diff options
Diffstat (limited to 'cli/app/search/search_class.py')
| -rw-r--r-- | cli/app/search/search_class.py | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/cli/app/search/search_class.py b/cli/app/search/search_class.py index 40801d6..0c3fd29 100644 --- a/cli/app/search/search_class.py +++ b/cli/app/search/search_class.py @@ -48,7 +48,8 @@ feature_layer_names = { def find_nearest_vector_for_images(paths, opt_dims, opt_steps, opt_video, opt_tag, opt_limit=-1, opt_stochastic_clipping=True, opt_label_clipping=True, - opt_use_feature_detector=False, opt_feature_layers=[1,2,4,7], opt_snapshot_interval=20, opt_clip_interval=500): + opt_use_feature_detector=False, opt_feature_layers=[1,2,4,7], opt_snapshot_interval=20, opt_clip_interval=500, + opt_folder_id=59): tf.reset_default_graph() sess = tf.compat.v1.Session() print("Initializing generator...") @@ -57,7 +58,7 @@ def find_nearest_vector_for_images(paths, opt_dims, opt_steps, opt_video, opt_ta fp_inverses = os.path.join(app_cfg.DIR_INVERSES, opt_tag) os.makedirs(fp_inverses, exist_ok=True) # save_params_latent(fp_inverses, opt_tag) - save_params_dense(fp_inverses, opt_tag) + save_params_dense(fp_inverses, opt_tag, folder_id=opt_folder_id) out_file = h5py.File(join(fp_inverses, 'dataset.latent.hdf5'), 'w') out_images = out_file.create_dataset('xtrain', (len(paths), 3, 512, 512,), dtype='float32') out_labels = out_file.create_dataset('ytrain', (len(paths), 1000,), dtype='float32') |