def __init__(self, cfg, parallel=False):
        """
        Args:
            cfg (CfgNode):
            parallel (bool) whether to run the model in different processes from visualization.:
                Useful since the visualization logic can be slow.
        """
        self.cfg = cfg
        self.parallel = parallel

        if parallel:
            self.num_gpus = torch.cuda.device_count()
            self.predictor = AsyncPredictor(cfg, self.num_gpus)
        else:
            self.predictor = DefaultPredictor(cfg)

        Args:
            cfg (CfgNode):
            parallel (bool) whether to run the model in different processes from visualization.:
                Useful since the visualization logic can be slow.
        
demo/predictor.py