Python+OpenCV实现角点、周长、面积检测

一、周长和面积检测

import cv2
import numpy as np
 
img = cv2.imread("test1.png")  
img = img.astype(np.uint8)

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)  
ret, binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)  
 
contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)  
cv2.drawContours(img,contours,-1,(0,255,255),3)

max_area = -1

for i in range(len(contours)):
    area = cv2.contourArea(contours[i])
    length= cv2.arcLength(contours[i], True)
    M = cv2.moments(contours[i])#计算图像矩
    cx = int(M['m10']/M['m00'])#重心的x坐标    
    cy = int(M['m01']/M['m00'])#重心的y坐标
    cv2.putText(img, f"area{str(i)}:"+str(area), (cx,cy), cv2.FONT_HERSHEY_PLAIN, 2.0, (0, 0, 255), 2)
    
    print(f"area{str(i)}:",area)
    
    if area>max_area:
        cnt = contours[i]
        max_area = area


cv2.imshow("img", img)  
cv2.waitKey(0)

程序中的图像：

 

二、 角点检测

import cv2
import numpy as np
 
#读入图像并转化为float类型，用于传递给harris函数
filename = 'test.jpg'
 
img = cv2.imread(filename)
 
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 
gray_img = np.float32(gray_img)
 
#对图像执行harris
Harris_detector = cv2.cornerHarris(gray_img, 2, 3, 0.04)
 
#腐蚀harris结果
dst = cv2.dilate(Harris_detector, None)
 
# 设置阈值
thres = 0.01*dst.max()
 
img[dst > thres] = [255,0,0]
 
cv2.imshow('show', img)
 
cv2.waitKey()