画出各个文件夹数据分布

import glob
import os,sys
import shutil
import numpy as np
import cv2
import matplotlib.pyplot as plt



import os, random, shutil,cv2

labelDir = 'F:/project/Breast/InBreast/INBreast/Unet/data/Inbreast/yes/test/label/'
imageDir = 'F:/project/Breast/InBreast/INBreast/Unet/data/Inbreast/yes/test/image/'
labelDir1 = 'F:/project/Breast/InBreast/INBreast/Unet/data/Inbreast/no/test/label/'
imageDir1 = 'F:/project/Breast/InBreast/INBreast/Unet/data/Inbreast/no/test/image/'
# Statistical the distribution of positive sample data
sum1 = np.zeros((256))
print(sum)
if __name__ == '__main__':
    txtLists = os.listdir(labelDir)  # 列出文件夹下所有的目录与文件
    print(txtLists)

    # i = 0
    for filename in txtLists:
        print(labelDir + filename)
        label = cv2.imread(labelDir + filename)
        image = cv2.imread(imageDir + filename)
        for i in range(112):
            for j in range(112):
                if label[i,j,0] == 0:
                    sum1[image[i,j,0]] = sum1[image[i,j,0]] + 1

    txtLists1 = os.listdir(labelDir1)
    for filename in txtLists1:
        print(labelDir1 + filename)
        label = cv2.imread(labelDir1 + filename)
        image = cv2.imread(imageDir1 + filename)
        for i in range(112):
            for j in range(112):
                if label[i,j,0] == 0:
                    sum1[image[i,j,0]] = sum1[image[i,j,0]] + 1

    print(sum1)
    np.savetxt("F:/project/Breast/InBreast/INBreast/Unet/data/Inbreast/yes/test/filename1.txt", sum1)











        # name = '0_'+str(i)+'_predict.png'
        # i =i + 2
        # print(name)
        # shutil.copy(fileDir + filename, tarDir + name)
        # if filename.startswith('yes'):
        #     filename1 = filename[4:]
        #     print(filename1)
        #     filename2 = os.path.join(tarDir, filename1.split('.')[0] + '_yes.png')
        #     print(filename2)
        # elif filename.startswith('no'):
        #     filename1 = filename[3:]
        #     print(filename1)
        #     filename2 = os.path.join(tarDir, filename1.split('.')[0] + '_no.png')#filename1 + '_no'
        #     print(filename2)
        #
        # img = cv2.imread(fileDir + filename)
        # image = img[:,:,0]
        # cv2.imwrite(filename2,image)
        # name = 'yes_' + filename#'yes_0_'+ str(i) + '_predict.png'
        # name1 = 'no_' + filename#'yes_0_'+ str(i) + '_predict.png'
        # i = i + 1
        # print(filename,name)
        # shutil.copy(fileDir + filename, tarDir + name)
        # shutil.copy(fileDir2 + filename, tarDir + name1)
        # shutil.copy(fileDir1 + filename, tarDir1 + name)
        # shutil.copy(fileDir22 + filename, tarDir1 + name1)
        # image1 = cv2.imread(fileDir + filename)
        # label1 = cv2.imread(fileDir1 + filename)
        # image2 = cv2.resize(image1,(448,448))
        # label2 = cv2.resize(label1,(448,448))
        # cv2.imwrite(fileDir + filename, image2)
        # cv2.imwrite(fileDir1 + filename,label2)
#         # source = fileDir + filename
#         # print(source)

        # shutil.copy(fileDir2 + filename, tarDir2 + name)
        # shutil.copy(fileDir3 + filename, tarDir3 + name)