Update app.py

app.py

@@ -302,7 +302,7 @@ async def detect_multiple_dogs(image):
 
 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
 
     try:
         if isinstance(image, np.ndarray):
@@ -311,12 +311,15 @@ async def predict(image):
         dogs = await detect_multiple_dogs(image)
         
         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)
+            return "No dogs detected. Please upload a clear image of a dog.", None
 
         explanations = []
         annotated_image = image.copy()
         draw = ImageDraw.Draw(annotated_image)
-        font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", 20)
+        try:
+            font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", 20)
+        except IOError:
+            font = ImageFont.load_default()
 
         for i, (cropped_image, _, box) in enumerate(dogs, 1):
             top1_prob, topk_breeds, topk_probs_percent = await predict_single_dog(cropped_image)
@@ -324,7 +327,8 @@ async def predict(image):
             # 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)
+            label_bbox = font.getbbox(label)
+            label_size = (label_bbox[2] - label_bbox[0], label_bbox[3] - label_bbox[1])
             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)
 
@@ -355,10 +359,10 @@ async def predict(image):
                 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)
+        return final_explanation, annotated_image
 
     except Exception as e:
-        return f"An error occurred: {e}", None, gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+        return f"An error occurred: {e}", None
 
 # Gradio 界面設置
 with gr.Blocks(css="""