数据集样式

下载地址：https://drive.google.com/file/d/1SlURvdQsokgsoyTosAaELc4zRjQz9T2U/view?usp=sharing

生成数据集样式

代码

import numpy as np
import cv2
import os

trainDataPath=r'F:\BaiduNetdiskDownload\DATA\train'
testDataPath=r'F:\BaiduNetdiskDownload\DATA\test'

origin_path=r'F:\BaiduNetdiskDownload\U_net_dataset\train'
label_path=r'F:\BaiduNetdiskDownload\U_net_dataset\train'

x_trainpath=r'F:\BaiduNetdiskDownload\deblugData\train\x'
y_trainpath=r'F:\BaiduNetdiskDownload\deblugData\train\y'
x_testpath=r'F:\BaiduNetdiskDownload\deblugData\test\x'
y_testpath=r'F:\BaiduNetdiskDownload\deblugData\test\y'

def cropping(path,Xsavepath,Ysavepath):

    def readFileDocument(path, layer):#read doucument
        layerN = layer
        fileDocument = os.listdir(path)
        subDocument = []
        for document in fileDocument:

            if layerN > 0:
                if (os.path.isdir(path + '/' + document, )):
                    subDocument.append((readFileDocument(path + '/' + document, layerN - 1)))
            else:
                subDocument.append(path + '/' + document)
        return subDocument

    document_location = readFileDocument(path, 1)
    cropping_height = 256
    cropping_width = 256
    number = 0 #total number of dataset to produce
    imgNumber = 10 #every img produce number
    for document in document_location:
        blur = []
        sharp = []

        for subducument in document:
            path,name = os.path.split(subducument)

            if name == 'blur':
                blur.append(subducument)
            if name == 'sharp':
                sharp.append(subducument)

        origin_list= glob.glob(blur[0]+'/*.png')
        origin_list.sort()

        label_list= glob.glob(sharp[0] +'/*.png')
        label_list.sort()

        zipped = itertools.cycle(zip(origin_list,label_list))
        for k in range(len(origin_list)):
            origin_position,label_position=next(zipped)

            origin_img=cv2.imread(origin_position,-1)
            label_img =cv2.imread(label_position,-1)
            shape = origin_img.shape

            i=0
            while i<imgNumber:

                    y=np.random.randint(0, shape[0]-cropping_height)
                    x=np.random.randint(0, shape[1]-cropping_width)

                    cropping1 = origin_img[y:(y + cropping_height),x:(x + cropping_width)]
                    cropping3 = label_img[y:(y + cropping_height),x:(x + cropping_width)]

                    cv2.imwrite(Xsavepath + '/' + str(number) + '.png', cropping1)
                    cv2.imwrite(Ysavepath + '/' + str(number) + '.png', cropping3)

                    i=i+1
                    number += 1
                    print('number',number)
                    if i ==20 :
                        break
if __name__ == '__main__':
    cropping(trainDataPath,x_trainpath,y_trainpath)
    cropping(testDataPath,x_testpath,y_testpath)