Opencv-图像检测学习

import cv2 import numpy as np # 读取图片 image = cv2.imread('test.jpg') # 将图片转换为灰度图 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # 使用高斯模糊减少噪声 blurred = cv2.GaussianBlur(gray, (9, 9), 0) # 使用霍夫圆变换检测圆 circles = cv2.HoughCircles(blurred, cv2.HOUGH_GRADIENT, dp=1, minDist=20, param1=50, param2=30, minRadius=0, maxRadius=70) # 初始化计数器 small_circle_count = 0 medium_circle_count = 0 # 确保至少找到一个圆 if circles is not None: circles = np.uint16(np.around(circles)) for i in circles[0, :]: if 0 <= i[2] < 40: # 小圆 cv2.circle(image, (i[0], i[1]), i[2], (255, 0, 255), 2) # 紫色框小圆 small_circle_count += 1 elif 40 <= i[2] <= 50: # 中圆 cv2.circle(image, (i[0], i[1]), i[2], (0, 255, 0), 2) # 红色框中圆 medium_circle_count += 1 # 显示结果和统计数量 print(f"Detected {small_circle_count} small circles.") print(f"Detected {medium_circle_count} medium circles.") cv2.imshow('Detected Circles', image) cv2.waitKey(0) cv2.destroyAllWindows()