parser.add_argument('--sort_min_hit', default=3, type=int)
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
Detector = SSD(args.gpu_id, args.model_def, args.model_weights,
args.image_resize, args.labelmap_file)
mot_tracker = Sort(args.sort_max_age, args.sort_min_hit)
seqDir = args.seq_dir
images = os.listdir(seqDir)
images.sort(key=str.lower)
colours = np.random.rand(32, 3) * 255
for image_name in images:
image_path = os.path.join(seqDir, image_name)
result = Detector.detect(image_path, args.det_conf_thresh)
im = cv2.imread(image_path)
height = im.shape[0]
width = im.shape[1]
result = np.array(result)
det = result[:, 0:5]
det[:, 0] = det[:, 0] * width
det[:, 1] = det[:, 1] * height
det[:, 2] = det[:, 2] * width
det[:, 3] = det[:, 3] * height
trackers = mot_tracker.update(det)
for d in trackers:
xmin = int(d[0])
ymin = int(d[1])
xmax = int(d[2])
ymax = int(d[3])
