From da243d0a0e00e8dd9f4ab3d3d5e973230b554347 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Wed, 8 Jan 2020 10:56:42 +0100 Subject: reprocess --- cli/app/search/search_dense.py | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) (limited to 'cli/app') diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py index 7c0c728..fe0c1aa 100644 --- a/cli/app/search/search_dense.py +++ b/cli/app/search/search_dense.py @@ -253,32 +253,32 @@ def find_dense_embedding_for_images(params): gen_feat = gen_feat_ex["InceptionV3/Conv2d_1a_3x3"] target_feat = target_feat_ex["InceptionV3/Conv2d_1a_3x3"] feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1]) - feat_loss = tf.reduce_mean(feat_square_diff) * 0.15 - img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.15 + feat_loss = tf.reduce_mean(feat_square_diff) * 0.25 + img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.25 gen_feat = gen_feat_ex["InceptionV3/Conv2d_2a_3x3"] target_feat = target_feat_ex["InceptionV3/Conv2d_2a_3x3"] feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1]) - feat_loss += tf.reduce_mean(feat_square_diff) * 0.15 - img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.15 + feat_loss += tf.reduce_mean(feat_square_diff) * 0.25 + img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.25 - gen_feat = gen_feat_ex["InceptionV3/Conv2d_3b_1x1"] - target_feat = target_feat_ex["InceptionV3/Conv2d_3b_1x1"] - feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1]) - feat_loss += tf.reduce_mean(feat_square_diff) * 0.15 - img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.15 + # gen_feat = gen_feat_ex["InceptionV3/Conv2d_3b_1x1"] + # target_feat = target_feat_ex["InceptionV3/Conv2d_3b_1x1"] + # feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1]) + # feat_loss += tf.reduce_mean(feat_square_diff) * 0.25 + # img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.25 gen_feat = gen_feat_ex["InceptionV3/Conv2d_4a_3x3"] target_feat = target_feat_ex["InceptionV3/Conv2d_4a_3x3"] feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1]) - feat_loss += tf.reduce_mean(feat_square_diff) * 0.15 - img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.15 + feat_loss += tf.reduce_mean(feat_square_diff) * 0.25 + img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.25 gen_feat = gen_feat_ex["InceptionV3/Mixed_7a"] target_feat = target_feat_ex["InceptionV3/Mixed_7a"] feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1]) - feat_loss += tf.reduce_mean(feat_square_diff) * 0.4 - img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.4 + feat_loss += tf.reduce_mean(feat_square_diff) * 0.25 + img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.25 else: feat_loss = tf.constant(0.0) -- cgit v1.2.3-70-g09d2