列表推导式

import cv2 as cv
import numpy as np


def add_demo(m1, m2):
    dst = cv.add(m1, m2)
    cv.imshow('add_demo', dst)

def subtract_demo(m1, m2):
    dst = cv.subtract(m1, m2)
    cv.imshow('subtract_demo', dst)

def divide_demo(m1, m2):
    dst = cv.divide(m1, m2)
    cv.imshow('divide_demo', dst)

def multiply(m1, m2):
    dst = cv.multiply(m1, m2)
    cv.imshow('multiply_demo', dst)

def logic_demo(m1, m2):
    dst = cv.bitwise_and(m1, m2)
    dst = cv.bitwise_or(m1, m2)
    img = cv.imread('0.png')
    dst = cv.bitwise_not(img)
    cv.imshow('logic_demo', dst)

def contrast_brightness_demo(image, c, b):
    h, w, ch = image.shape
    blank = np.zeros([h,w, ch], image.dtype)
    dst = cv.addWeighted(image, c, blank, 1-c, b)
    cv.imshow('con_bri_demo', dst)

def others(m1, m2):
    M1, dev1 = cv.meanStdDev(m1)
    M2, dev2 = cv.meanStdDev(m2)
    h, w = m1.shape[:2]
    print(M1)
    print(M2)
    print(dev1)
    print(dev2)
    img = np.zeros([h, w], np.uint8)
    m, dev = cv.meanStdDev(img)
    print(m)
    print(dev)


src1 = cv.imread('./1.jpg')  # blue, green, red
src2 = cv.imread('./2.jpg')  # blue, green, red
print(src1.shape)
print(src2.shape)
cv.namedWindow('image1', cv.WINDOW_AUTOSIZE)
cv.imshow('image1', src1)
cv.imshow('image2', src2)
src = cv.imread('0.png')
cv.imshow('image2', src)
contrast_brightness_demo(src, 1.5, 10)  #图像, 对比度, 亮度
# add_demo(src1, src2)
# subtract_demo(src1, src2)
# subtract_demo(src1, src2)
# multiply(src1, src2)
# others(src1, src2)
# logic_demo(src1, src2)
cv.waitKey(0)

cv.destroyAllWindows()

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