update cog predict

cog_predict.py

@@ -42,6 +42,13 @@ def setup(self):
         if not os.path.exists('gfpgan/weights/GFPGANv1.4.pth'):
             os.system(
                 'wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P ./gfpgan/weights')
+        if not os.path.exists('gfpgan/weights/RestoreFormer.pth'):
+            os.system(
+                'wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth -P ./gfpgan/weights'
+            )
+        if not os.path.exists('gfpgan/weights/CodeFormer.pth'):
+            os.system(
+                'wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/CodeFormer.pth -P ./gfpgan/weights')
 
         # background enhancer with RealESRGAN
         model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
@@ -64,11 +71,18 @@ def predict(
         img: Path = Input(description='Input'),
         version: str = Input(
             description='GFPGAN version. v1.3: better quality. v1.4: more details and better identity.',
-            choices=['v1.2', 'v1.3', 'v1.4'],
+            choices=['v1.2', 'v1.3', 'v1.4', 'RestoreFormer', 'CodeFormer'],
             default='v1.4'),
-        scale: float = Input(description='Rescaling factor', default=2)
+        scale: float = Input(description='Rescaling factor', default=2),
+        weight: float = Input(
+            description='Weight, only for CodeFormer. 0 for better quality, 1 for better identity',
+            default=0.5,
+            ge=0,
+            le=1.0)
     ) -> Path:
-        print(img, version, scale)
+        if not isinstance(weight, (int, float)):
+            weight = 0.5
+        print(img, version, scale, weight)
         try:
             extension = os.path.splitext(os.path.basename(str(img)))[1]
             img = cv2.imread(str(img), cv2.IMREAD_UNCHANGED)
@@ -109,14 +123,26 @@ def predict(
                         channel_multiplier=2,
                         bg_upsampler=self.upsampler)
                     self.current_version = 'v1.4'
+                elif version == 'RestoreFormer':
+                    self.face_enhancer = GFPGANer(
+                        model_path='gfpgan/weights/RestoreFormer.pth',
+                        upscale=2,
+                        arch='RestoreFormer',
+                        channel_multiplier=2,
+                        bg_upsampler=self.upsampler)
+                elif version == 'CodeFormer':
+                    self.face_enhancer = GFPGANer(
+                        model_path='gfpgan/weights/CodeFormer.pth',
+                        upscale=2,
+                        arch='CodeFormer',
+                        channel_multiplier=2,
+                        bg_upsampler=self.upsampler)
 
             try:
                 _, _, output = self.face_enhancer.enhance(
-                    img, has_aligned=False, only_center_face=False, paste_back=True)
+                    img, has_aligned=False, only_center_face=False, paste_back=True, weight=weight)
             except RuntimeError as error:
                 print('Error', error)
-            else:
-                extension = 'png'
 
             try:
                 if scale != 2: