From 7fc01cb41ab974915b16f907f0fbe776d800824b Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Sun, 15 Dec 2019 11:45:11 +0100 Subject: 17 --- inversion/image_inversion_inception.py | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) (limited to 'inversion/image_inversion_inception.py') diff --git a/inversion/image_inversion_inception.py b/inversion/image_inversion_inception.py index b220a55..80c1729 100644 --- a/inversion/image_inversion_inception.py +++ b/inversion/image_inversion_inception.py @@ -254,14 +254,14 @@ if params.features: 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) * 0.25 - img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.25 + feat_loss = tf.reduce_mean(feat_square_diff) * 0.5 + img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.5 - 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) * 0.25 - 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) * 0.25 + # 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"] @@ -269,17 +269,17 @@ if params.features: # feat_loss += tf.reduce_mean(feat_square_diff) * 0.2 # img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.2 - 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) * 0.25 - 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) * 0.25 + # 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) * 0.25 - img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.25 + feat_loss += tf.reduce_mean(feat_square_diff) * 0.5 + img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.5 else: feat_loss = tf.constant(0.0) -- cgit v1.2.3-70-g09d2