利用python的图像分块与拼接

import os
import matplotlib.pyplot as plt
import cv2
import numpy as np
 
def divide_img(img_path, img_name, save_path):
   imgg=img_path+img_name
   img = cv2.imread(imgg)
#   img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
   h = img.shape[0]
   w = img.shape[1]
   n=8
   m=8
   print('h={},w={},n={},m={}'.format(h,w,n,m))
   dis_h=int(np.floor(h/n))
   dis_w=int(np.floor(w/m))
   num=0
   for i in range(n):
     for j in range(m):
       num+=1
       print('i,j={}{}'.format(i,j))
       sub=img[dis_h*i:dis_h*(i+1),dis_w*j:dis_w*(j+1),:]
       cv2.imwrite(save_path + '_{}.tif'.format(num),sub)
   
 
 
if __name__ == '__main__':
 
  img_path = 'D:\\PycharmDOC\\divide_test_photo\\s1\\'
  save_path = 'D:\\PycharmDOC\\divide_test_photo\\s2\\'
  img_list = os.listdir(img_path)
  for name in img_list:
    divide_img(img_path,name,save_path)

import PIL.Image as Image
import os
 
IMAGES_PATH = 'D:\\PycharmDOC\\divide_test_photo\\s3\\'  # 图片集地址
IMAGES_FORMAT = ['.jpg', '.tif']  # 图片格式
IMAGE_SIZE = 128  # 每张小图片的大小
IMAGE_ROW = 8  # 图片间隔，也就是合并成一张图后，一共有几行
IMAGE_COLUMN = 8  # 图片间隔，也就是合并成一张图后，一共有几列
IMAGE_SAVE_PATH = 'D:\\PycharmDOC\\divide_test_photo\\pj.tif'  # 图片转换后的地址
 
# 获取图片集地址下的所有图片名称
image_names = [name for name in os.listdir(IMAGES_PATH) for item in IMAGES_FORMAT if
               os.path.splitext(name)[1] == item]
 
# 简单的对于参数的设定和实际图片集的大小进行数量判断
if len(image_names) != IMAGE_ROW * IMAGE_COLUMN:
    raise ValueError("合成图片的参数和要求的数量不能匹配！")
 
# 定义图像拼接函数
def image_compose():
    to_image = Image.new('RGB', (IMAGE_COLUMN * IMAGE_SIZE, IMAGE_ROW * IMAGE_SIZE)) #创建一个新图
    # 循环遍历，把每张图片按顺序粘贴到对应位置上
    for y in range(1, IMAGE_ROW + 1):
        for x in range(1, IMAGE_COLUMN + 1):
            from_image = Image.open(IMAGES_PATH + image_names[IMAGE_COLUMN * (y - 1) + x - 1]).resize(
                (IMAGE_SIZE, IMAGE_SIZE),Image.ANTIALIAS)
            to_image.paste(from_image, ((x - 1) * IMAGE_SIZE, (y - 1) * IMAGE_SIZE))
    return to_image.save(IMAGE_SAVE_PATH) # 保存新图
image_compose() #调用函数