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add realesr-general-x4v3 and realesr-general-wdn-x4v3

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Xintao
2022-09-19 00:15:32 +08:00
parent e5e79fbde3
commit b827be13a1
1 changed files with 13 additions and 6 deletions
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19
inference_realesrgan.py
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@@ -19,8 +19,9 @@ def main():
type=str, type=str,
default='RealESRGAN_x4plus', default='RealESRGAN_x4plus',
help=('Model names: RealESRGAN_x4plus | RealESRNet_x4plus | RealESRGAN_x4plus_anime_6B | RealESRGAN_x2plus | ' help=('Model names: RealESRGAN_x4plus | RealESRNet_x4plus | RealESRGAN_x4plus_anime_6B | RealESRGAN_x2plus | '
'realesr-animevideov3')) 'realesr-animevideov3 | realesr-general-x4v3 | realesr-general-wdn-x4v3'))
parser.add_argument('-o', '--output', type=str, default='results', help='Output folder') 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('-s', '--outscale', type=float, default=4, help='The final upsampling scale of the image') parser.add_argument('-s', '--outscale', type=float, default=4, help='The final upsampling scale of the image')
parser.add_argument('--suffix', type=str, default='out', help='Suffix of the restored image') 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('-t', '--tile', type=int, default=0, help='Tile size, 0 for no tile during testing')
@@ -58,13 +59,19 @@ def main():
elif args.model_name in ['realesr-animevideov3']: # x4 VGG-style model (XS size) elif args.model_name in ['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') model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu')
netscale = 4 netscale = 4
elif args.model_name in ['realesr-general-x4v3', 'realesr-general-wdn-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
# determine model paths # determine model paths
model_path = os.path.join('experiments/pretrained_models', args.model_name + '.pth') if args.model_path is not None:
if not os.path.isfile(model_path): model_path = args.model_path
model_path = os.path.join('realesrgan/weights', args.model_name + '.pth') else:
if not os.path.isfile(model_path): model_path = os.path.join('experiments/pretrained_models', args.model_name + '.pth')
raise ValueError(f'Model {args.model_name} does not exist.') if not os.path.isfile(model_path):
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.')
# restorer # restorer
upsampler = RealESRGANer( upsampler = RealESRGANer(