input Size AP Speed Download Config Training Log
Fast Pose ResNet50 YOLOv3 256x192 69.0 3.54 iter/s Google Baidu cfg log

You can run with:

python scripts/demo_inference.py --cfg configs/halpe_26/resnet/256x192_res50_lr1e-3_1x.yaml --checkpoint pretrained_models/halpe26_fast_res50_256x192.pth --indir examples/demo/ --save_img

Notes

  • More models coming soon!

Halpe dataset (136 keypoints)

Model Backbone Detector Input Size AP Speed Download Config Training Log
Fast Pose ResNet50 YOLOv3 256x192 69.0 3.54 iter/s Google Baidu cfg log

You can run with:

python scripts/demo_inference.py --cfg configs/halpe_136/resnet/256x192_res50_lr1e-3_2x-regression.yaml --checkpoint pretrained_models/halpe136_fast_res50_256x192.pth --indir examples/demo/ --save_img

Coco-wholebody dataset (133 keypoints)

Model Backbone Detector Input Size Speed Download Config Training Log
Fast Pose ResNet50 YOLOv3 256x192 3.54 iter/s Google cfg log

You can run with:

cd scripts
python3 demo_inference.py --cfg configs/coco_wholebody/resnet/256x192_res50_lr1e-3_1x.yaml --checkpoint {CHECKPOINT-PATH} --indir {IMAGE_DIR-PATH} --save_img

Notes

  • More models coming soon!