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| author | Jules Laplace <julescarbon@gmail.com> | 2020-01-16 04:06:17 +0100 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2020-01-16 04:06:17 +0100 |
| commit | 36d6ab100116f60deb33b622910b1132cb1752e1 (patch) | |
| tree | e8998f0b6c4e6b6da84208496423431b5c06f131 | |
| parent | 887c6874ff8d7bf44ea0e039f777234007398b55 (diff) | |
idk why im still using this h5py thing
| -rw-r--r-- | cli/app/search/search_dense.py | 11 |
1 files changed, 5 insertions, 6 deletions
diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py index df6edd7..a07e15b 100644 --- a/cli/app/search/search_dense.py +++ b/cli/app/search/search_dense.py @@ -431,12 +431,6 @@ def find_dense_embedding_for_images(params, opt_tag="inverse_" + timestamp(), op # Save images that are ready. label_trained, latent_trained, enc_trained, rec_err_trained = sess.run([label, latent, encoding, img_rec_err]) - count = len(latent_trained) - out_lat[out_pos:out_pos+count] = latent_trained - out_enc[out_pos:out_pos+count] = enc_trained - out_images[out_pos:out_pos+count] = image_batch - out_labels[out_pos:out_pos+count] = label_trained - out_err[out_pos:out_pos+count] = rec_err_trained gen_images = sess.run(gen_img_orig) images = vs.data2img(gen_images) @@ -466,6 +460,11 @@ def find_dense_embedding_for_images(params, opt_tag="inverse_" + timestamp(), op 'encoding': out_enc[out_i], } write_pickle(out_data, fp_out_pkl) + out_lat[out_i] = latent_trained[i] + out_enc[out_i] = enc_trained[i] + out_images[out_i] = image_batch[i] + out_labels[out_i] = label_trained[i] + out_err[out_i] = rec_err_trained[i] out_pos += BATCH_SIZE if params.max_batches > 0 and (out_pos / BATCH_SIZE) >= params.max_batches: |