Update app.py

app.py

@@ -249,10 +249,9 @@ def get_akc_breeds_link():
 # if __name__ == "__main__":
 #     iface.launch()
 
-
-
 def format_description(description, breed):
     if isinstance(description, dict):
+        # 確保每一個描述項目換行顯示
         formatted_description = "\n\n".join([f"**{key}**: {value}" for key, value in description.items()])
     else:
         formatted_description = description
@@ -268,39 +267,6 @@ def format_description(description, breed):
 
     return formatted_description
 
-
-async def predict_single_dog(image):
-    return await asyncio.to_thread(_predict_single_dog, image)
-
-def _predict_single_dog(image):
-    image_tensor = preprocess_image(image)
-    with torch.no_grad():
-        output = model(image_tensor)
-        logits = output[0] if isinstance(output, tuple) else output
-        probabilities = F.softmax(logits, dim=1)
-        topk_probs, topk_indices = torch.topk(probabilities, k=3)
-        top1_prob = topk_probs[0][0].item()
-        topk_breeds = [dog_breeds[idx.item()] for idx in topk_indices[0]]
-        topk_probs_percent = [f"{prob.item() * 100:.2f}%" for prob in topk_probs[0]]
-    return top1_prob, topk_breeds, topk_probs_percent
-
-async def detect_multiple_dogs(image, conf_threshold=0.3):
-    # 調整 YOLO 模型的置信度閾值
-    return await asyncio.to_thread(_detect_multiple_dogs, image, conf_threshold)
-
-def _detect_multiple_dogs(image, conf_threshold):
-    results = model_yolo(image, conf=conf_threshold)
-    dogs = []
-    for result in results:
-        for box in result.boxes:
-            if box.cls == 16:  # COCO 資料集中狗的類別是 16
-                xyxy = box.xyxy[0].tolist()
-                confidence = box.conf.item()
-                if confidence >= conf_threshold:  # 只保留置信度高於閾值的框
-                    cropped_image = image.crop((xyxy[0], xyxy[1], xyxy[2], xyxy[3]))
-                    dogs.append((cropped_image, confidence, xyxy))
-    return dogs
-
 async def predict(image):
     if image is None:
         return "Please upload an image to start.", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
@@ -333,7 +299,7 @@ async def predict(image):
                     f"3. **{topk_breeds[2]}** ({topk_probs_percent[2]} confidence)\n\n"
                     "Click on a button to view more information about the breed."
                 )
-                return explanation, gr.update(visible=True, value=f"More about {topk_breeds[0]}"), gr.update(visible=True, value=f"More about {topk_breeds[1]}"), gr.update(visible=True, value=f"More about {topk_breeds[2]}")
+                return explanation, image, gr.update(visible=True, value=f"More about {topk_breeds[0]}"), gr.update(visible=True, value=f"More about {topk_breeds[1]}"), gr.update(visible=True, value=f"More about {topk_breeds[2]}")
 
         # 多狗處理
         color_list = ['#FF0000', '#00FF00', '#0000FF', '#FFFF00', '#00FFFF', '#FF00FF', '#800080', '#FFA500']
@@ -365,13 +331,15 @@ 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 Dog {i+1}: {topk_breeds[0]}", f"More about Dog {i+1}: {topk_breeds[1]}", f"More about Dog {i+1}: {topk_breeds[2]}"])
+                visible_buttons.append(gr.update(visible=True, value=f"More about Dog {i+1}: {topk_breeds[0]}"))
+                visible_buttons.append(gr.update(visible=True, value=f"More about Dog {i+1}: {topk_breeds[1]}"))
+                visible_buttons.append(gr.update(visible=True, value=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.")
 
         final_explanation = "\n\n".join(explanations)
 
-        return final_explanation, annotated_image, gr.update(visible=True, choices=visible_buttons), gr.update(visible=False), gr.update(visible=False)
+        return final_explanation, annotated_image, visible_buttons
 
     except Exception as e:
         return f"An error occurred: {e}", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
@@ -391,6 +359,7 @@ async def show_details(choice):
         return f"An error occurred while showing details: {e}"
 
 
+
 with gr.Blocks(css="""
     .container { max-width: 900px; margin: auto; padding: 20px; }
     .gr-box { border-radius: 15px; }