矩形检测.py

import time

import cv2
import numpy as np
# 创建VideoCapture对象，参数为0表示使用本地摄像头
cap = cv2.VideoCapture(0)
#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
        if area <10000:
            continue#过滤小点
        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
        print("轮廓角点坐标={}".format(approx))
        print("x={},y={},w={} h={}".format(x,y,w,h))

        #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



if __name__ == '__main__':
    while True:
        ret, frame = cap.read()# 从摄像头中读取一帧图像

        # 显示图像
        # #cv2.imshow('Local Camera', frame)
        # path = '123.jpg'
        # img = cv2.imread(path)
        img =frame
        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("shape Detection", imgContour)
        #time.sleep(1)
        cv2.waitKey(0)#按读取下一帧图片