def main():
filepath = lambda p: os.path.abspath(
os.path.realpath(os.path.expanduser(p)))
parser = argparse.ArgumentParser(
prog='run.py',
description=
'Style Transfer script applying style of one image to another one')
parser.add_argument('--style_image',
'-si',
type=filepath,
metavar='STYLE_IMAGE',
required=True,
help='Path to image which style will be extracted')
parser.add_argument('--content_image',
'-ci',
type=filepath,
metavar='CONTENT_IMAGE',
required=True,
help='Path to image which content will be extracted')
parser.add_argument(
'--output_folder',
'-of',
type=filepath,
metavar='OUTPUT_PATH',
required=True,
help='Folder path where the output image will be stored')
parser.add_argument('--epochs',
'-e',
type=int,
metavar='N_EPOCHS',
default=1,
help='Number of optimization steps')
parser.add_argument(
'--white_noise',
'-wn',
action='store_true',
help=
'If set to True, initial image is white noise and not the content image'
)
args = parser.parse_args()
style_image = Processing.load_image(args.style_image)
content_image = Processing.load_image(args.content_image)
assert style_image.size() == content_image.size(
), "Style and content images must be the same sizes"
if args.white_noise:
LOGGER.debug('Preparing input image as white noise')
input_image = torch.randn(content_image.data.size(),
device=Utils.DEVICE)
else:
LOGGER.debug('Preparing input image as the content image')
input_image = content_image.clone()
final_image = input_image.clone()
LOGGER.info('Starting the Style Transfer')
run_style_transfer(final_image,
content_image,
style_image,
epochs=args.epochs)
LOGGER.info('Ended the Style Transfer')
os.makedirs(args.output_folder, exist_ok=True)
show_image(input_image,
'Input image',
save_path=os.path.join(args.output_folder, 'input_image'))
show_image(content_image,
'Content image',
save_path=os.path.join(args.output_folder, 'content_image'))
show_image(style_image,
'Style image',
save_path=os.path.join(args.output_folder, 'style_image'))
show_image(final_image,
'Final image',
save_path=os.path.join(args.output_folder, 'final_image'))
