Python opencv进行圆形识别(圆检测)实例代码

img = cv2.imread("save1.jpg", 0)     # 0或者cv2.IMREAD_GRAYSCALE  读取为灰度图像
img2 = cv2.imread("save1.jpg", 1)     # 1或者cv2.IMREAD_COLOR 读取为为彩色图像

size = 400
x1 = 560
y1 = 200
x2 = x1+size
y2 = y1+size
cut = img[y1:y2, x1:x2]

numpy_img = cv2.adaptiveThreshold(cut, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 15)   # 自动阈值二值化

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

#                                                      圆心距 canny阈值    投票数      最小半径       最大半径
circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 170,   param1=100, param2=60,  minRadius=60, maxRadius=90)

arr1 = np.zeros([0, 2], dtype=int)                      # 创建一个0行, 2列的空数组
if circles is not None:
    circles = np.uint16(np.around(circles))   # 4舍5入, 然后转为uint16
    for i in circles[0, :]:
        arr1 = np.append(arr1, (i[0], i[1]))            # arr1是圆心坐标的np数组
        # print(arr1)
        cv2.circle(img2, (i[0], i[1]), i[2], (0, 0, 255), 3)  # 轮廓
        cv2.circle(img2, (i[0], i[1]), 2, (0, 0, 0), 6)     # 圆心