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()