diff --git a/20240529RGBtest3/classifer.py b/20240529RGBtest3/classifer.py
index 10e5cab..4c83495 100644
--- a/20240529RGBtest3/classifer.py
+++ b/20240529RGBtest3/classifer.py
@@ -4,20 +4,18 @@
 # @File    : classifer.py
 # @Software: PyCharm
 
-
-import cv2
-import numpy as np
 import os
+import cv2
+import json
 import utils
-from sklearn.ensemble import RandomForestRegressor
 import joblib
-import torch.nn as nn
-import torch
+import logging
+import numpy as np
 from PIL import Image
 from torchvision import transforms
-import numpy as np
-import json
-import logging
+from sklearn.ensemble import RandomForestRegressor
+import torch
+import torch.nn as nn
 
 
 class Tomato:
@@ -297,11 +295,11 @@ class Passion_fruit:
         '''
         # 检查 RGB 图像是否为空或全黑
         if rgb_img is None or rgb_img.size == 0 or np.all(rgb_img == 0):
-            logging.error("RGB 图像为空或全黑，返回一个全黑RGB图像。")
+            logging.warning("RGB 图像为空或全黑，返回一个全黑RGB图像。")
             return np.zeros((100, 100, 3), dtype=np.uint8) if rgb_img is None else np.zeros_like(rgb_img)
         # 检查二值图像是否为空或全黑
         if bin_img is None or bin_img.size == 0 or np.all(bin_img == 0):
-            logging.error("二值图像为空或全黑，返回一个全黑RGB图像。")
+            logging.warning("二值图像为空或全黑，返回一个全黑RGB图像。")
             return np.zeros((100, 100, 3), dtype=np.uint8) if rgb_img is None else np.zeros_like(rgb_img)
         # 转换二值图像为三通道
         try:
@@ -359,7 +357,7 @@ class Data_processing:
     def contour_process(self, image_array):
         # 检查图像是否为空或全黑
         if image_array is None or image_array.size == 0 or np.all(image_array == 0):
-            logging.error("输入的图像为空或全黑，返回一个全黑图像。")
+            logging.warning("输入的图像为空或全黑，返回一个全黑图像。")
             return np.zeros_like(image_array) if image_array is not None else np.zeros((100, 100), dtype=np.uint8)
         # 应用中值滤波
         image_filtered = cv2.medianBlur(image_array, 5)
@@ -521,6 +519,10 @@ class Data_processing:
 
         return diameter, weigth, number_defects, total_pixels, rp
 
+
+#下面封装的是ResNet18和ResNet34的网络模型构建
+#原定用于构建RGB图像有果无果判断，后续发现存在纰漏，暂时搁置并未实际使用
+
 class BasicBlock(nn.Module):
     '''
     BasicBlock for ResNet18 and ResNet34
@@ -691,7 +693,6 @@ def resnetzy(num_classes=1000, include_top=True):
     return ResNet(Bottleneck, [2, 2, 2, 2], num_classes=num_classes, include_top=include_top)
 
 
-
 class ImageClassifier:
     '''
     图像分类器，用于加载预训练的 ResNet 模型并进行图像分类。
diff --git a/20240529RGBtest3/utils.py b/20240529RGBtest3/utils.py
index b802ba1..59ff965 100644
--- a/20240529RGBtest3/utils.py
+++ b/20240529RGBtest3/utils.py
@@ -72,12 +72,12 @@ class Pipe:
             result, data = win32file.ReadFile(rgb_receive, data_size, None)
             # 检查读取操作是否成功
             if result != 0:
-                print(f"读取失败，错误代码: {result}")
+                logging.error(f"读取失败，错误代码: {result}")
                 return None
             # 返回成功读取的数据
             return data
         except Exception as e:
-            print(f"数据接收失败，错误原因: {e}")
+            logging.error(f"数据接收失败，错误原因: {e}")
             return None
 
     def receive_spec_data(self, spec_receive):
@@ -89,12 +89,12 @@ class Pipe:
             result, spec_data = win32file.ReadFile(spec_receive, data_size, None)
             # 检查读取操作是否成功
             if result != 0:
-                print(f"读取失败，错误代码: {result}")
+                logging.error(f"读取失败，错误代码: {result}")
                 return None
             # 返回成功读取的数据
             return spec_data
         except Exception as e:
-            print(f"数据接收失败，错误原因: {e}")
+            logging.error(f"数据接收失败，错误原因: {e}")
             return None
 
     def parse_img(self, data: bytes) -> (str, any):
@@ -232,41 +232,17 @@ class Pipe:
         try:
             win32file.WriteFile(self.rgb_send, send_message)
             # time.sleep(0.01)
-            print('发送成功')
-            # print(len(send_message), len(img_bytes))
-            # print(len(send_message))
+            # print('发送成功')
         except Exception as e:
             logging.error(f'发送指令失败，错误类型：{e}')
             return False
-
         # end_time = time.time()
         # print(f'发送时间：{end_time - start_time}秒')
-
         return True
 
 
 
 
-def mkdir_if_not_exist(dir_name, is_delete=False):
-    """
-    创建文件夹
-    :param dir_name: 文件夹
-    :param is_delete: 是否删除
-    :return: 是否成功
-    """
-    try:
-        if is_delete:
-            if os.path.exists(dir_name):
-                shutil.rmtree(dir_name)
-                print('[Info] 文件夹 "%s" 存在, 删除文件夹.' % dir_name)
-
-        if not os.path.exists(dir_name):
-            os.makedirs(dir_name)
-            print('[Info] 文件夹 "%s" 不存在, 创建文件夹.' % dir_name)
-        return True
-    except Exception as e:
-        print('[Exception] %s' % e)
-        return False
 
 def create_file(file_name):
     """