else:
print("Create segmentation.")
content_segmentation, style_segmentation = compute_segmentation(args.content_image, args.style_image)
cv2.imwrite(change_filename(args.seg_dir, args.content_image, '_seg_raw', '.png'), content_segmentation)
cv2.imwrite(change_filename(args.seg_dir, args.style_image, '_seg_raw', '.png'), style_segmentation)
content_segmentation_masks, style_segmentation_masks = merge_segments(content_segmentation, style_segmentation,
args.semantic_thresh, args.similarity_metric)
cv2.imwrite(change_filename(args.seg_dir, args.content_image, '_seg', '.png'),
reduce_dict(content_segmentation_masks, content_image))
cv2.imwrite(change_filename(args.seg_dir, args.style_image, '_seg', '.png'),
reduce_dict(style_segmentation_masks, style_image))
if args.init == "noise":
random_noise_scaling_factor = 0.0001
random_noise = np.random.randn(*content_image.shape).astype(np.float32)
init_image = vgg.postprocess(random_noise * random_noise_scaling_factor).astype(np.float32)
elif args.init == "content":
init_image = content_image
elif args.init == "style":
init_image = style_image
else:
print("Init image parameter {} unknown.".format(args.init))
exit(1)
result = style_transfer(content_image, style_image, mask_for_tf(content_segmentation_masks),
mask_for_tf(style_segmentation_masks), init_image, args)
save_image(result, os.path.join(args.results_dir, "final_transfer_image.png"))
cv2.imwrite(
change_filename(result_dir,
os.path.basename(args.content_image).split('.')[0],
'_seg', '.jpg'),
reduce_dict(content_segmentation_masks, content_image))
cv2.imwrite(
change_filename(result_dir,
os.path.basename(args.style_image).split('.')[0],
'_seg', '.jpg'),
reduce_dict(style_segmentation_masks, style_image))
if args.init == "noise":
random_noise_scaling_factor = 0.0001
random_noise = np.random.randn(*content_image.shape).astype(np.float32)
init_image = vgg.postprocess(
random_noise * random_noise_scaling_factor).astype(np.float32)
elif args.init == "content":
init_image = content_image
elif args.init == "style":
init_image = style_image
else:
print("Init image parameter {} unknown.".format(args.init))
exit(0)
result = style_transfer(content_image, style_image,
mask_for_tf(content_segmentation_masks),
mask_for_tf(style_segmentation_masks), init_image,
result_dir, timestamp, args)
save_image(result, os.path.join(result_dir, "final_transfer_image.png"))