diff --git a/app/controller/AlgorithmController.py b/app/controller/AlgorithmController.py
index 25897d7..7e54e85 100644
--- a/app/controller/AlgorithmController.py
+++ b/app/controller/AlgorithmController.py
@@ -102,8 +102,8 @@ def start_download_pt():
         @bp.route('/start_download_pt', methods=['get'])
         def wrapped_function_start_download_pt():
             param = request.args.get('param')
-            func(param)
-            return output_wrapped(0, 'success', '成功')
+            data = func(param)
+            return output_wrapped(0, 'success', data)
 
         return wrapped_function_start_download_pt
 
@@ -309,9 +309,6 @@ def Export_model_RODY(params_str):
         zipf.write(file, arcname=Path(file).name)  # 将torchscript和onnx模型压缩
 
     return exp_outputPath
-    zipf.write(modellist[1], arcname=modellist[1])
-    zip_inputpath = os.path.join(exp_outputPath, "inference_model")
-    zip_outputPath = os.path.join(exp_outputPath, "inference_model.zip")
 
 
 @obtain_train_param()
@@ -397,7 +394,7 @@ def returnDownloadParams():
     params_list = [
         {"index": 0, "name": "exp_inputPath", "value": 'E:/alg_demo-master/alg_demo/app/yolov5/圆孔_123_RODY_1_640.pt',
          "description": '转化模型输入路径',
-         "default": '/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/new磁环检测test_183504733393264640_R-DDM_11.pt/',
+         "default": 'E:/alg_demo-master/alg_demo/app/yolov5/圆孔_123_RODY_1_640.pt/',
          "type": "S", 'show': False},
         {"index": 1, "name": "device", "value": 'gpu', "description": 'CPU或GPU', "default": 'gpu', "type": "S",
          'show': False}
diff --git a/app/yolov5/detect_server.py b/app/yolov5/detect_server.py
index 16b03ec..3d14e40 100644
--- a/app/yolov5/detect_server.py
+++ b/app/yolov5/detect_server.py
@@ -224,10 +224,10 @@ def run(id,
 
                 # 原始图像路径/结果图像路径 传参
                 #online_img_tools.get_res_img(res_path=save_path, img_path=path, proj_no=pro)
-                print('数量：',count)
-                print('总量：',len(os.listdir(source)))
-                print('path：',path)
-                print('path：', str(save_path))
+                # print('数量：',count)
+                # print('总量：',len(os.listdir(source)))
+                # print('path：',path)
+                # print('path：', str(save_path))
                 report_cellback(count,len(os.listdir(source)),path,str(save_path))
         # Print time (inference-only)
         LOGGER.info(f"{s}{'' if len(det) else '(no detections), '}{dt[1].dt * 1E3:.1f}ms")