__author__ = "WSX"

 import cv2 as cv

 import numpy as np

 # 基于拓扑结构来发现和绘制（边缘提取）

 # cv.findContours() 发现轮廓

 # cv.drawContours()  绘制轮廓

 # 使用梯度 ，不需要阈值了就

 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)

     cv.imshow("Canny Edge", edge_output)

     return edge_output

 def contours_demo(image):

     """dst = cv.GaussianBlur(image, (3, 3), 0)

     gray = cv.cvtColor(dst, cv.COLOR_BGR2GRAY)

     ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)

     cv.imshow("binary image", binary)"""

     binary = edge_demo(image)

     cloneImage, contours, heriachy = cv.findContours(binary, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)

     # cv.RETR_EXTERNAL最大轮廓  CHAIN_APPROX_SIMPLE简单的

     #contours 放轮廓          heriachy层次信息

     for i, contour in enumerate(contours):

         cv.drawContours(image, contours, i, (0, 0, 255), 2)

         #绘制(0, 0, 255)颜色   2 为宽度       若为-1 则填充轮廓

         approxCurve = cv.approxPolyDP(contour, 4, True)

         if approxCurve.shape[0] > 6:

             cv.drawContours(image, contours, i, (0, 255, 255), 2)

         if approxCurve.shape[0] == 4:

             cv.drawContours(image, contours, i, (255, 255, 0), 2)

         print(approxCurve.shape[0])

         print(i)

     cv.imshow("detect contours", image)

 def main():

     img = cv.imread("1.JPG")

     cv.namedWindow("Show", cv.WINDOW_AUTOSIZE)

     cv.imshow("Show", img)

     contours_demo(img)

     cv.waitKey(0)

     cv.destroyAllWindows()

 main()