Update app.py

app.py

@@ -308,73 +308,59 @@ async def predict(image):
         if isinstance(image, np.ndarray):
             image = Image.fromarray(image)
 
-        # 快速檢查是否有多個狗
         dogs = await detect_multiple_dogs(image)
         
-        if len(dogs) <= 1:  # 單狗或無狗情況
-            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)
-            
-            if top1_prob >= 0.5:
-                return formatted_description, image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
-            elif 0.2 <= top1_prob < 0.5:
-                explanation = f"""
-**Detected with moderate confidence. Here are the top 3 possible breeds:**
-
-1. **{topk_breeds[0]}** ({topk_probs_percent[0]})
-2. **{topk_breeds[1]}** ({topk_probs_percent[1]})
-3. **{topk_breeds[2]}** ({topk_probs_percent[2]})
+        if len(dogs) == 0:
+            return "No dogs detected. Please upload a clear image of a dog.", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
-Click on a button below to view more information about each breed.
-"""
-                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]}")
-            else:
-                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)
-        
-        # 多狗情況
         explanations = []
-        visible_buttons = []
         annotated_image = image.copy()
         draw = ImageDraw.Draw(annotated_image)
-        font = ImageFont.load_default()
+        font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", 20)
 
         for i, (cropped_image, _, box) in enumerate(dogs, 1):
             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}", fill="red", font=font)
+            # 繪製更醒目的邊框和標籤
+            draw.rectangle(box, outline="red", width=5)
+            label = f"Dog {i}"
+            label_size = draw.textsize(label, font=font)
+            draw.rectangle([box[0], box[1], box[0] + label_size[0], box[1] + label_size[1]], fill="red")
+            draw.text((box[0], box[1]), label, fill="white", font=font)
 
             if top1_prob >= 0.5:
                 breed = topk_breeds[0]
                 description = get_dog_description(breed)
-                explanations.append(format_description(description, breed, is_multi_dog=True, dog_number=i))
-            elif 0.2 <= top1_prob < 0.5:
+                explanation = f"**Dog {i}: {breed}**\n\n{format_description(description, breed)}"
+            else:
                 explanation = f"""
 **Dog {i}: Detected with moderate confidence. Here are the top 3 possible breeds:**
 
 1. **{topk_breeds[0]}** ({topk_probs_percent[0]})
 2. **{topk_breeds[1]}** ({topk_probs_percent[1]})
 3. **{topk_breeds[2]}** ({topk_probs_percent[2]})
+
+[More about {topk_breeds[0]}](#breed_{i}_1)
+[More about {topk_breeds[1]}](#breed_{i}_2)
+[More about {topk_breeds[2]}](#breed_{i}_3)
 """
-                explanations.append(explanation)
-                visible_buttons.extend([f"More about Dog {i}: {topk_breeds[0]}", f"More about Dog {i}: {topk_breeds[1]}", f"More about Dog {i}: {topk_breeds[2]}"])
-            else:
-                explanations.append(f"**Dog {i}**: 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=len(visible_buttons) >= 1, value=visible_buttons[0] if visible_buttons else ""), gr.update(visible=True, value=visible_buttons[1] if len(visible_buttons) >= 2 else ""), gr.update(visible=True, value=visible_buttons[2] if len(visible_buttons) >= 3 else "")
+            explanations.append(explanation)
+
+        final_explanation = "\n\n---\n\n".join(explanations)
+        
+        # 添加隱藏的詳細信息部分
+        for i, (_, _, _) in enumerate(dogs, 1):
+            for j, breed in enumerate(topk_breeds, 1):
+                description = get_dog_description(breed)
+                final_explanation += f"\n\n<div id='breed_{i}_{j}' style='display:none;'>\n\n{format_description(description, breed)}\n\n</div>"
+
+        return final_explanation, annotated_image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
     except Exception as e:
         return f"An error occurred: {e}", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
-def show_details(breed):
-    breed_name = breed.split("More about ")[-1].split(": ")[-1]  # Handle both single and multi-dog cases
-    description = get_dog_description(breed_name)
-    return format_description(description, breed_name)
-
-# Gradio interface setup
+# Gradio 界面設置
 with gr.Blocks(css="""
     .container { max-width: 900px; margin: auto; padding: 20px; }
     .gr-box { border-radius: 15px; }
@@ -391,17 +377,8 @@ with gr.Blocks(css="""
         output_image = gr.Image(label="Annotated Image")
     
     output = gr.Markdown(label="Prediction Results")
-    
-    with gr.Row():
-        btn1 = gr.Button("View More 1", visible=False)
-        btn2 = gr.Button("View More 2", visible=False)
-        btn3 = gr.Button("View More 3", visible=False)
 
-    input_image.change(predict, inputs=input_image, outputs=[output, output_image, btn1, btn2, btn3])
-    
-    btn1.click(show_details, inputs=btn1, outputs=output)
-    btn2.click(show_details, inputs=btn2, outputs=output)
-    btn3.click(show_details, inputs=btn3, outputs=output)
+    input_image.change(predict, inputs=input_image, outputs=[output, output_image])
 
     gr.Examples(
         examples=['Border_Collie.jpg', 'Golden_Retriever.jpeg', 'Saint_Bernard.jpeg', 'French_Bulldog.jpeg', 'Samoyed.jpg'],