queue test

vtoonify_model.py

@@ -208,6 +208,7 @@ class Model():
         if self.style_name != style_type:
             exstyle, _  = self.load_model(style_type)
         if exstyle is None:
+            exstyle, _ = self.load_model(style_type)
             return np.zeros((256,256,3), np.uint8), 'Opps, something wrong with the style type. Please go to Step 1 and load model again.'
         with torch.no_grad():
             if self.color_transfer:
@@ -228,15 +229,16 @@ class Model():
     def video_tooniy(self, aligned_video: str, instyle: torch.Tensor, exstyle: torch.Tensor, style_degree: float, style_type: str) -> tuple[str, str]:
         #print(style_type + ' ' + self.style_name)
         if aligned_video is None:
-            return 'default.mp4', 'Opps, something wrong with the input. Please go to Step 2 and Rescale Video again.'         
+            return 'default.mp4', 'Opps, something wrong with the input. Please go to Step 2 and Rescale Video again. 1'
         video_cap = cv2.VideoCapture(aligned_video)
         if instyle is None or aligned_video is None or video_cap.get(7) == 0:
             video_cap.release()
-            return 'default.mp4', 'Opps, something wrong with the input. Please go to Step 2 and Rescale Video again.'
+            return 'default.mp4', 'Opps, something wrong with the input. Please go to Step 2 and Rescale Video again. 2'
         if self.style_name != style_type:
             exstyle, _  = self.load_model(style_type)
         if exstyle is None:
-            return 'default.mp4', 'Opps, something wrong with the style type. Please go to Step 1 and load model again.'
+            exstyle, _ = self.load_model(style_type)
+            return 'default.mp4', 'Opps, something wrong with the style type. Please go to Step 1 and load model again. 3'
         num = min(self.video_limit_gpu, int(video_cap.get(7)))
         if self.device == 'cpu':
             num = min(self.video_limit_cpu, num)