第十七天边缘检测

获取轮廓的多边形拟合结果   approxPlyDp   -coutour     -epsilon 越小越折线越逼近真是形状   -colse  是否为闭合区域

import cv2 as cv
import numpy as np


def edge_demo(image):
    blurred = cv.GaussianBlur(image, (3, 3), 0)
    gray = cv.cvtColor(blurred, cv.COLOR_BGR2GRAY)
    # X Gradient
    xgrad = cv.Sobel(gray, cv.CV_16SC1, 1, 0)
    # Y Gradient
    ygrad = cv.Sobel(gray, cv.CV_16SC1, 0, 1)
    #edge
    #edge_output = cv.Canny(xgrad, ygrad, 50, 150)
    edge_output = cv.Canny(gray, 30, 100)               ##边缘检测
    cv.imshow("Canny Edge", edge_output)
    return edge_output

def contours_demo(image):
    # dst = cv.GaussianBlur(image, (3, 3), 0)    #GaussianBlur()函数用高斯滤波器(GaussianFilter)对图像进行平滑处理。
    # gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    # ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)
    # cv.imshow("binary image", binary)

    cloneImage, contours, heriachy = cv.findContours(binary, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)  #轮廓  contours  层次信息heriachy
    for i,contour in enumerate(contours):
        cv.drawContours(image, contours, i, (0, 0, 255), 2)
        print(i)
        cv.imshow("contours",image)
print("--------- Python OpenCV Tutorial ---------")
src = cv.imread("C:/Users/weiqiangwen/Desktop/sest/contours.png")
# cv.namedWindow("input contours",cv.WINDOW_AUTOSIZE)
cv.imshow("contours", src)
edge_demo(src)
cv.waitKey(0)

cv.destroyAllWindows()

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转载自blog.csdn.net/qq_32340685/article/details/83626631