Computer vision: Object Detection and Object Tracking Using HSV Color Space 




import cv2

import numpy as np


def nothing(x):

    pass    


cv2.namedWindow("Tracking")

cv2.createTrackbar("LH", "Tracking", 0, 255, nothing)

cv2.createTrackbar("LS", "Tracking", 0, 255, nothing)

cv2.createTrackbar("LV", "Tracking", 0, 255, nothing)

cv2.createTrackbar("UH", "Tracking", 255, 255, nothing)

cv2.createTrackbar("US", "Tracking", 255, 255, nothing)

cv2.createTrackbar("UV", "Tracking", 255, 255, nothing)


while True:

    frame = cv2.imread('smarties.png')      


    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)       


    l_h = cv2.getTrackbarPos("LH", "Tracking")       

    l_s = cv2.getTrackbarPos("LS", "Tracking")       

    l_v = cv2.getTrackbarPos("LV", "Tracking")       


    u_h = cv2.getTrackbarPos("UH", "Tracking")       

    u_s = cv2.getTrackbarPos("US", "Tracking")       

    u_v = cv2.getTrackbarPos("UV", "Tracking")       


    l_b = np.array([l_h, l_s, l_v])       

    u_b = np.array([u_h, u_s, u_v])       


    mask = cv2.inRange(hsv, l_b, u_b)       


    res = cv2.bitwise_and(frame, frame, mask=mask)        


    cv2.imshow("frame", frame)        

    cv2.imshow("mask", mask)        

    cv2.imshow("res", res)        


    key = cv2.waitKey(1)         

    if key == 27:        

        break               


cv2.destroyAllWindows() #colse window

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data used in this video



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