python实现图片切割和合并

Myth丶恋晨 2023-10-03 21:38 40阅读 0赞

> 在进行滑块验证码图像还原的过程中，需要用到图片切割成小的图像块，然后根据给定的排序对小的图像块进行重新组合。

**目录**

一、将原图进行切割

二、切割之后的图片

三、还原之后的图片

--------------------

![05c672d2196c4f419dbe862006987589.png][] 未切割前的图片

## 一、将原图进行切割 ##

> 根据分析，原图像大小尺寸为：宽：300px,高：200px
> 
> 需要将原图切割为：宽：30px ，高：100px ,共20块

from PIL import Image
    import numpy as np
    import cv2
    import os
    
    
    # 切割图片
    def splitimage(src, rownum, colnum, dstpath, arr):
        img = Image.open(src)
        w, h = img.size
        if rownum <= h and colnum <= w:
            print('原图基本信息:宽:{}px,高:{}px,图片格式:{}'.format(w, h, img.format))
            print('图片切割开始处理, 请稍候...')
            s = os.path.split(src)
            if dstpath == '':
                dstpath = s[0]
            fn = s[1].split('.')
            basename = fn[0]
            ext = fn[-1]
            num = 0
            rowheight = h // rownum
            colwidth = w // colnum
            for r in range(rownum):
                for c in range(colnum):
                    box = (c * colwidth, r * rowheight, (c + 1) * colwidth, (r + 1) * rowheight)
                    img.crop(box).save(os.path.join(dstpath, rewrite_filename(arr.pop()) + '.' + ext), ext)
                    num = num + 1
    
            print('图片切割完成，共生成 {}张小图片'.format(num))
        else:
            print('行列切割参数不合法')
    
    
    # 合并图片
    def merge_picture(merge_path, num_of_cols, num_of_rows):
        filename = file_name(merge_path, ".png")
        shape = cv2.imread(filename[0], -1).shape  # 三通道的影像需把-1改成1
        cols = shape[1]
        rows = shape[0]
        channels = shape[2]
        dst = np.zeros((rows * num_of_rows, cols * num_of_cols, channels), np.uint8)
        for i in range(len(filename)):
            img = cv2.imread(filename[i])
            m, n = filename[i].split("\\")[-1].split(".")[0].split("_")
            cols_th = int(n)
            rows_th = int(m)
            roi = img[0:rows, 0:cols, :]
            dst[rows_th * rows:(rows_th + 1) * rows, cols_th * cols:(cols_th + 1) * cols, :] = roi
        cv2.imwrite(merge_path + "merge.png", dst)
    
    
    # 遍历文件夹下的图片
    def file_name(root_path, picturetype):
        filename = []
        for root, dirs, files in os.walk(root_path):
            for file in files:
                if os.path.splitext(file)[1] == picturetype:
                    filename.append(os.path.join(root, file))
        return filename
    
    
    # 重写文件名称
    def rewrite_filename(num):
        num = int(num)
        if (num < 10):
            return "0_{}".format(num)
        else:
            i = num % 10
            return "1_{}".format(i)
    
    
    if __name__ == '__main__':
        # 正确的文件块顺序
        arr = "18,13,9,5,3,10,2,7,19,14,6,1,12,17,11,0,8,15,4,16".split(",")
        arr.reverse()
        # 切割图片
        splitimage(r'E:\vdemo\img\code.png', 2, 10, r'E:\vdemo\img\file', arr)
        # 合并图片
        merge_picture(r'E:\vdemo\img\file', 10, 2)

## 二、切割之后的图片 ##

![bc1c22fdff394a429a96877ce070d34c.png][] 切割之后的图片

## 三、还原之后的图片 ##

![1eac60e53d574f3da22e98414c77ab3e.png][]

![f153771b223e4b12ab1895953031e16a.png][] 还原之后的图片

[05c672d2196c4f419dbe862006987589.png]: https://img-blog.csdnimg.cn/05c672d2196c4f419dbe862006987589.png
[bc1c22fdff394a429a96877ce070d34c.png]: https://img-blog.csdnimg.cn/bc1c22fdff394a429a96877ce070d34c.png
[1eac60e53d574f3da22e98414c77ab3e.png]: https://img-blog.csdnimg.cn/1eac60e53d574f3da22e98414c77ab3e.png
[f153771b223e4b12ab1895953031e16a.png]: https://img-blog.csdnimg.cn/f153771b223e4b12ab1895953031e16a.png