opencv学习笔记05

算术运算
逻辑运算

1.像素相加

import cv2 as cv
import numpy as np


def add_demo(m1, m2):
    dst = cv.add(m1, m2)  # 将图像m1和图像m2的像素相加
    cv.imshow("add_demo", dst)


src1 = cv.imread("C:/Users/ASUS/Desktop/11/LinuxLogo.jpg")  # 从目录中读取图片
src2 = cv.imread("C:/Users/ASUS/Desktop/11/WindowsLogo.jpg")
cv.namedWindow("image1", cv.WINDOW_AUTOSIZE)  # 通过opencv的GUI将图片显示出来
cv.namedWindow("image2", cv.WINDOW_AUTOSIZE)
cv.imshow("image1", src1)  # 在窗口中将图片显示出来，通过名字“src”找到图片
cv.imshow("image2", src2)
add_demo(src1, src2)
cv.waitKey(0)
cv.destroyAllWindows()

输出：



2.像素相减

import cv2 as cv
import numpy as np


def subtract_demo(m1, m2):
    dst = cv.subtract(m1, m2)  # 将图像m1和图像m2的像素相加
    cv.imshow("subtract_demo", dst)


src1 = cv.imread("C:/Users/ASUS/Desktop/11/LinuxLogo.jpg")  # 从目录中读取图片
src2 = cv.imread("C:/Users/ASUS/Desktop/11/WindowsLogo.jpg")
cv.namedWindow("image1", cv.WINDOW_AUTOSIZE)  # 通过opencv的GUI将图片显示出来
cv.namedWindow("image2", cv.WINDOW_AUTOSIZE)
cv.imshow("image1", src1)  # 在窗口中将图片显示出来，通过名字“src”找到图片
cv.imshow("image2", src2)
subtract_demo(src1, src2)
cv.waitKey(0)
cv.destroyAllWindows()

输出

3.像素相除

import cv2 as cv
import numpy as np


def divide_demo(m1, m2):
    dst = cv.divide(m1, m2)  # 将图像m1和图像m2的像素相加
    cv.imshow("divide_demo", dst)


src1 = cv.imread("C:/Users/ASUS/Desktop/11/LinuxLogo.jpg")  # 从目录中读取图片
src2 = cv.imread("C:/Users/ASUS/Desktop/11/WindowsLogo.jpg")
cv.namedWindow("image1", cv.WINDOW_AUTOSIZE)  # 通过opencv的GUI将图片显示出来
cv.namedWindow("image2", cv.WINDOW_AUTOSIZE)
cv.imshow("image1", src1)  # 在窗口中将图片显示出来，通过名字“src”找到图片
cv.imshow("image2", src2)
divide_demo(src1, src2)
cv.waitKey(0)
cv.destroyAllWindows()

输出

4.像素相乘

import cv2 as cv
import numpy as np


def multiply_demo(m1, m2):
    dst = cv.multiply(m1, m2)  # 将图像m1和图像m2的像素相加
    cv.imshow("divide_demo", dst)


src1 = cv.imread("C:/Users/ASUS/Desktop/11/LinuxLogo.jpg")  # 从目录中读取图片
src2 = cv.imread("C:/Users/ASUS/Desktop/11/WindowsLogo.jpg")
cv.namedWindow("image1", cv.WINDOW_AUTOSIZE)  # 通过opencv的GUI将图片显示出来
cv.namedWindow("image2", cv.WINDOW_AUTOSIZE)
cv.imshow("image1", src1)  # 在窗口中将图片显示出来，通过名字“src”找到图片
cv.imshow("image2", src2)
multiply_demo(src1, src2)
cv.waitKey(0)
cv.destroyAllWindows()

输出

5.计算每个通道均值

import cv2 as cv
import numpy as np


def others(m1, m2):  # 计算每个通道的均值
    M1 = cv.mean(m1)
    M2 = cv.mean(m2)
    print(M1)
    print(M2)


src1 = cv.imread("C:/Users/ASUS/Desktop/11/LinuxLogo.jpg")  # 从目录中读取图片
src2 = cv.imread("C:/Users/ASUS/Desktop/11/WindowsLogo.jpg")
cv.namedWindow("image1", cv.WINDOW_AUTOSIZE)  # 通过opencv的GUI将图片显示出来
cv.namedWindow("image2", cv.WINDOW_AUTOSIZE)
cv.imshow("image1", src1)  # 在窗口中将图片显示出来，通过名字“src”找到图片
cv.imshow("image2", src2)
others(src1, src2)
cv.waitKey(0)
cv.destroyAllWindows()

输出

三个通道分别对应：blue   green   red
(15.0128125, 15.0128125, 15.0128125, 0.0)
(128.05269531250002, 109.60858072916668, 62.55748697916667, 0.0)

6.计算图像均值和方差

import cv2 as cv
import numpy as np


def others(m1, m2):  # 计算每个通道的均值
    M1, dev1 = cv.meanStdDev(m1)
    M2, dev2 = cv.meanStdDev(m2)
    print(M1)
    print(M2)
    print(dev1)
    print(dev2)


src1 = cv.imread("C:/Users/ASUS/Desktop/11/LinuxLogo.jpg")  # 从目录中读取图片
src2 = cv.imread("C:/Users/ASUS/Desktop/11/WindowsLogo.jpg")
cv.namedWindow("image1", cv.WINDOW_AUTOSIZE)  # 通过opencv的GUI将图片显示出来
cv.namedWindow("image2", cv.WINDOW_AUTOSIZE)
cv.imshow("image1", src1)  # 在窗口中将图片显示出来，通过名字“src”找到图片
cv.imshow("image2", src2)
others(src1, src2)
cv.waitKey(0)
cv.destroyAllWindows()

输出

[[15.0128125]
 [15.0128125]
 [15.0128125]]
[[128.05269531]
 [109.60858073]
 [ 62.55748698]]
[[58.14062149]
 [58.14062149]
 [58.14062149]]
[[54.60093646]
 [45.52335089]
 [50.01800277]]