1、代码
import matplotlib.pyplot as plt# from scipy import signalimport numpy as np# import copy as cpimport cv2def divide_method2(img,m,n):#分割成m行n列 h, w = img.shape[0],img.shape[1] grid_h=int(h*1.0/(m-1)+0.5)#每个网格的高 grid_w=int(w*1.0/(n-1)+0.5)#每个网格的宽 #满足整除关系时的高、宽 h=grid_h*(m-1) w=grid_w*(n-1) #图像缩放 img_re=cv2.resize(img,(w,h),cv2.INTER_LINEAR)# 也可以用img_re=skimage.transform.resize(img, (h,w)).astype(np.uint8) #plt.imshow(img_re) gx, gy = np.meshgrid(np.linspace(0, w, n),np.linspace(0, h, m)) gx=gx.astype(np.int) gy=gy.astype(np.int) divide_image = np.zeros([m-1, n-1, grid_h, grid_w,3], np.uint8)#这是一个五维的张量，前面两维表示分块后图像的位置（第m行，第n列），后面三维表示每个分块后的图像信息 for i in range(m-1): for j in range(n-1): divide_image[i,j,...]=img_re[ gy[i][j]:gy[i+1][j+1], gx[i][j]:gx[i+1][j+1],:] return divide_image#显示图片def display_blocks(divide_image): m,n=divide_image.shape[0],divide_image.shape[1] for i in range(m): for j in range(n): plt.subplot(m, n, i*n+j+1) cv2.imwrite('block:'+ str(i*n+j)+'.jpg', cv2.cvtColor(divide_image[i,j,:],cv2.COLOR_BGR2RGB)) plt.imshow(divide_image[i,j,:]) plt.axis('off') plt.title('block:'+str(i*n+j), fontdict={'weight': 'normal', 'size': 10}) plt.subplots_adjust(left=0.125, bottom=0.1, right=0.9, top=0.9, wspace=0.2, hspace=0.35) plt.show()img = cv2.imread("cat.jpg")img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)width = height = 224dim = (width, height)# resize imageimg = cv2.resize(img, dim, interpolation = cv2.INTER_AREA)h, w = img.shape[0], img.shape[1]print(h, w)fig1 = plt.figure('原始图像')plt.imshow(img)plt.axis('off')plt.title('Original image')m=4n=4divide_image2=divide_method2(img,m+1,n+1)#该函数中m+1和n+1表示网格点个数，m和n分别表示分块的块数fig3 = plt.figure('分块后的子图像:图像缩放法')display_blocks(divide_image2)# Patch Paritition 后 h/4, w/4, 16*3
2、参考 https://blog.csdn.net/qq_38970783/article/details/90083142
https://www.delftstack.com/zh/howto/matplotlib/how-to-improve-subplot-size-or-spacing-with-many-subplots-in-matplotlib/