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# -*- coding: utf-8 -*"""Created by Xingxiangrui on 2019.5.9This code is to :    1. copy image from source_image_dir to the target_image_dir    2. And generate .txt file for further training        in which each line is : image_name.jpg  (tab)  image_label (from 0)        such as:            image_01.jpg    0            iamge_02.jpg    1            ...            image_02.jpg    0""" # import matplotlib.pyplot as pltimport numpy as npfrom PIL import Imageimport osimport random # variables need to be changesource_image_dir="/Users/baidu/Desktop/used/SuZhouRuiTu_dataset/single-poly-defect/poly_OK"target_image_dir="/Users/baidu/Desktop/used/SuZhouRuiTu_dataset/data_for_resnet_classification"txt_file_dir="/Users/baidu/Desktop/used/SuZhouRuiTu_dataset/data_for_resnet_classification/TxtFile"prefix="poly_OK"class_label=1# label 0: single_OK ; label_1: poly_OK ; label 2: poly_defect print("Program Start......")print("-"*20)print("-"*20)print("-"*20) # load image list in the source dirsource_image_list = os.listdir(source_image_dir)for idx in range(len(source_image_list)):    if '.png' in source_image_list[idx-1]:        continue    elif '.jpg' in source_image_list[idx-1]:        continue    else:        del source_image_list[idx-1] # shuffle image listprint("initial list:")print source_image_listrandom.shuffle(source_image_list)print("shuffled list:")print source_image_list # train list and val listsource_train_list=[]source_val_list=[]for idx in range(len(source_image_list)):    if idx

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