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update cog predict
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commit
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@ -42,6 +42,13 @@ class Predictor(BasePredictor):
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if not os.path.exists('gfpgan/weights/GFPGANv1.4.pth'):
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if not os.path.exists('gfpgan/weights/GFPGANv1.4.pth'):
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os.system(
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os.system(
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'wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P ./gfpgan/weights')
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'wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P ./gfpgan/weights')
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if not os.path.exists('gfpgan/weights/RestoreFormer.pth'):
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os.system(
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'wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth -P ./gfpgan/weights'
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)
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if not os.path.exists('gfpgan/weights/CodeFormer.pth'):
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os.system(
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'wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/CodeFormer.pth -P ./gfpgan/weights')
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# background enhancer with RealESRGAN
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# background enhancer with RealESRGAN
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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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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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@ -64,11 +71,18 @@ class Predictor(BasePredictor):
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img: Path = Input(description='Input'),
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img: Path = Input(description='Input'),
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version: str = Input(
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version: str = Input(
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description='GFPGAN version. v1.3: better quality. v1.4: more details and better identity.',
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description='GFPGAN version. v1.3: better quality. v1.4: more details and better identity.',
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choices=['v1.2', 'v1.3', 'v1.4'],
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choices=['v1.2', 'v1.3', 'v1.4', 'RestoreFormer', 'CodeFormer'],
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default='v1.4'),
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default='v1.4'),
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scale: float = Input(description='Rescaling factor', default=2)
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scale: float = Input(description='Rescaling factor', default=2),
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weight: float = Input(
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description='Weight, only for CodeFormer. 0 for better quality, 1 for better identity',
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default=0.5,
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ge=0,
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le=1.0)
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) -> Path:
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) -> Path:
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print(img, version, scale)
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if not isinstance(weight, (int, float)):
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weight = 0.5
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print(img, version, scale, weight)
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try:
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try:
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extension = os.path.splitext(os.path.basename(str(img)))[1]
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extension = os.path.splitext(os.path.basename(str(img)))[1]
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img = cv2.imread(str(img), cv2.IMREAD_UNCHANGED)
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img = cv2.imread(str(img), cv2.IMREAD_UNCHANGED)
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@ -109,14 +123,26 @@ class Predictor(BasePredictor):
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channel_multiplier=2,
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channel_multiplier=2,
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bg_upsampler=self.upsampler)
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bg_upsampler=self.upsampler)
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self.current_version = 'v1.4'
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self.current_version = 'v1.4'
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elif version == 'RestoreFormer':
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self.face_enhancer = GFPGANer(
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model_path='gfpgan/weights/RestoreFormer.pth',
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upscale=2,
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arch='RestoreFormer',
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channel_multiplier=2,
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bg_upsampler=self.upsampler)
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elif version == 'CodeFormer':
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self.face_enhancer = GFPGANer(
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model_path='gfpgan/weights/CodeFormer.pth',
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upscale=2,
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arch='CodeFormer',
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channel_multiplier=2,
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bg_upsampler=self.upsampler)
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try:
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try:
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_, _, output = self.face_enhancer.enhance(
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_, _, output = self.face_enhancer.enhance(
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img, has_aligned=False, only_center_face=False, paste_back=True)
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img, has_aligned=False, only_center_face=False, paste_back=True, weight=weight)
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except RuntimeError as error:
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except RuntimeError as error:
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print('Error', error)
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print('Error', error)
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else:
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extension = 'png'
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try:
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try:
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if scale != 2:
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if scale != 2:
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