[Python+OpenCV contour detection shape recognition rectangle/square/circle]

Part Ⅰ

As the title shows, the ultimate goal is to identify three different shapes of square, rectangle, and circle in a picture through the method of contour detection, and mark them in the picture. code show as below:

import cv2
import numpy as np

#定义形状检测函数
def ShapeDetection(img):
    contours,hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)  #寻找轮廓点
    for obj in contours:
        area = cv2.contourArea(obj)  #计算轮廓内区域的面积
        cv2.drawContours(imgContour, obj, -1, (255, 0, 0), 4)  #绘制轮廓线
        perimeter = cv2.arcLength(obj,True)  #计算轮廓周长
        approx = cv2.approxPolyDP(obj,0.02*perimeter,True)  #获取轮廓角点坐标
        CornerNum = len(approx)   #轮廓角点的数量
        x, y, w, h = cv2.boundingRect(approx)  #获取坐标值和宽度、高度

        #轮廓对象分类
        if CornerNum ==3: objType ="triangle"
        elif CornerNum == 4:
            if w==h: objType= "Square"
            else:objType="Rectangle"
        elif CornerNum>4: objType= "Circle"
        else:objType="N"

        cv2.rectangle(imgContour,(x,y),(x+w,y+h),(0,0,255),2)  #绘制边界框
        cv2.putText(imgContour,objType,(x+(w//2),y+(h//2)),cv2.FONT_HERSHEY_COMPLEX,0.6,(0,0,0),1)  #绘制文字

path = 'Photos/shapes.png'
img = cv2.imread(path)
imgContour = img.copy()

imgGray = cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)  #转灰度图
imgBlur = cv2.GaussianBlur(imgGray,(5,5),1)  #高斯模糊
imgCanny = cv2.Canny(imgBlur,60,60)  #Canny算子边缘检测
ShapeDetection(imgCanny)  #形状检测

cv2.imshow("Original img", img)
cv2.imshow("imgGray", imgGray)
cv2.imshow("imgBlur", imgBlur)
cv2.imshow("imgCanny", imgCanny)
cv2.imshow("shape Detection", imgContour)

cv2.waitKey(0)

Part Ⅱ

The implemented functions are shown in the figure below.



The understanding of the functions used is written in the comments, and the level is limited. Please feel free to correct me!