opencv_day4

import cv2
import matplotlib.pylab as plt
import numpy as np
img1 = cv2.imread('D:\\gudugudu\\Pictures\\weixin\\xiaotidaya.jpg', cv2.IMREAD_ANYCOLOR)
img2 = cv2.imread('D:\\gudugudu\\Pictures\\weixin\\guoqing.jpg', cv2.IMREAD_GRAYSCALE)
img3 = cv2.imread('D:\\gudugudu\\Pictures\\weixin\\zhaoyang.jpg', cv2.IMREAD_GRAYSCALE)
img_x = cv2.resize(img1, (500, 500))
img_y = cv2.resize(img2, (500, 500))
img_z = cv2.resize(img3, (500, 500))
vc = cv2.VideoCapture("D:\\gudugudu\\Pictures\\weixin\\WeChat_20240706150425.mp4")


def cv_show(name, img):
    cv2.imshow('name', img)
    cv2.waitKey(0)
    cv2.destroyWindow()


def Blur(img):#均值滤波，简单的平均卷积操作
    blur = cv2.blur(img, (3, 3))
    cv2.imshow('blur', blur)
    cv2.waitKey(0)
    cv2.destroyWindow()


def Box_1(img):#方框滤波，基本和平均滤波一样，可以选择 归一化
    box = cv2.boxFilter(img, -1, (3, 3), normalize=True)
    cv_show('box', box)


def Box_2(img):#方框滤波，基本和平均滤波一样，可以选择 归一化 容易越界
    box = cv2.boxFilter(img, -1, (3, 3), normalize=False)
    cv_show('box', box)


def Gauss(img): #高斯滤波， 高斯分布的卷积核里满足高斯分布， 相当于重视中间的
    aussian = cv2.GaussianBlur(img, (5, 5), 1)
    cv_show('Gauss', img)


def Media(img):#中值滤波，取中间的
    media = cv2.medianBlur(img, 5)
    cv_show('media', media)