7abc fixed

1 files changed, 26 insertions, 20 deletions

diff --git a/inversion/image_inversion_inception.py b/inversion/image_inversion_inception.py
index 80c1729..5e68bc9 100644
--- a/inversion/image_inversion_inception.py
+++ b/inversion/image_inversion_inception.py
@@ -220,17 +220,23 @@ if params.features:
   gen_feat_ex = feature_extractor(dict(images=gen_img_1), as_dict=True, signature='image_feature_vector')
   target_feat_ex = feature_extractor(dict(images=target_img_1), as_dict=True, signature='image_feature_vector')
 
-  # 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) * 0.5
-  # img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.5
+  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) * 0.334
+  img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.334
 
-  # # gen_feat = gen_feat_ex["InceptionV3/Mixed_6b"]
-  # # target_feat = target_feat_ex["InceptionV3/Mixed_6b"]
-  # # feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1])
-  # # feat_loss += tf.reduce_mean(feat_square_diff) * 0.16
-  # # img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.16
+  gen_feat = gen_feat_ex["InceptionV3/Mixed_7b"]
+  target_feat = target_feat_ex["InceptionV3/Mixed_7b"]
+  feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1])
+  feat_loss += tf.reduce_mean(feat_square_diff) * 0.333
+  img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.333
+
+  gen_feat = gen_feat_ex["InceptionV3/Mixed_7c"]
+  target_feat = target_feat_ex["InceptionV3/Mixed_7c"]
+  feat_square_diff = tf.reshape(tf.square(gen_feat - target_feat), [BATCH_SIZE, -1])
+  feat_loss += tf.reduce_mean(feat_square_diff) * 0.333
+  img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.333
 
   # # gen_feat = gen_feat_ex["InceptionV3/Mixed_5a"]
   # # target_feat = target_feat_ex["InceptionV3/Mixed_5a"]
@@ -251,11 +257,11 @@ if params.features:
   # # img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.17
 
   # conv1 1, conv1 2, conv3 2 and conv4 2
-  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) * 0.5
-  img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.5
+  # 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) * 0.5
+  # 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"]
@@ -275,11 +281,11 @@ if params.features:
   # 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) * 0.5
-  img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.5
+  # 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) * 0.5
+  # img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.5
 
 else:
   feat_loss = tf.constant(0.0)