Update app.py

app.py

@@ -415,14 +415,14 @@ def _detect_multiple_dogs(image, conf_threshold):
 
 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)
+        return "Please upload an image to start.", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
     try:
         if isinstance(image, np.ndarray):
             image = Image.fromarray(image)
 
-        # 嘗試檢測多隻狗，降低閾值以提高檢測率
-        dogs = await detect_multiple_dogs(image, conf_threshold=0.2)
+        # 嘗試檢測多隻狗，進一步降低閾值以提高檢測率
+        dogs = await detect_multiple_dogs(image, conf_threshold=0.1)
         if len(dogs) == 0:
             # 單狗情境
             return await process_single_dog(image)
@@ -460,24 +460,25 @@ async def predict(image):
             return (final_explanation, annotated_image, 
                     buttons[0] if len(buttons) > 0 else gr.update(visible=False),
                     buttons[1] if len(buttons) > 1 else gr.update(visible=False),
-                    buttons[2] if len(buttons) > 2 else gr.update(visible=False))
+                    buttons[2] if len(buttons) > 2 else gr.update(visible=False),
+                    gr.update(visible=False))
         else:
-            return final_explanation, annotated_image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+            return final_explanation, annotated_image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
     except Exception as e:
-        return f"An error occurred: {str(e)}", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+        return f"An error occurred: {str(e)}", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
 
 async def process_single_dog(image):
     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)
+        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), gr.update(visible=False)
 
     breed = topk_breeds[0]
     description = get_dog_description(breed)
 
     if top1_prob >= 0.5:
         formatted_description = format_description(description, breed)
-        return formatted_description, image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+        return formatted_description, image, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
     else:
         explanation = (
             f"The model couldn't confidently identify the breed. Here are the top 3 possible breeds:\n\n"
@@ -489,19 +490,19 @@ async def process_single_dog(image):
         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]}"))
+                gr.update(visible=True, value=f"More about {topk_breeds[2]}"),
+                gr.update(visible=True))
 
-
-def show_details(choice):
+def show_details(choice, previous_output):
     if not choice:
-        return "Please select a breed to view details."
+        return previous_output, gr.update(visible=False)
 
     try:
         breed = choice.split("More about ")[-1]
         description = get_dog_description(breed)
-        return format_description(description, breed)
+        return format_description(description, breed), gr.update(visible=True)
     except Exception as e:
-        return f"An error occurred while showing details: {e}"
+        return f"An error occurred while showing details: {e}", gr.update(visible=True)
 
 # 介面部分
 with gr.Blocks() as iface:
@@ -518,16 +519,26 @@ with gr.Blocks() as iface:
         btn1 = gr.Button("View More 1", visible=False)
         btn2 = gr.Button("View More 2", visible=False)
         btn3 = gr.Button("View More 3", visible=False)
-
+    
+    back_button = gr.Button("Back", visible=False)
+    
     input_image.change(
         predict,
         inputs=input_image,
-        outputs=[output, output_image, btn1, btn2, btn3]
+        outputs=[output, output_image, btn1, btn2, btn3, back_button]
     )
 
-    btn1.click(show_details, inputs=btn1, outputs=output)
-    btn2.click(show_details, inputs=btn2, outputs=output)
-    btn3.click(show_details, inputs=btn3, outputs=output)
+    for btn in [btn1, btn2, btn3]:
+        btn.click(
+            show_details,
+            inputs=[btn, output],
+            outputs=[output, back_button]
+        )
+
+    back_button.click(
+        lambda: (gr.update(value=""), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True), gr.update(visible=False)),
+        outputs=[output, btn1, btn2, btn3, back_button]
+    )
 
     gr.Examples(
         examples=['Border_Collie.jpg', 'Golden_Retriever.jpeg', 'Saint_Bernard.jpeg', 'French_Bulldog.jpeg', 'Samoyed.jpg'],