Update app.py

app.py

@@ -251,6 +251,7 @@ def get_akc_breeds_link():
 
 
 def format_description(description, breed):
+    # 分別將不同的屬性分開來顯示，保持結果的可讀性
     if isinstance(description, dict):
         formatted_description = "\n".join([f"**{key}**: {value}" for key, value in description.items()])
     else:
@@ -258,9 +259,12 @@ def format_description(description, breed):
 
     formatted_description = f"""
 **Breed**: {breed}
+
 {formatted_description}
+
 **Want to learn more about dog breeds?**  
 [Visit the AKC dog breeds page]({get_akc_breeds_link()}) and search for {breed} to find detailed information.
+
 *Disclaimer: The external link provided leads to the American Kennel Club (AKC) dog breeds page. 
 You may need to search for the specific breed on that page. 
 I am not responsible for the content on external sites. 
@@ -270,7 +274,7 @@ Please refer to the AKC's terms of use and privacy policy.*
 
 
 async def predict_single_dog(image):
-    # 直接使用模型進行預測，無需通過 YOLO
+    # 單一品種直接預測，避免 YOLO
     return await asyncio.to_thread(_predict_single_dog, image)
 
 def _predict_single_dog(image):
@@ -286,6 +290,7 @@ def _predict_single_dog(image):
     return top1_prob, topk_breeds, topk_probs_percent
 
 async def detect_multiple_dogs(image):
+    # 檢測多隻狗時使用 YOLO
     return await asyncio.to_thread(_detect_multiple_dogs, image)
 
 def _detect_multiple_dogs(image):
@@ -308,9 +313,11 @@ async def predict(image):
         if isinstance(image, np.ndarray):
             image = Image.fromarray(image)
 
+        # 首先檢查圖片中是否有多隻狗
         dogs = await detect_multiple_dogs(image)
 
         if len(dogs) == 0:
+            # 單狗直接分類
             top1_prob, topk_breeds, topk_probs_percent = await predict_single_dog(image)
             if top1_prob < 0.2:
                 return "The image is unclear or the breed is not in the dataset. Please upload a clearer image of a dog.", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
@@ -319,23 +326,19 @@ async def predict(image):
             formatted_description = format_description(description, breed)
             return formatted_description, image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
-        if len(dogs) == 1:
-            top1_prob, topk_breeds, topk_probs_percent = await predict_single_dog(image)
-            breed = topk_breeds[0]
-            description = get_dog_description(breed)
-            formatted_description = format_description(description, breed)
-            return formatted_description, image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
-
         explanations = []
         visible_buttons = []
         annotated_image = image.copy()
         draw = ImageDraw.Draw(annotated_image)
 
+        # 多狗情況
         for i, (cropped_image, _, box) in enumerate(dogs):
             top1_prob, topk_breeds, topk_probs_percent = await predict_single_dog(cropped_image)
 
-            draw.rectangle(box, outline="red", width=3)
-            draw.text((box[0], box[1]), f"Dog {i+1}", fill="red")
+            # 更改框的顏色以增加辨識度
+            color = ["red", "blue", "green", "yellow"][i % 4]
+            draw.rectangle(box, outline=color, width=3)
+            draw.text((box[0], box[1]), f"Dog {i+1}", fill=color)
 
             if top1_prob >= 0.5:
                 breed = topk_breeds[0]
@@ -349,7 +352,8 @@ Dog {i+1}: Detected with moderate confidence. Here are the top 3 possible breeds
 3. **{topk_breeds[2]}** ({topk_probs_percent[2]})
 """
                 explanations.append(explanation)
-                visible_buttons.extend([f"More about {topk_breeds[0]}", f"More about {topk_breeds[1]}", f"More about {topk_breeds[2]}"])
+                # 將 Top3 選項顯示在該狗的下方
+                visible_buttons.extend([f"More about Dog {i+1}: {topk_breeds[0]}", f"More about Dog {i+1}: {topk_breeds[1]}", f"More about Dog {i+1}: {topk_breeds[2]}"])
             else:
                 explanations.append(f"Dog {i+1}: The image is unclear or the breed is not in the dataset.")