二 OpenCV 图像的基础操作

1·获取像素并修改

import cv2 as cv

import numpy as np

img = cv.imread('E:\\fruits.jpg')

##print(img)     

px = img[100,100]#获取第100行第100列的3维矩阵

print(px)

print(img[100,100,2])#获取矩阵值

val =[ i for i in img[100,100] ]#遍历矩阵

print(val)

 

print(img.item(100,100,2))#快速获取矩阵值

img.itemset((100,100,2),99)#快速修改矩阵值

print(img[100,100])

 

 

2·获取图像的属性信息

           获取到属性信息有：

          

 

        

 

import cv2 as cv

import numpy as np

 

img = cv.imread('E:\\fruits.jpg')

print(img.shape)

 

3·图像通道的合并和拆分

           #局部区域赋值

import cv2 as cv

import numpy as np

#deal

img = cv.imread('E:\\fruits.jpg')

print(img.shape)

area = img[280:340,330:390]#选中区域280行-340行，330列-360列

img[273:333,100:160] = area#将该区域修改值

#show

cv.namedWindow('IMG')

cv.imshow('IMG',img)

cv.waitKey(0)

cv.destroyAllWindows()

 

 

           #通道合并、拆分、修改               

import cv2 as cv

import numpy as np

#deal

img = cv.imread('E:\\fruits.jpg')

 

b,g,r = cv.split(img)#分离

img = cv.merge([b,g,r])#合并

#for i in img[:,:,0]:print(i)

 

img[:,:,0] = 0 #改变R通道值

img[:,:,1] = 0 #改变G通道值

img[:,:,2] = 0 #改变B通道值

 

#show

cv.namedWindow('IMG')

cv.imshow('IMG',img)

cv.waitKey(0)

cv.destroyAllWindows()

 

4·图形填充

           函数：cv.copyMakeBorder()

                   例子：略

• ·图像的算术运算

         两个图形的大小，数据类型一致才可以进行运算，运算结果越界则取余数

         #直接运算

例：        

import cv2 as cv

import numpy as np

 

x = np.uint8([250])

y = np.uint8([10])

z = np.uint16(65537)

 

print(cv.add(x,y))# 250+10 = 260 => 255

print(x+y)# 250+10 = 260 % 256 = 4

print(z)#65537%2^16 = 1

        

         #图形混合：

算法一 ：cv.addWeighted()   g (x) = (1 − α)  (x) + α (x)  其中α为透明度

例如：    

 

import cv2 as cv

import numpy as np

#两个大小、数据类型一致的图像

imgf1 = cv.imread('E:\\fruits.jpg')

imgf2 = cv.imread('E:\\fruits_copy.jpg')

 

dst = cv.addWeighted(imgf1,0.3,imgf2,0.7,0)#目标图像

 

cv.namedWindow('IMG')

cv.imshow('IMG',dst)

cv.waitKey(0)

cv.destroyAllWindows()

 

        

          #图形合并：在图片上加图标、水印、文字等        

 

import cv2 as cv

import numpy as np

#两个大小、数据类型一致的图像

img1 = cv.imread('E:\\fruits.jpg')

img2 = cv.imread('E:\\logo.jpg')

 

rows,cols ,channels = img2.shape

roi = img1[0:rows,0:cols]

img2gray = cv.cvtColor(img2,cv.COLOR_BGR2GRAY)

ret,mask = cv.threshold(img2gray,175,255,cv.THRESH_BINARY)#峰值,掩码

mask_inv = cv.bitwise_not(mask)#按位not操作

 

img1_bg = cv.bitwise_and(roi,roi,mask)

img2_fg = cv.bitwise_and(img2,img2,mask=mask_inv)

 

dst = cv.add(img1_bg,img2_fg)

img1[0:rows,0:cols] = dst

 

cv.namedWindow('IMG')

cv.imshow('IMG', img1)

cv.waitKey(0)

cv.destroyAllWindows()

 

 

 

 

参考 OpenCv官方教材文档

1.http://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_gui/py_table_of_contents_gui/py_table_of_contents_gui.html#