Chapter 7 Color Detection

img = cv2.imread('images/lambo.png')

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

cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars", 640, 240)
cv2.createTrackbar('Hue Min', "TrackBars", 2, 179, lambda x:x)
cv2.createTrackbar('Hue Max', "TrackBars", 18, 180, lambda x:x)
cv2.createTrackbar('Sat Min', "TrackBars", 0, 255, lambda x:x)
cv2.createTrackbar('Sat Max', "TrackBars", 255, 255, lambda x:x)
cv2.createTrackbar('Value Min', "TrackBars", 51, 255, lambda x:x)
cv2.createTrackbar('Value Max', "TrackBars", 255, 255, lambda x:x)

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

while True:
    h_min = cv2.getTrackbarPos('Hue Min', "TrackBars")
    h_max = cv2.getTrackbarPos('Hue Max', "TrackBars")
    sat_min = cv2.getTrackbarPos('Sat Min', "TrackBars")
    sat_max = cv2.getTrackbarPos('Sat Max', "TrackBars")
    value_min = cv2.getTrackbarPos('Value Min', "TrackBars")
    value_max = cv2.getTrackbarPos('Value Max', "TrackBars")

    # 重点
    lower = np.array([h_min, sat_min, value_min])
    upper = np.array([h_max, sat_max, value_max])
    mask = cv2.inRange(imgHSV, lower, upper)
    # 想要识别的弄成白色，其他黑色
    print(h_min, h_max, sat_min, sat_max, value_min, value_max)
    # 就只留下mask的部分
    imgResult = cv2.bitwise_and(img, img, mask=mask)

    # cv2.imshow('mask', mask)
    imgStack = stackImages(0.5, [img, imgHSV, imgResult])
    cv2.imshow('imgStack', imgStack)
    cv2.waitKey(1)