python-opencv 图像切块

python-opencv 图像切块

                

1. 代码

import matplotlib.pyplot as plt
# from scipy import signal
import numpy as np
# import copy as cp
import cv2

def 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 = 224
dim = (width, height)
# resize image
img = 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=4
n=4
divide_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/