43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
|
import cv2
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
def detect_circles(image_path):
|
||
|
|
# 读取图像
|
||
|
|
img = cv2.imread(image_path, cv2.IMREAD_COLOR)
|
||
|
|
|
||
|
|
# 将图像转换为灰度图
|
||
|
|
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
|
||
|
|
|
||
|
|
# 使用高斯模糊处理图像
|
||
|
|
blurred = cv2.GaussianBlur(gray, (9, 9), 2)
|
||
|
|
|
||
|
|
# 使用霍夫圆检测法检测圆圈
|
||
|
|
circles = cv2.HoughCircles(blurred, cv2.HOUGH_GRADIENT, dp=1.2, minDist=30,
|
||
|
|
param1=80, param2=38, minRadius=15, maxRadius=60)
|
||
|
|
|
||
|
|
# 确认至少检测到一个圆圈
|
||
|
|
if circles is not None:
|
||
|
|
circles = np.round(circles[0, :]).astype("int")
|
||
|
|
|
||
|
|
print(f"检测到 {len(circles)} 个圆圈")
|
||
|
|
for i, (x, y, r) in enumerate(circles, start=1): # 从1开始计数
|
||
|
|
# 在图像中绘制圆圈
|
||
|
|
cv2.circle(img, (x, y), r, (0, 255, 0), 4)
|
||
|
|
# 在图像中绘制圆心
|
||
|
|
cv2.circle(img, (x, y), 2, (0, 128, 255), 3)
|
||
|
|
# 在图像中绘制圆圈编号
|
||
|
|
cv2.putText(img, f'{i}', (x - 10, y + 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
|
||
|
|
|
||
|
|
# 显示结果图像并处理退出事件
|
||
|
|
while True:
|
||
|
|
cv2.imshow("detected circles", img)
|
||
|
|
key = cv2.waitKey(1) & 0xFF
|
||
|
|
if key == 27: # ESC键的ASCII码是27
|
||
|
|
break
|
||
|
|
|
||
|
|
cv2.destroyAllWindows()
|
||
|
|
else:
|
||
|
|
print("没有检测到圆圈")
|
||
|
|
|
||
|
|
# 调用函数并传递图像路径
|
||
|
|
detect_circles("image2.jpg")
|