基于opencv的规则图形的识别
# -*- codeing = utf-8 -*-# @Time : 2021/5/9 21:41
# @File ：校内赛识别图形最终版本.py
# @Software : PyCharm
import cv2 as cv
def detectShape(img):
# 查找轮廓，cv2.RETR_ExTERNAL=获取外部轮廓点, CHAIN_APPROX_NONE = 得到所有的像素点
contours, hierarchy = cv.findContours(img, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
# 循环轮廓，判断每一个形状
global count
global objectType
count = 0
objectType = None
for cnt in contours:
# 获取轮廓面积
area = cv.contourArea(cnt)
# 当面积大于2000，代表有形状存在
if area > 2000:
# 绘制所有的轮廓并显示出来(-1)
cv.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
# 计算所有轮廓的周长，便于做多边形拟合
peri = cv.arcLength(cnt, True)
# 多边形拟合，获取每个形状的边
approx = cv.approxPolyDP(cnt, 0.02 * peri, True)
objCor = len(approx)
# 获取每个形状的x，y，w，h
x, y, w, h = cv.boundingRect(approx)
# 计算出边界后，即边数代表形状，如三角形边数=3
if objCor == 3:
objectType = "Triangle"
print("形状是%s,面积是%d" % (objectType, area))
count += 1
elif objCor == 4:
objectType = "Rectangle"
print("形状是%s,面积是%d" % (objectType, area))
count += 1
# 大于4个边的就是五边形
elif 5 <= objCor < 7:
objectType = "Pentagon"
print("形状是%s,面积是%d" % (objectType, area))
count += 1
elif objCor == 8:
objectType = "Circle"
print("形状是%s,面积是%d" % (objectType, area))
count += 1
elif objCor > 8:
objectType = "Star"
print("形状是%s,面积是%d" % (objectType, area))
count += 1
# 绘制文本时需要绘制在图形附件
cv.rectangle(imgContour, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv.putText(imgContour, objectType,
(x + (w // 2) - 10, y + (h // 2) - 10), cv.FONT_HERSHEY_COMPLEX, 0.7,
(0, 0, 0), 2)
# 调用笔记本内置摄像头，所以参数为0，官方摄像头为1
cap = cv.VideoCapture(0, cv.CAP_DSHOW)
while True:
# 从摄像头读取图片
success, img = cap.read()
# 转换大小
img = cv.resize(img, (1280, 720))
# 灰度化
imgGray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# 高斯平滑
imgBlur = cv.GaussianBlur(imgGray, (7, 7), 1)
# 边缘检测
imgCanny = cv.Canny(imgBlur, 200, 200)
# 膨胀
kernel = cv.getStructuringElement(cv.MORPH_RECT, (2, 2))
swell = cv.dilate(imgCanny, kernel=kernel)
# 调用检测函数
imgContour = img.copy()
detectShape(swell)
# 绘制文本
cv.putText(imgContour, "%s,%d" % (objectType, count), (10, 50), cv.FONT_HERSHEY_PLAIN, 2.0,
(0, 0, 0), 2)
# 若参数delay≤0：表示一直等待按键；
# 若delay取正整数：表示等待按键的时间，比如cv2.waitKey(100)，就是等待100毫秒
k = cv.waitKey(100)
# 保持画面的持续。
cv.imshow("img", imgContour)
if k == 27:
# 通过esc键退出摄像
cv.destroyAllWindows()
break
# 关闭摄像头
cap.release()
cv.destroyAllWindows()
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