class PhotoStyle():
def __init__(self, model_path=MODEL_PATH, use_cuda=True):
self.p_wct = PhotoWCT()
self.p_wct.load_state_dict(torch.load(model_path))
self.use_cuda = use_cuda
if use_cuda:
self.p_wct.cuda(0)
def stylize(self,
content_image_path,
style_image_path,
output_image_path,
content_seg_path=None,
style_seg_path=None,
smooth=True,
verbose=False):
process_stylization.stylization(
p_wct=self.p_wct,
content_image_path=content_image_path,
style_image_path=style_image_path,
content_seg_path=content_seg_path,
style_seg_path=style_seg_path,
output_image_path=output_image_path,
cuda=self.use_cuda,
smooth=smooth,
verbose=verbose,
)
def load_model(model='./PhotoWCTModels/photo_wct.pth', fast=True, cuda=1):
"""load model, fast=lighter version"""
# Load model
p_wct = PhotoWCT()
p_wct.load_state_dict(torch.load(model))
if fast:
from photo_gif import GIFSmoothing
p_pro = GIFSmoothing(r=35, eps=0.001)
else:
from photo_smooth import Propagator
p_pro = Propagator()
if cuda:
p_wct.cuda(0)
return p_wct, p_pro
def setup(opts):
p_wct = PhotoWCT()
p_wct.load_state_dict(torch.load(PRETRAINED_MODEL_PATH))
if opts['propagation_mode'] == 'fast':
from photo_gif import GIFSmoothing
p_pro = GIFSmoothing(r=35, eps=0.001)
else:
from photo_smooth import Propagator
p_pro = Propagator()
if torch.cuda.is_available():
p_wct.cuda(0)
return {
'p_wct': p_wct,
'p_pro': p_pro,
}
class StyleTransfer_Engine:
def __init__(self):
# Load model
self.p_wct = PhotoWCT()
self.p_wct.load_state_dict(
torch.load('./PhotoWCTModels/photo_wct.pth'))
self.p_wct.cuda(0)
self.p_pro = Propagator()
def run(self, content, style):
out = stylization(stylization_module=self.p_wct,
smoothing_module=self.p_pro,
cont_img=content,
styl_img=style,
cuda=1,
save_intermediate=False,
no_post=False)
return out
def main():
parser = argparse.ArgumentParser(
description='Photorealistic Image Stylization')
parser.add_argument(
'--model',
default='./PhotoWCTModels/photo_wct.pth',
help=
'Path to the PhotoWCT model. These are provided by the PhotoWCT submodule, please use `git submodule update --init --recursive` to pull.'
)
parser.add_argument('--content_image_path',
default='./images/content1.png')
parser.add_argument('--content_seg_path', default=[])
parser.add_argument('--style_image_path', default='./images/style1.png')
parser.add_argument('--style_seg_path', default=[])
parser.add_argument('--output_image_path',
default='./results/example1.png')
parser.add_argument('--cuda', type=int, default=1, help='Enable CUDA.')
args = parser.parse_args()
# Load model
p_wct = PhotoWCT()
try:
p_wct.load_state_dict(torch.load(args.model))
except:
print("Fail to load PhotoWCT models. PhotoWCT submodule not updated?")
exit()
if args.cuda:
p_wct.cuda(0)
process_stylization.stylization(
p_wct=p_wct,
content_image_path=args.content_image_path,
style_image_path=args.style_image_path,
content_seg_path=args.content_seg_path,
style_seg_path=args.style_seg_path,
output_image_path=args.output_image_path,
cuda=args.cuda,
)
folder = 'examples'
cont_img_folder = os.path.join(folder, 'content_img')
cont_seg_folder = os.path.join(folder, 'content_seg')
styl_img_folder = os.path.join(folder, 'style_img')
styl_seg_folder = os.path.join(folder, 'style_seg')
outp_img_folder = os.path.join(folder, 'results')
cont_img_list = [
f for f in os.listdir(cont_img_folder)
if os.path.isfile(os.path.join(cont_img_folder, f))
]
cont_img_list.sort()
# Load model
p_wct = PhotoWCT()
p_wct.load_state_dict(torch.load(args.model))
p_wct.cuda(0)
for f in cont_img_list:
print("Process " + f)
content_image_path = os.path.join(cont_img_folder, f)
content_seg_path = os.path.join(cont_seg_folder, f).replace(".png", ".pgm")
style_image_path = os.path.join(styl_img_folder, f)
style_seg_path = os.path.join(styl_seg_folder, f).replace(".png", ".pgm")
output_image_path = os.path.join(outp_img_folder, f)
process_stylization.stylization(
p_wct=p_wct,
content_image_path=content_image_path,
style_image_path=style_image_path,
content_seg_path=content_seg_path,
parser.add_argument('--fast', action='store_true', default=False)
parser.add_argument('--no_post', action='store_true', default=False)
parser.add_argument('--cuda', type=int, default=1, help='Enable CUDA.')
parser.add_argument('--device', type=int, default=0, help='CUDA device.')
args = parser.parse_args()
# Load model
p_wct = PhotoWCT(device=args.device)
p_wct.load_state_dict(torch.load(args.model))
if args.fast:
from photo_gif import GIFSmoothing
p_pro = GIFSmoothing(r=35, eps=0.001)
else:
from photo_smooth import Propagator
p_pro = Propagator()
if args.cuda:
p_wct.cuda(args.device)
process_stylization.stylization(stylization_module=p_wct,
smoothing_module=p_pro,
content_image_path=args.content_image_path,
style_image_path=args.style_image_path,
content_seg_path=args.content_seg_path,
style_seg_path=args.style_seg_path,
output_image_path=args.output_image_path,
cuda=args.cuda,
save_intermediate=args.save_intermediate,
no_post=args.no_post,
device=args.device)
parser.add_argument('--cuda', type=int, default=1, help='Enable CUDA.')
parser.add_argument('--mode', type=str, default="")
args = parser.parse_args()
# Load model
p_wct = PhotoWCT(args)
if args.mode == "original" or args.mode == "":
p_wct.load_state_dict(torch.load(args.model))
if args.fast:
from photo_gif import GIFSmoothing
p_pro = GIFSmoothing(r=35, eps=0.001)
else:
from photo_smooth import Propagator
p_pro = Propagator()
if args.cuda:
p_wct.cuda(args.cuda)
process_stylization.stylization(
stylization_module=p_wct,
smoothing_module=p_pro,
content_image_path=args.content_image_path,
style_image_path=args.style_image_path,
content_seg_path=args.content_seg_path,
style_seg_path=args.style_seg_path,
output_image_path=args.output_image_path,
cuda=args.cuda,
save_intermediate=args.save_intermediate,
no_post=args.no_post
)
parser.add_argument('--model', default='./PhotoWCTModels/photo_wct.pth',
help='Path to the PhotoWCT model. These are provided by the PhotoWCT submodule, please use `git submodule update --init --recursive` to pull.')
parser.add_argument('--content_image_path', default='./images/content1.png')
parser.add_argument('--content_seg_path', default=[])
parser.add_argument('--style_image_path', default='./images/style1.png')
parser.add_argument('--style_seg_path', default=[])
parser.add_argument('--output_image_path', default='./results/example1.png')
parser.add_argument('--cuda', type=int, default=1, help='Enable CUDA.')
args = parser.parse_args()
# Load model
p_wct = PhotoWCT()
try:
p_wct.load_state_dict(torch.load(args.model))
except:
print("Fail to load PhotoWCT models. PhotoWCT submodule not updated?")
exit()
if args.cuda:
p_wct.cuda(0)
process_stylization.stylization(
p_wct=p_wct,
content_image_path=args.content_image_path,
style_image_path=args.style_image_path,
content_seg_path=args.content_seg_path,
style_seg_path=args.style_seg_path,
output_image_path=args.output_image_path,
cuda=args.cuda,
)
