Skip to content

Commit

Permalink
support denoise strength for realesr-general-x4v3
Browse files Browse the repository at this point in the history
  • Loading branch information
@xinntao
xinntao committed Sep 18, 2022
1 parent b827be1 commit 576aadd
Show file tree
Hide file tree
Showing 2 changed files with 70 additions and 16 deletions.
53 changes: 42 additions & 11 deletions inference_realesrgan.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
import glob
import os
from basicsr.archs.rrdbnet_arch import RRDBNet
from basicsr.utils.download_util import load_file_from_url

from realesrgan import RealESRGANer
from realesrgan.archs.srvgg_arch import SRVGGNetCompact
Expand All @@ -19,10 +20,18 @@ def main():
type=str,
default='RealESRGAN_x4plus',
help=('Model names: RealESRGAN_x4plus | RealESRNet_x4plus | RealESRGAN_x4plus_anime_6B | RealESRGAN_x2plus | '
'realesr-animevideov3 | realesr-general-x4v3 | realesr-general-wdn-x4v3'))
'realesr-animevideov3 | realesr-general-x4v3'))
parser.add_argument('-o', '--output', type=str, default='results', help='Output folder')
parser.add_argument('--model_path', type=str, default=None, help='Model path')
parser.add_argument(
'-dn',
'--denoise_strength',
type=float,
default=0.5,
help=('Denoise strength. 0 for weak denoise (keep noise), 1 for strong denoise ability. '
'Only used for the realesr-general-x4v3 model'))
parser.add_argument('-s', '--outscale', type=float, default=4, help='The final upsampling scale of the image')
parser.add_argument(
'--model_path', type=str, default=None, help='[Option] Model path. Usually, you do not need to specify it')
parser.add_argument('--suffix', type=str, default='out', help='Suffix of the restored image')
parser.add_argument('-t', '--tile', type=int, default=0, help='Tile size, 0 for no tile during testing')
parser.add_argument('--tile_pad', type=int, default=10, help='Tile padding')
Expand All @@ -47,36 +56,58 @@ def main():

# determine models according to model names
args.model_name = args.model_name.split('.')[0]
if args.model_name in ['RealESRGAN_x4plus', 'RealESRNet_x4plus']: # x4 RRDBNet model
if args.model_name == 'RealESRGAN_x4plus': # x4 RRDBNet model
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
netscale = 4
file_url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth'
elif args.model_name == 'RealESRNet_x4plus': # x4 RRDBNet model
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
netscale = 4
elif args.model_name in ['RealESRGAN_x4plus_anime_6B']: # x4 RRDBNet model with 6 blocks
file_url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth'
elif args.model_name == 'RealESRGAN_x4plus_anime_6B': # x4 RRDBNet model with 6 blocks
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
netscale = 4
elif args.model_name in ['RealESRGAN_x2plus']: # x2 RRDBNet model
file_url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth'
elif args.model_name == 'RealESRGAN_x2plus': # x2 RRDBNet model
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
netscale = 2
elif args.model_name in ['realesr-animevideov3']: # x4 VGG-style model (XS size)
file_url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth'
elif args.model_name == 'realesr-animevideov3': # x4 VGG-style model (XS size)
model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu')
netscale = 4
elif args.model_name in ['realesr-general-x4v3', 'realesr-general-wdn-x4v3']: # x4 VGG-style model (S size)
file_url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth'
elif args.model_name == 'realesr-general-x4v3': # x4 VGG-style model (S size)
model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
netscale = 4
file_url = [
'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth',
'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth'
]

# determine model paths
if args.model_path is not None:
model_path = args.model_path
else:
model_path = os.path.join('experiments/pretrained_models', args.model_name + '.pth')
if not os.path.isfile(model_path):
model_path = os.path.join('realesrgan/weights', args.model_name + '.pth')
model_path = os.path.join('realesrgan/weights', args.model_name + '.pth')
if not os.path.isfile(model_path):
raise ValueError(f'Model {args.model_name} does not exist.')
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
for url in file_url:
# model_path will be updated
model_path = load_file_from_url(
url=url, model_dir=os.path.join(ROOT_DIR, 'realesrgan/weights'), progress=True, file_name=None)

# use dni to control the denoise strength
dni_weight = None
if args.model_name == 'realesr-general-x4v3' and args.denoise_strength != 1:
wdn_model_path = model_path.replace('realesr-general-x4v3', 'realesr-general-wdn-x4v3')
model_path = [model_path, wdn_model_path]
dni_weight = [args.denoise_strength, 1 - args.denoise_strength]

# restorer
upsampler = RealESRGANer(
scale=netscale,
model_path=model_path,
dni_weight=dni_weight,
model=model,
tile=args.tile,
tile_pad=args.tile_pad,
Expand Down
33 changes: 28 additions & 5 deletions realesrgan/utils.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@ class RealESRGANer():
def __init__(self,
scale,
model_path,
dni_weight=None,
model=None,
tile=0,
tile_pad=10,
Expand All @@ -49,22 +50,44 @@ def __init__(self,
f'cuda:{gpu_id}' if torch.cuda.is_available() else 'cpu') if device is None else device
else:
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') if device is None else device
# if the model_path starts with https, it will first download models to the folder: realesrgan/weights
if model_path.startswith('https://'):
model_path = load_file_from_url(
url=model_path, model_dir=os.path.join(ROOT_DIR, 'realesrgan/weights'), progress=True, file_name=None)
loadnet = torch.load(model_path, map_location=torch.device('cpu'))

if isinstance(model_path, list):
# dni
assert len(model_path) == len(dni_weight), 'model_path and dni_weight should have the save length.'
loadnet = self.dni(model_path[0], model_path[1], dni_weight)
else:
# if the model_path starts with https, it will first download models to the folder: realesrgan/weights
if model_path.startswith('https://'):
model_path = load_file_from_url(
url=model_path,
model_dir=os.path.join(ROOT_DIR, 'realesrgan/weights'),
progress=True,
file_name=None)
loadnet = torch.load(model_path, map_location=torch.device('cpu'))

# prefer to use params_ema
if 'params_ema' in loadnet:
keyname = 'params_ema'
else:
keyname = 'params'
model.load_state_dict(loadnet[keyname], strict=True)

model.eval()
self.model = model.to(self.device)
if self.half:
self.model = self.model.half()

def dni(self, net_a, net_b, dni_weight, key='params', loc='cpu'):
"""Deep network interpolation.
``Paper: Deep Network Interpolation for Continuous Imagery Effect Transition``
"""
net_a = torch.load(net_a, map_location=torch.device(loc))
net_b = torch.load(net_b, map_location=torch.device(loc))
for k, v_a in net_a[key].items():
net_a[key][k] = dni_weight[0] * v_a + dni_weight[1] * net_b[key][k]
return net_a

def pre_process(self, img):
"""Pre-process, such as pre-pad and mod pad, so that the images can be divisible
"""
Expand Down

0 comments on commit 576aadd

Please sign in to comment.