diff options
| -rw-r--r-- | inversion/image_inversion_inception.py | 22 |
1 files changed, 14 insertions, 8 deletions
diff --git a/inversion/image_inversion_inception.py b/inversion/image_inversion_inception.py index 570c1ac..a97bf0f 100644 --- a/inversion/image_inversion_inception.py +++ b/inversion/image_inversion_inception.py @@ -254,26 +254,32 @@ 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) * 0.2 + img_feat_err = tf.reduce_mean(feat_square_diff, axis=1) * 0.2 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 + 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_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 + 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 + 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/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) * 0.2 + img_feat_err += tf.reduce_mean(feat_square_diff, axis=1) * 0.2 else: feat_loss = tf.constant(0.0) |