def predict(self, repeats=1):
        '''
        Args:
            repeats (int): repeats number for prediction
        Returns:
            result (dict): include 'bboxes', 'cts' and 'tracking':
                np.ndarray: shape:[N,6],[N,2] and [N,2], N: number of box
        '''
        # model prediction
        np_bboxes, np_cts, np_tracking = None, None, None
        for i in range(repeats):
            self.predictor.run()
            output_names = self.predictor.get_output_names()
            bboxes_tensor = self.predictor.get_output_handle(output_names[0])
            np_bboxes = bboxes_tensor.copy_to_cpu()
            cts_tensor = self.predictor.get_output_handle(output_names[1])
            np_cts = cts_tensor.copy_to_cpu()
            tracking_tensor = self.predictor.get_output_handle(output_names[2])
            np_tracking = tracking_tensor.copy_to_cpu()

        result = dict(bboxes=np_bboxes, cts=np_cts, tracking=np_tracking)
        return result

        Args:
            repeats (int): repeats number for prediction
        Returns:
            result (dict): include 'bboxes', 'cts' and 'tracking':
                np.ndarray: shape:[N,6],[N,2] and [N,2], N: number of box
        
deploy/python/mot_centertrack_infer.py