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| author | Jules Laplace <julescarbon@gmail.com> | 2020-01-08 12:10:06 +0100 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2020-01-08 12:10:06 +0100 |
| commit | ca032925551726fbca9e3fffa76aa766fdc37499 (patch) | |
| tree | 698ca326ec3962e7484be4be4c4f34e3d29c245c /cli/app/search/search_class.py | |
| parent | 93ffa86d32844e2517409bf507d38e2f766011e3 (diff) | |
removing
Diffstat (limited to 'cli/app/search/search_class.py')
| -rw-r--r-- | cli/app/search/search_class.py | 10 |
1 files changed, 5 insertions, 5 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 |