diff options
Diffstat (limited to 'cli/app/search/search_dense.py')
| -rw-r--r-- | cli/app/search/search_dense.py | 9 |
1 files changed, 5 insertions, 4 deletions
diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py index ac4dc59..46183c7 100644 --- a/cli/app/search/search_dense.py +++ b/cli/app/search/search_dense.py @@ -124,6 +124,8 @@ def find_dense_embedding_for_images(params): else: gen_img = generator(latent, signature=gen_signature) + gen_img_orig = gen_img + # Convert generated image to channels_first. gen_img = tf.transpose(gen_img, [0, 3, 1, 2]) @@ -393,7 +395,7 @@ def find_dense_embedding_for_images(params): ]) # Main optimization loop. - print("Total iterations: {}".format(params.inv_it)) + print("Beginning dense iteration...") for _ in range(params.inv_it): _inv_loss, _mse_loss, _feat_loss,\ @@ -435,15 +437,14 @@ def find_dense_embedding_for_images(params): out_labels[out_pos:out_pos+BATCH_SIZE] = label_batch out_err[out_pos:out_pos+BATCH_SIZE] = rec_err_batch - gen_images = sess.run(gen_img) + gen_images = sess.run(gen_img_orig) images = vs.data2img(gen_images) # write encoding, latent to pkl file for i in range(BATCH_SIZE): out_i = out_pos + i sample_fn, ext = os.path.splitext(sample_fns[out_i]) - image = Image.fromarray(images[i]) - image = vs.grid_transform(image) + image = Image.fromarray(image) fp = BytesIO() image.save(fp, format='png') data = upload_bytes_to_cortex(params.folder_id, sample_fn + "-inverse.png", fp, "image/png") |