该代码是在处理DeepGlobe时所写，可灵活应用

deepglobe 数据训练图片和标签的大小都是1024×1024，而我们要处理成256×256；便可以使用下列代码。

def clip():

    imgpath = "Original training image path"
    labelpath = "Original label path"

    imgfile = os.listdir(imgpath)
    labelfile = os.listdir(labelpath)

    conut = len(imgfile)
    strip = np.int32(1024/256)  #256 随自己变动

    for i in range(conut):

        imgp = imgpath + "/" + imgfile[i]
        labelp = labelpath + "/" + labelfile[i]

        imgname = imgfile[i][0:-4]
        labelname = labelfile[i][0:-4]

        img = Image.open(imgp)
        label = Image.open(labelp)

        saveimg = "save image path" + imgname
        savelabel = "save label path" + labelname

        c = 0

        for j in range(strip):
            for n in range(strip):

                box = (256*j, 256*n, 256*(j+1), 256*(n+1))  #裁剪关键

                img2 = img.crop(box)
                label2 = label.crop(box)

                si = saveimg + " %d" % (c+1) + ".png"
                sl = savelabel + " %d " % (c+1) + ".png"

                img2.save(si)
                label2.save(sl)
                c = c + 1