Python+OpenCV（四）——像素运算

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Python+OpenCV（四）——像素运算

学习视频：python+opencv3.3视频教学基础入门
其他学习记录：
Python+OpenCV（一）——基础操作
Python+OpenCV（二）——Numpy模块
Python+OpenCV（三）——色彩空间

源码如下：

# -*- coding = utf-8 -*-
# @Time : 2021/7/31 16:00
# @Author : 西兰花
# @File : OpenCV02.py
# @Software : PyCharm


"""
像素运算
"""

import cv2 as cv
import numpy as np


def arithmetic_demo(m1, m2):    # 像素的四则运算
    dst = cv.add(m1, m2)        # 像素相加
    cv.imshow("add_demo", dst)

    dst = cv.subtract(m1, m2)   # 像素相减
    cv.imshow("subtract_demo", dst)

    dst = cv.divide(m1, m2)     # 像素相除
    cv.imshow("divide_demo", dst)

    dst = cv.multiply(m1, m2)   # 像素相乘
    cv.imshow("multiply_demo", dst)
    

def logic_demo(m1, m2):             # 像素的逻辑运算
    dst = cv.bitwise_and(m1, m2)    # 像素“和”运算
    cv.imshow("bitwise_and", dst)

    dst = cv.bitwise_or(m1, m2)     # 像素“或”运算
    cv.imshow("bitwise_or", dst)

    image = cv.imread("C:/Users/Administrator/Pictures/PS/3.jpg")
    cv.imshow("image_3.jpg----before", image)
    image = cv.bitwise_not(image)     # 像素取反运算
    cv.imshow("image_3.jpg----after", image)


def contrast_brightness_demo(image, c, b):  # 对比度、亮度调节
    h, w, c = image.shape
    blank = np.zeros([h, w, c], image.dtype)
    dst = cv.addWeighted(image, c, blank, 1-c, b)
    cv.imshow("contrast_brightness_demo——after", dst)


def others(m1, m2):
    M1, dev1 = cv.meanStdDev(m1)    # 计算矩阵的均值和标准偏差
    M2, dev2 = cv.meanStdDev(m2)

    print(M1)
    print(M2)

    print(dev1)
    print(dev2)


print("------ Hello OpenCV ------")
# src1 = cv.imread("C:/Users/Administrator/Pictures/PS/2.jpg")     # 读取图像
# src2 = cv.imread("C:/Users/Administrator/Pictures/PS/8.png")
# print(src1.shape)
# print(src2.shape)
# cv.imshow("image1", src1)    # 显示图像
# cv.imshow("image2", src2)

# others(src1, src2)
# arithmetic_demo(src1, src2)   #像素的四则运算
# logic_demo(src1, src2)        #像素的逻辑运算
src3 = cv.imread("C:/Users/Administrator/Pictures/PS/1.jpg")
cv.imshow("contrast_brightness_demo——before", src3)
contrast_brightness_demo(src3, 3, 50)  # 对比度、亮度调节
cv.waitKey(0)

cv.destroyAllWindows()  # 销毁/关闭所有窗口

输出结果：