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