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]*rowshor_con = [imageBlank]*rowsfor 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 = horreturn vercv2.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)
