opencv_day7

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")


#canny边缘检测
'''
    1.使用高斯滤波器，平滑图像，消除噪音
    2.计算每个像素点的梯度强度和方向
    3.应用非极大值抑制，消除边缘检测带来的影响
    4.应用双阈值来检测真实的边缘和潜在的边缘
    5.通过抑制孤立的弱边缘来达到最终的边缘检测
'''


def canny(img):
    v1 = cv2.Canny(img, 20, 30)
    cv2.imshow('name', v1)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


'''
    图像金字塔
    1.高斯金字塔
    2.拉普拉斯金字塔
    作用：
        图像的提取；对每一层进行提取
'''

'''
   高斯金字塔： 从下向上采样：
                （缩小操作）向下采样的方法；
                高斯核去做，将所有偶数行与偶数列去掉
              从上向下采样：
                将图像扩大两倍，新增的行与列用0代替
'''


def Pyrup(img): #向上采样
    up = cv2.pyrUp(img)
    cv2.imshow('gudu', up)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


def Pyrdown(img): #向下采样
    down = cv2.pyrDown(img)
    cv2.imshow('gudu', down)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


def Pyrup_down(img):#反复执行会变模糊
    up = cv2.pyrUp(img)
    updown = cv2.pyrDown(up)
    cv2.imshow('gudu', np.hstack((img, updown)))
    cv2.waitKey(0)
    cv2.destroyAllWindows()


def lapulasi(img):#拉普拉斯金字塔
    up = cv2.pyrUp(img)
    updown = cv2.pyrDown(up)
    l_l = img - updown
    cv2.imshow('gudu', l_l)
    cv2.waitKey(0)
    cv2.destroyAllWindows()