Update app.py

app.py

@@ -286,7 +286,11 @@ async def predict_single_dog(image):
 # 偵測多隻狗的函數
 async def detect_multiple_dogs(image):
     try:
-        results = model_yolo(image)
+        # 調整圖像大小以加快處理速度
+        img = image.copy()
+        img.thumbnail((640, 640))
+        
+        results = model_yolo(img, conf=0.3)  # 降低置信度閾值以檢測更多狗
         dogs = []
         for result in results:
             for box in result.boxes:
@@ -308,18 +312,16 @@ async def predict(image):
         if isinstance(image, np.ndarray):
             image = Image.fromarray(image)
 
-        # Always use YOLO to detect dogs
+        # 使用 YOLO 檢測狗
         dogs = await detect_multiple_dogs(image)
 
         if len(dogs) == 0:
             return "No dogs detected in the image. Please upload a clear image of a dog.", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
         elif len(dogs) == 1:
-            # Single dog detected
-            cropped_image, _, _ = dogs[0]
+            cropped_image, _, box = dogs[0]
             top1_prob, topk_breeds, topk_probs_percent = await predict_single_dog(cropped_image)
-            return await process_single_dog_result(top1_prob, topk_breeds, topk_probs_percent, image, dogs[0][2])
+            return await process_single_dog_result(top1_prob, topk_breeds, topk_probs_percent, image, box)
         else:
-            # Multiple dogs detected
             return await process_multiple_dogs_result(dogs, image)
 
     except Exception as e: