Update app.py

app.py

@@ -125,7 +125,7 @@ num_classes = 120
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 model = BaseModel(num_classes=num_classes, device=device)
 
-checkpoint = torch.load('/content/drive/Othercomputers/我的 MacBook Pro/Learning/Cats_Dogs_Detector/(120)best_model/best_model_81_dog.pth', map_location=torch.device('cpu'))
+checkpoint = torch.load('best_model_81_dog.pth', map_location=torch.device('cpu'))
 model.load_state_dict(checkpoint['model_state_dict'])
 
 # evaluation mode
@@ -441,11 +441,11 @@ def main():
         with gr.Tabs():
             # 1. 品種檢測標籤頁
             example_images = [
-                '/content/drive/Othercomputers/我的 MacBook Pro/Learning/Cats_Dogs_Detector/test_images/Border_Collie.jpg',
-                '/content/drive/Othercomputers/我的 MacBook Pro/Learning/Cats_Dogs_Detector/test_images/Golden_Retriever.jpeg',
-                '/content/drive/Othercomputers/我的 MacBook Pro/Learning/Cats_Dogs_Detector/test_images/Saint_Bernard.jpeg',
-                '/content/drive/Othercomputers/我的 MacBook Pro/Learning/Cats_Dogs_Detector/test_images/Samoyed.jpg',
-                '/content/drive/Othercomputers/我的 MacBook Pro/Learning/Cats_Dogs_Detector/test_images/French_Bulldog.jpeg'
+                'Border_Collie.jpg',
+                'Golden_Retriever.jpeg',
+                'Saint_Bernard.jpeg',
+                'Samoyed.jpg',
+                'French_Bulldog.jpeg'
             ]
             detection_components = create_detection_tab(predict, example_images)