diff options
| -rw-r--r-- | cli/app/search/search_class.py | 10 | ||||
| -rw-r--r-- | cli/app/search/search_dense.py | 8 |
2 files changed, 9 insertions, 9 deletions
diff --git a/cli/app/search/search_class.py b/cli/app/search/search_class.py index fb672c3..f7b2136 100644 --- a/cli/app/search/search_class.py +++ b/cli/app/search/search_class.py @@ -157,7 +157,7 @@ def find_nearest_vector(sess, generator, opt_fp_in, opt_dims, out_images, out_la train_step_z = tf.train.AdamOptimizer(z_lr).minimize(loss, var_list=[input_z], name='AdamOpterZ') train_step_y = tf.train.AdamOptimizer(y_lr).minimize(loss, var_list=[input_y], name='AdamOpterY') - target_im, fp_frames = load_target_image(opt_fp_in) + target_im, fp_frames, fn_base = load_target_image(opt_fp_in) # crop image and convert to format for next script phi_target_for_inversion = resize_and_crop_image(target_im, 512) @@ -199,7 +199,7 @@ def find_nearest_vector(sess, generator, opt_fp_in, opt_dims, out_images, out_la phi_guess = sess.run(output) guess_im = imgrid(imconvert_uint8(phi_guess), cols=1) - imwrite(join(app_cfg.DIR_OUTPUTS, 'frame_{}_final.png'.format(opt_tag)), guess_im) + imwrite(join(app_cfg.DIR_OUTPUTS, 'frame-{}-{}-final.png'.format(opt_tag, fn_base)), guess_im) z_guess, y_guess = sess.run([input_z, input_y]) out_images[index] = phi_target_for_inversion @@ -224,10 +224,10 @@ def export_video(fp_frames): def load_target_image(opt_fp_in): print("Loading {}".format(opt_fp_in)) fn = os.path.basename(opt_fp_in) - fbase, ext = os.path.splitext(fn) - fp_frames = "frames_{}_{}".format(fbase, int(time.time() * 1000)) + fn_base, ext = os.path.splitext(fn) + fp_frames = "frames_{}_{}".format(fn_base, int(time.time() * 1000)) fp_frames_fullpath = join(app_cfg.DIR_OUTPUTS, fp_frames) print("Output to {}".format(fp_frames_fullpath)) os.makedirs(fp_frames_fullpath, exist_ok=True) target_im = imread(opt_fp_in) - return target_im, fp_frames + return target_im, fp_frames, fn_base diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py index fe0c1aa..ac4dc59 100644 --- a/cli/app/search/search_dense.py +++ b/cli/app/search/search_dense.py @@ -396,9 +396,9 @@ def find_dense_embedding_for_images(params): print("Total iterations: {}".format(params.inv_it)) for _ in range(params.inv_it): - _inv_loss, _mse_loss, _feat_loss, _rec_loss, _reg_loss, _dist_loss,\ + _inv_loss, _mse_loss, _feat_loss,\ _lrate, _ = sess.run([inv_loss, mse_loss, feat_loss, - rec_loss, reg_loss, dist_loss, lrate, inv_train_op]) + lrate, inv_train_op]) if params.clipping or params.stochastic_clipping: sess.run(clip_latent) @@ -408,9 +408,9 @@ def find_dense_embedding_for_images(params): # Log losses. etime = time.time() - start_time print('It [{:8d}] time [{:5.1f}] total [{:.4f}] mse [{:.4f}] ' - 'feat [{:.4f}] rec [{:.4f}] reg [{:.4f}] dist [{:.4f}] ' + 'feat [{:.4f}] ' 'lr [{:.4f}]'.format(it, etime, _inv_loss, _mse_loss, - _feat_loss, _rec_loss, _reg_loss, _dist_loss, _lrate)) + _feat_loss, _lrate)) sys.stdout.flush() |