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authorJules Laplace <julescarbon@gmail.com>2020-02-10 18:48:15 +0100
committerJules Laplace <julescarbon@gmail.com>2020-02-10 18:48:15 +0100
commit8197048ae7b33ce27a810ed43ea188f3815c0f5b (patch)
tree8c07a69f014df7afa00a20485597177c15e12932 /cli
parent67e5e02456ff796dba4601d0305fbc08e358cce9 (diff)
feature loss on quadrants
Diffstat (limited to 'cli')
-rw-r--r--cli/app/commands/biggan/extract_dense_vectors.py2
-rw-r--r--cli/app/search/search_class.py5
2 files changed, 4 insertions, 3 deletions
diff --git a/cli/app/commands/biggan/extract_dense_vectors.py b/cli/app/commands/biggan/extract_dense_vectors.py
index e8f0587..54f9762 100644
--- a/cli/app/commands/biggan/extract_dense_vectors.py
+++ b/cli/app/commands/biggan/extract_dense_vectors.py
@@ -10,7 +10,7 @@ from app.search.params import timestamp
@click.command('')
@click.option('-f', '--folder_id', 'opt_folder_id', type=int,
help='Folder ID to process')
-@click.option('-ls', '--latent_steps', 'opt_latent_steps', default=2000, type=int,
+@click.option('-ls', '--latent_steps', 'opt_latent_steps', default=1000, type=int,
help='Number of optimization iterations')
@click.option('-ds', '--dense_steps', 'opt_dense_steps', default=2000, type=int,
help='Number of optimization iterations')
diff --git a/cli/app/search/search_class.py b/cli/app/search/search_class.py
index 371316e..3e36a02 100644
--- a/cli/app/search/search_class.py
+++ b/cli/app/search/search_class.py
@@ -120,8 +120,9 @@ def find_nearest_vector(sess, generator, opt_fp_in, opt_dims, out_images, out_la
## if computing Feature loss, use these encoders
if opt_use_feature_detector:
print("Initializing feature detector...")
- pix_square_diff = tf.square((target - output) / 2.0)
- mse_loss = tf.reduce_mean(pix_square_diff)
+ # pix_square_diff = tf.square((target - output) / 2.0)
+ # mse_loss = tf.reduce_mean(pix_square_diff)
+ mse_loss = tf.compat.v1.losses.mean_squared_error(target, output)
feature_extractor = hub.Module("https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1")