RedBallTracker.py

# RedBallTracker.py

import cv2
import numpy as np
import os

###################################################################################################
def main():

    capWebcam = cv2.VideoCapture(0)                     # declare a VideoCapture object and associate to webcam, 0 => use 1st webcam

    if capWebcam.isOpened() == False:                           # check if VideoCapture object was associated to webcam successfully
        print "error: capWebcam not accessed successfully\n\n"          # if not, print error message to std out
        os.system("pause")                                              # pause until user presses a key so user can see error message
        return                                                          # and exit function (which exits program)

    while cv2.waitKey(1) != 27 and capWebcam.isOpened():                # until the Esc key is pressed or webcam connection is lost
        blnFrameReadSuccessfully, imgOriginal = capWebcam.read()            # read next frame

        if not blnFrameReadSuccessfully or imgOriginal is None:             # if frame was not read successfully
            print "error: frame not read from webcam\n"                     # print error message to std out
            os.system("pause")                                              # pause until user presses a key so user can see error message
            break                                                           # exit while loop (which exits program)

        imgProcessed = cv2.GaussianBlur(imgOriginal, (5, 5), 2)                 # blur

        imgProcessed = cv2.inRange(imgProcessed, (0, 0, 175), (100, 100, 256))      # filter on color

        imgProcessed = cv2.GaussianBlur(imgProcessed, (5, 5), 2)                # blur again

        imgProcessed = cv2.dilate(imgProcessed, np.ones((5,5),np.uint8))        # close image (dilate, then erode)
        imgProcessed = cv2.erode(imgProcessed, np.ones((5,5),np.uint8))         # closing "closes" (i.e. fills in) foreground gaps

        intRows, intColumns = imgProcessed.shape        # break out number of rows and columns in the image, rows is used for minimum distance between circles in call to Hough Circles

        circles = cv2.HoughCircles(imgProcessed, cv2.cv.CV_HOUGH_GRADIENT, 2, intRows / 4)      # fill variable circles with all circles in the processed image

        if circles is not None:                     # this line is necessary to keep program from crashing on next line if no circles were found
            for circle in circles[0]:                           # for each circle
                x, y, radius = circle                                                                       # break out x, y, and radius
                print "ball position x = " + str(x) + ", y = " + str(y) + ", radius = " + str(radius)       # print ball position and radius
                cv2.circle(imgOriginal, (x, y), 3, (0, 255, 0), cv2.cv.CV_FILLED)           # draw small green circle at center of detected object
                cv2.circle(imgOriginal, (x, y), radius, (0, 0, 255), 3)                     # draw red circle around the detected object
            # end for
        # end if

        cv2.namedWindow("Original", cv2.WINDOW_AUTOSIZE)            # create windows, use WINDOW_AUTOSIZE for a fixed window size
        cv2.namedWindow("Processed", cv2.WINDOW_AUTOSIZE)           # or use WINDOW_NORMAL to allow window resizing

        cv2.imshow("Original", imgOriginal)                 # show windows
        cv2.imshow("Processed", imgProcessed)
    # end while

    cv2.destroyAllWindows()                     # remove windows from memory

    return

###################################################################################################
if __name__ == "__main__":
    main()