def make_edge_smooth(dataset_name, img_size) :
check_folder(os.path.dirname(os.path.dirname(__file__))+'/dataset/{}/{}'.format(dataset_name, 'smooth'))
file_list = glob(os.path.dirname(os.path.dirname(__file__))+'/dataset/{}/{}/*.*'.format(dataset_name, 'style'))
save_dir = os.path.dirname(os.path.dirname(__file__))+'/dataset/{}/smooth'.format(dataset_name)
kernel_size = 5
kernel = np.ones((kernel_size, kernel_size), np.uint8)
gauss = cv2.getGaussianKernel(kernel_size, 0)
gauss = gauss * gauss.transpose(1, 0)
for f in tqdm(file_list) :
file_name = os.path.basename(f)
bgr_img = cv2.imread(f)
gray_img = cv2.imread(f, 0)
bgr_img = cv2.resize(bgr_img, (img_size, img_size))
pad_img = np.pad(bgr_img, ((2, 2), (2, 2), (0, 0)), mode='reflect')
gray_img = cv2.resize(gray_img, (img_size, img_size))
edges = cv2.Canny(gray_img, 100, 200)
dilation = cv2.dilate(edges, kernel)
gauss_img = np.copy(bgr_img)
idx = np.where(dilation != 0)
for i in range(np.sum(dilation != 0)):
gauss_img[idx[0][i], idx[1][i], 0] = np.sum(
np.multiply(pad_img[idx[0][i]:idx[0][i] + kernel_size, idx[1][i]:idx[1][i] + kernel_size, 0], gauss))
gauss_img[idx[0][i], idx[1][i], 1] = np.sum(
np.multiply(pad_img[idx[0][i]:idx[0][i] + kernel_size, idx[1][i]:idx[1][i] + kernel_size, 1], gauss))
gauss_img[idx[0][i], idx[1][i], 2] = np.sum(
np.multiply(pad_img[idx[0][i]:idx[0][i] + kernel_size, idx[1][i]:idx[1][i] + kernel_size, 2], gauss))
cv2.imwrite(os.path.join(save_dir, file_name), gauss_img)
def check_args(args):
# check folder
check_folder(args.checkpoint_dir)
check_folder(args.result_dir)
check_folder(args.log_dir)
# check hyperparameter
assert args.epoch >= 1, 'epochs must >= 1 ...'
assert args.batch_size >= 1, 'batch size must >= 1 ...'
assert args.z_dim >= 1, 'dimension of noise vector must >= 1'
return args
pbar = tqdm(total=total)
vid.set(cv2.CAP_PROP_POS_FRAMES, 0)
while ret:
ret, frame = vid.read()
if frame is None:
print('Warning: got empty frame.')
continue
img = convert_image(frame, img_size)
fake_img = sess.run(test_generated, feed_dict={test_real: img})
fake_img = inverse_image(fake_img)
if if_adjust_brightness:
fake_img = cv2.cvtColor(adjust_brightness_from_src_to_dst(fake_img, frame), cv2.COLOR_BGR2RGB)
else:
fake_img = cv2.cvtColor(fake_img, cv2.COLOR_BGR2RGB)
fake_img = cv2.resize(fake_img, (width, height))
out.write(fake_img)
pbar.update(1)
pbar.close()
vid.release()
# cv2.destroyAllWindows()
return os.path.join(output, vid_name)
if __name__ == '__main__':
arg = parse_args()
check_folder(arg.output)
info = cvt2anime_video(arg.video, arg.output, arg.checkpoint_dir, output_format=arg.output_format, if_adjust_brightness=arg.if_adjust_brightness)
print(f'output video: {info}')
