Detecting colored circle and it's center using OpenCV

Question

I am trying to detect BLUE colored CIRCLE and it's CENTER. Then draw a circle on the detected circle and a very small circle on it's center. But I get a few errors. (I am using OpenCV 3.1.0, Python 2.7 Anaconda 64 bits, PyCharm as an IDE) (Please help me using python codes) I run the following code:

  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"

The error I get when I run the code is:

OpenCV Error: Assertion failed (depth == CV_8U || depth == CV_16U || depth == CV_32F) in cv::cvtColor, file C:\builds\master_PackSlaveAddon-win64-vc12-static\opencv\modules\imgproc\src\color.cpp, line 7935 Traceback (most recent call last): File "C:/Users/Meliodas/PycharmProjects/OpenCV_By_Examples/code_tester.py", line 11, in 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: error: (-215) depth == CV_8U || depth == CV_16U || depth == CV_32F in function cv::cvtColor Thanks a lot in advance for your help!

What is the type of frame_gau_blur? using frame_gau_blur.dtype — Amitay Nachmani
How do I check the data type of "frame_gau_blur"? I am very sorry, I am very new to numpy and python and computer vision too. @AmitayNachmani — Omee
it's data type "float 64" for frame_gau_blur.dtype @AmitayNachmani — Omee
You can see that the exception you get sais that you need one of the following: "depth == CV_8U || depth == CV_16U || depth == CV_32F" therefore try to do hsv = cv2.cvtColor(frame_gau_blur.astype(np.float32, cv2.COLOR_BGR2HSV) — Amitay Nachmani

Omee Omee · Accepted Answer · 2016-08-10T12:09:10

I have solved the my problem and after looking up the meanings of the errors online (the one's that I got), I was able to find the solutions for them and hence I was able to solve them. If you run the following code given below you should be able to detect blue circles pretty well. Thanks a lot to the people who tried to help me to solve my problem.

The code is given below:

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'

Detecting colored circle and it's center using OpenCV

2 Answers