color_track.py

############################################################
####Program to Track/differentiate objects based on color###
####in HSV color space                                   ###
############################################################

import cv2 # opencv library
import numpy as np #linear algebra library

def nothing(x):
    pass

cap = cv2.VideoCapture(0); #Initiating camera. '0' refers to inbuilt/default camera.
                          #change number to switch camera


# Create trackbars
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')
    ret, frame = cap.read() #Read Camera

    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) #convert BGR to HSV

    #Threshold tuning with trackbars

    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) #mask output (binary)

    result = cv2.bitwise_and(frame, frame, mask=mask) #Thresholded output 
    
    #Display results
    cv2.imshow("frame", frame)
    cv2.imshow("mask", mask)
    cv2.imshow("result", result)

    key = cv2.waitKey(1)
    if key == 27:
        break

cap.release() # Terminate camera
cv2.destroyAllWindows() #close all windows