Detecting Colors in Open CV

detect_colors.py

import cv2
    import numpy as np
    '''
    Here we will try to detect colors in the image 
    '''
    def empty(a):
        pass
        # Function used to stack the images


    def stackImages(scale, imgArray):
        rows = len(imgArray)
        cols = len(imgArray[0])
        rowsAvailable = isinstance(imgArray[0], list)
        width = imgArray[0][0].shape[1]
        height = imgArray[0][0].shape[0]
        if rowsAvailable:
            for x in range(0, rows):
                for y in range(0, cols):
                    if imgArray[x][y].shape[:2] == imgArray[0][0].shape[:2]:
                        imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
                    else:
                        imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]),
                                                    None, scale, scale)
                    if len(imgArray[x][y].shape) == 2: imgArray[x][y] = cv2.cvtColor(imgArray[x][y], cv2.COLOR_GRAY2BGR)
            imageBlank = np.zeros((height, width, 3), np.uint8)
            hor = [imageBlank] * rows
            hor_con = [imageBlank] * rows
            for x in range(0, rows):
                hor[x] = np.hstack(imgArray[x])
            ver = np.vstack(hor)
        else:
            for x in range(0, rows):
                if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
                    imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
                else:
                    imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None, scale,
                                             scale)
                if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
            hor = np.hstack(imgArray)
            ver = hor
        return ver

    path = 'Resources/lambo.png'
    cv2.namedWindow("TrackBars")
    cv2.resizeWindow("TrackBars", 640, 240)
    cv2.createTrackbar("Hue Min", "TrackBars", 0, 179, empty)
    cv2.createTrackbar("Hue Max", "TrackBars", 19, 179, empty)
    cv2.createTrackbar("Sat Min", "TrackBars", 110, 255, empty)
    cv2.createTrackbar("Sat Max", "TrackBars", 240, 255, empty)
    cv2.createTrackbar("Val Min", "TrackBars", 153, 255, empty)
    cv2.createTrackbar("Val Max", "TrackBars", 255, 255, empty)
    while True:
        img = cv2.imread(path)
        #cv2.imshow("Original", img)

        imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
        #cv2.imshow("HSV",imgHSV)

        h_min = cv2.getTrackbarPos("Hue Min", "TrackBars")
        h_max = cv2.getTrackbarPos("Hue Max", "TrackBars")
        s_min = cv2.getTrackbarPos("Sat Min", "TrackBars")
        s_max = cv2.getTrackbarPos("Sat Max", "TrackBars")
        v_min = cv2.getTrackbarPos("Val Min", "TrackBars")
        v_max = cv2.getTrackbarPos("Val Max", "TrackBars")
        print(h_min, h_max, s_min, s_max, v_min, v_max)
        lower = np.array([h_min, s_min, v_min])
        upper = np.array([h_max, s_max, v_max])
        mask = cv2.inRange(imgHSV, lower, upper)
        #cv2.imshow("Mask",mask)

        imgResult = cv2.bitwise_and(img, img, mask=mask)
        #cv2.imshow("Image Result",imgResult)

        # Instead of displaying all image seprate we can stack them up in single window
        imgStack = stackImages(0.6,([img,imgHSV],[mask,imgResult]))
        cv2.imshow("Result", imgStack)
        cv2.waitKey(200)