使用 OpenCV 检测彩色圆圈及其中心

Question

我正在尝试检测蓝色圆圈并且它是中心。然后在检测到的圆圈上画一个圆圈，在它的中心画一个非常小的圆圈。但我得到了一些错误。 （我使用 OpenCV 3.1.0，Python 2.7 Anaconda 64 位，PyCharm 作为 IDE）（请帮助我使用 python 代码） 我运行以下代码：

  import cv2
    import numpy as np
    
    cap = cv2.VideoCapture(0)
    if cap.isOpened():
        while(True):
            frame, _ = cap.read()
            # blurring the frame that's captured
            frame_gau_blur = cv2.GaussianBlur(frame, (3, 3), 0)
            # converting BGR to HSV
            hsv = cv2.cvtColor(frame_gau_blur, cv2.COLOR_BGR2HSV)
            # the range of blue color in HSV
            lower_blue = np.array([110, 50, 50])
            higher_blue = np.array([130, 255, 255])
            # getting the range of blue color in frame
            blue_range = cv2.inRange(hsv, lower_blue, higher_blue)
            # getting the V channel which is the gray channel
            blue_s_gray = blue_range[::2]
            # applying HoughCircles
            circles = cv2.HoughCircles(blue_s_gray, cv2.HOUGH_GRADIENT, 1, 10, 100, 30, 5, 50)
            circles = np.uint16(np.around(circles))
            for i in circles[0,:]:
                # drawing on detected circle and its center
                cv2.circle(frame,(i[0],i[1]),i[2],(0,255,0),2)
                cv2.circle(frame,(i[0],i[1]),2,(0,0,255),3)
            cv2.imshow('circles', frame)
            k = cv2.waitKey(5) & 0xFF
            if k == 27:
                break
        cv2.destroyAllWindows()
    else:
        print "Can't find camera"

我运行代码时遇到的错误是：

OpenCV 错误：在 cv::cvtColor、文件 C:\builds\master_PackSlaveAddon-win64-vc12-static\opencv 中断言失败（深度 == CV_8U || 深度 == CV_16U || 深度 == CV_32F） \modules\imgproc\src\color.cpp，第 7935 行 回溯（最近一次通话最后）： 文件“C:/Users/Meliodas/PycharmProjects/OpenCV_By_Examples/code_tester.py”，第 11 行，在 hsv = cv2.cvtColor(frame_gau_blur, cv2.COLOR_BGR2HSV) cv2.error: C:\builds\master_PackSlaveAddon-win64-vc12-static\opencv\modules\imgproc\src\color.cpp:7935: 错误: (-215) depth == CV_8U ||深度 == CV_16U ||函数 cv::cvtColor 中的深度 == CV_32F 非常感谢您的帮助！

Answer 1

将frame, _ = cap.read() 更改为ret,frame = cap.read()

import cv2
import numpy as np

cap = cv2.VideoCapture(0)
if cap.isOpened():
while(True):
    ret,frame= cap.read()
    # blurring the frame that's captured
    frame_gau_blur = cv2.GaussianBlur(frame, (3, 3), 0)
    # converting BGR to HSV
    hsv = cv2.cvtColor(frame_gau_blur, cv2.COLOR_BGR2HSV)
    # the range of blue color in HSV
    lower_blue = np.array([110, 50, 50])
    higher_blue = np.array([130, 255, 255])
    # getting the range of blue color in frame
    blue_range = cv2.inRange(hsv, lower_blue, higher_blue)
    # getting the V channel which is the gray channel
    blue_s_gray = blue_range[::2]
    # applying HoughCircles
    circles = cv2.HoughCircles(blue_s_gray, cv2.HOUGH_GRADIENT, 1, 10, 100, 30, 5, 50)
    circles = np.uint16(np.around(circles))
    for i in circles[0,:]:
        # drawing on detected circle and its center
        cv2.circle(frame,(i[0],i[1]),i[2],(0,255,0),2)
        cv2.circle(frame,(i[0],i[1]),2,(0,0,255),3)
    cv2.imshow('circles', frame)
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break
cv2.destroyAllWindows()

Answer 2

我已经解决了我的问题，并且在网上查找了错误的含义（我得到的那个）之后，我能够找到它们的解决方案，因此我能够解决它们。如果您运行下面给出的以下代码，您应该能够很好地检测到蓝色圆圈。非常感谢那些试图帮助我解决我的问题的人。

代码如下：

import cv2
import numpy as np

cap = cv2.VideoCapture(0)
if cap.isOpened():
    while(True):
        ret, frame = cap.read()
        # blurring the frame that's captured
        frame_gau_blur = cv2.GaussianBlur(frame, (3, 3), 0)
        # converting BGR to HSV
        hsv = cv2.cvtColor(frame_gau_blur, cv2.COLOR_BGR2HSV)
        # the range of blue color in HSV
        lower_blue = np.array([110, 50, 50])
        higher_blue = np.array([130, 255, 255])
        # getting the range of blue color in frame
        blue_range = cv2.inRange(hsv, lower_blue, higher_blue)
        res_blue = cv2.bitwise_and(frame_gau_blur,frame_gau_blur, mask=blue_range)
        blue_s_gray = cv2.cvtColor(res_blue, cv2.COLOR_BGR2GRAY)
        canny_edge = cv2.Canny(blue_s_gray, 50, 240)
        # applying HoughCircles
        circles = cv2.HoughCircles(canny_edge, cv2.HOUGH_GRADIENT, dp=1, minDist=10, param1=10, param2=20, minRadius=100, maxRadius=120)
        cir_cen = []
        if circles != None:
            # circles = np.uint16(np.around(circles))
            for i in circles[0,:]:
                # drawing on detected circle and its center
                cv2.circle(frame,(i[0],i[1]),i[2],(0,255,0),2)
                cv2.circle(frame,(i[0],i[1]),2,(0,0,255),3)
                cir_cen.append((i[0],i[1]))
        print cir_cen
        cv2.imshow('circles', frame)
        cv2.imshow('gray', blue_s_gray)
        cv2.imshow('canny', canny_edge)
        k = cv2.waitKey(5) & 0xFF
        if k == 27:
            break
    cv2.destroyAllWindows()
else:
    print 'no cam'