onnx口罩分类

softmax python版：

      # -*- coding: utf-8 -*-
      import os
      import time
      import cv2
      import numpy as np
      net = cv2.dnn.readNetFromONNX(r'mobile_mask.onnx')
      print("net load")
      def softmax(x, axis=1):
         # 计算每行的最大值
          row_max = x.max(axis=axis)
         # 每行元素都需要减去对应的最大值，否则求exp(x)会溢出，导致inf情况
          row_max = row_max.reshape(-1, 1)
          x = x - row_max
          x_exp = np.exp(x)
          x_sum = np.sum(x_exp, axis=axis, keepdims=True)
          s = x_exp / x_sum
         return s
      if __name__ == '__main__':
          list_path=r"D:\project\face\face_mask\2020\0/"
          list_path = r"test/"
          g = os.walk(list_path)
          files = ['%s\\%s' % (i[0], j) for i in g for j in i[-1] if
                   j.endswith('jpg')]
          count=0
          ok_count=0
         for file in files:
              file_path=file
              img=cv2.imread(file)
             if img is
  
 

文章来源: blog.csdn.net，作者：AI视觉网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/104393063