import os
import numpy as np

#
# name:txt文件名
# rootdir:根路径
# metaimage:原始图像路径
# imglabel:标签图像路径
#
def write_to_txt(name, root_dir, metaimage, imglabel):
    txt_path = root_dir + name + \'.txt\'
    txt = open(txt_path, \'w\')
    for (i,j) in zip(metaimage,imglabel):
        image_dir = os.path.join(str(i))
        # image_dir = os.path.join(\'./data/metaimage/\', str(i))
        label_dir = os.path.join(str(j))
        # label_dir = os.path.join(\'./data/imglabel/\', str(j))
        # 截取文件名
        txt.write(image_dir[0:-4] + \'\n\')
        txt.write(label_dir[0:-4] + \'\n\')

def read_image(path1, path2):
    filelist1 = os.listdir(path1)
    meta_image = np.array([file for file in filelist1 if file.endswith(\'.jpg\')], dtype=object)
    print("-------len(metaimage):", len(meta_image))
    filelist2 = os.listdir(path2)
    img_label = np.array([file for file in filelist2 if file.endswith(\'.png\')], dtype=object)
    print("-------len(imglabel):", len(img_label))
    return meta_image, img_label


path1 = r\'data/VOCtrainval_11-May-2012/VOCdevkit/Meta/JPEGImages\'
path2 = r\'data/VOCtrainval_11-May-2012/VOCdevkit/Meta/SegmentationClass\'

metaimage, imglabel = read_image(path1, path2)
write_to_txt(\'train\', \'./data/\', metaimage, imglabel)

 

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