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 usin

Answer 1

Change frame, _ = cap.read() to 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

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'