From 7609d1c8b046c2c59d81f8df7dea3e0fc77b544f Mon Sep 17 00:00:00 2001 From: Yuchen Fan Date: Wed, 12 Apr 2017 22:34:35 -0500 Subject: [PATCH] better model and config --- model_pixel_up.py | 11 ++++++++++- run.sh | 10 +++++----- 2 files changed, 15 insertions(+), 6 deletions(-) diff --git a/model_pixel_up.py b/model_pixel_up.py index 2084add..74e212a 100644 --- a/model_pixel_up.py +++ b/model_pixel_up.py @@ -10,7 +10,16 @@ def build_model(x, scale, training, reuse): for i in range(6): x = util.crop_by_pixel(x, 1) + conv(x, hidden_size, bottleneck_size, training, 'lr_conv'+str(i), reuse) x = util.lrelu(x) - x = tf.image.resize_nearest_neighbor(x, tf.shape(x)[1:3] * scale) + tf.layers.conv2d_transpose(x, hidden_size, scale, strides=scale, activation=None, name='up', reuse=reuse) + if (scale == 4): + scale = 2 + x = tf.layers.conv2d_transpose(x, hidden_size, scale, strides=scale, activation=None, name='up1', reuse=reuse) + x = util.crop_by_pixel(x, 1) + conv(x, hidden_size, bottleneck_size, training, 'up_conv', reuse) + x = util.lrelu(x) + hidden_size = 64 + x = tf.layers.conv2d_transpose(x, hidden_size, scale, strides=scale, activation=None, name='up2', reuse=reuse) + else: + hidden_size = 64 + x = tf.layers.conv2d_transpose(x, hidden_size, scale, strides=scale, activation=None, name='up', reuse=reuse) for i in range(4): x = util.crop_by_pixel(x, 1) + conv(x, hidden_size, bottleneck_size, training, 'hr_conv'+str(i), reuse) x = util.lrelu(x) diff --git a/run.sh b/run.sh index 031d7a8..5a2a837 100755 --- a/run.sh +++ b/run.sh @@ -24,10 +24,10 @@ set -x EXPR_NAME="try" TRAIN_DIR="tmp" -MODEL_NAME="model_resnet_up" +MODEL_NAME="model_pixel_up" DATA_NAME="data_residual" -HR_FLIST="flist/hr.flist" -LR_FLIST="flist/lrX2.flist" +HR_FLIST="flist/hr_tv.flist" +LR_FLIST="flist/lrX2_bicubic_tv.flist" SCALE=2 LEARNING_RATE=0.001 @@ -49,10 +49,10 @@ ARGS="--data_name=$DATA_NAME --hr_flist=$HR_FLIST --lr_flist=$LR_FLIST --model_n iter=0 rate=$LEARNING_RATE -for i in `seq 1 8`; +for i in `seq 1 16`; do python $SCRIPT $ARGS --model_file_in=$MODEL_FILE-$iter --model_file_out=$MODEL_FILE-$((iter+1)) --learning_rate=$rate iter=$((iter+1)) - rate=$(echo "$rate" | awk '{print $1*0.5}') + rate=$(echo "$rate" | awk '{print $1*0.618}') echo "Iteration $iter Finished" done