Update api_server.py

api_server.py

@@ -117,6 +117,8 @@ def predict():
         labels = result.boxes.cls  # Get predicted label IDs
         label_names = [model.names[int(label)] for label in labels]  # Convert to names
 
+        print(f"======YOLO result: {label_names}======")
+
         element_counts = Counter(label_names)
 
         encoded_images=[]
@@ -135,7 +137,7 @@ def predict():
             for yolo_img in yolo_file: # 每張切圖yolo_img
                 top_k_words.append(clip_model.clip_result(yolo_img)) # CLIP預測3個結果(top_k_words)
                 encoded_images.append(image_to_base64(yolo_img))
-                print(top_k_words)
+                print(f"**{yolo_img}:{top_k_words}**\n")
 
             # if element_counts[element] > 1: #某隻角色的數量>1
             #     yolo_path = f"{YOLO_DIR}/{message_id}/{element}"