```
import cv2
import numpy as np

圆检测算法

def detect(img):

# 定义红色、蓝色、白色的hsv区间文件
red1 = np.array([0, 100, 46])
red2 = np.array([8, 255, 255])

white1 = np.array([0, 0, 221])
white2 = np.array([180, 30, 255])

blue1 = np.array([100, 43, 46])
blue2 = np.array([124, 255, 255])
# 从rgb转到hsv颜色空间
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# 找到每个像素的值，得到对应的单色图像
mask_red = cv2.inRange(hsv, red1, red2)
mask_white = cv2.inRange(hsv, white1, white2)
mask_blue = cv2.inRange(hsv, blue1, blue2)

result_red = cv2.bitwise_and(img, img, mask=mask_red)
result_white = cv2.bitwise_and(img, img, mask=mask_white)
result_blue = cv2.bitwise_and(img, img, mask=mask_blue)

# 对图像进行灰度化
gray_red = cv2.cvtColor(result_red, cv2.COLOR_BGR2GRAY)
gray_white = cv2.cvtColor(result_white, cv2.COLOR_BGR2GRAY)
gray_blue = cv2.cvtColor(result_blue, cv2.COLOR_BGR2GRAY)
# 对灰度图像进行轮廓提取，更加面积，去除较大或较小面积，保存和圆相同的面积轮廓
_, contours, heridency = cv2.findContours(gray_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
_, contours2, heridency = cv2.findContours(gray_white, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# 定义绘制字体
font = cv2.FONT_HERSHEY_SIMPLEX
# 红色轮廓
for i in contours:
    # 计算轮廓面积
    area = cv2.contourArea(i)
    # 当面积在500-2000之间，才进行圆检测
    if 500 < area < 2000:
        circles_red = cv2.HoughCircles(gray_red, cv2.HOUGH_GRADIENT, 1,
                                       50, param1=150, param2=20, minRadius=5, maxRadius=14)
        # 若不为空，则进行绘制
        if circles_red is not None:
            circles_1 = np.uint16(np.around(circles_red))
            for i in circles_1[0, :]:
                cv2.circle(img, (i[0], i[1]), i[2], (0, 0, 255), 2)  # 画圆
                cv2.circle(img, (i[0], i[1]), 2, (0, 0, 255), 2)  # 画圆心
                cv2.putText(img, 'red', (i[0], i[1]), font, 0.8, (0, 0, 255), 2)
# 白色轮廓
for i in contours2:
    area = cv2.contourArea(i)
    if 350 < area < 1500:

        circles_white = cv2.HoughCircles(gray_white, cv2.HOUGH_GRADIENT, 1,
                        20, param1=35, param2=20, minRadius=0, maxRadius=30)

        if circles_white is not None:
            circles_2 = np.uint16(np.around(circles_white))
            for i in circles_2[0, :]:
                cv2.circle(img, (i[0], i[1]), i[2], (255, 255, 255), 2)  # 画圆
                cv2.circle(img, (i[0], i[1]), 2, (255, 255, 255), 2)  # 画圆心
                cv2.putText(img, 'white', (i[0], i[1]), font, 0.8, (255, 255, 255), 2)

# 因蓝色轮廓较少，所以不需要进行轮廓提取
circles_blue = cv2.HoughCircles(gray_blue, cv2.HOUGH_GRADIENT, 1,
                        50, param1=35, param2=20, minRadius=5, maxRadius=25)

if circles_blue is not None:
    circles_3 = np.uint16(np.around(circles_blue))
    for i in circles_3[0, :]:
        cv2.circle(img, (i[0], i[1]), i[2], (255, 0, 0), 2)  # 画圆
        cv2.circle(img, (i[0], i[1]), 2, (255, 0, 0), 2)  # 画圆心
        cv2.putText(img, 'blue', (i[0], i[1]), font, 0.8, (255, 0, 0), 2)

return img

cap = cv2.VideoCapture('demo/DSC_0001.MOV')

while(cap.isOpened()):
ret, frame = cap.read()
frame = cv2.resize(frame, (640, 480))
result = detect(frame)
cv2.imshow('frame', result)
if cv2.waitKey(25) & 0xFF == ord('q'):
break

cap.release()
cv2.destroyAllWindows()