class_docstr: Asynchronous Action Prediction and Visualization pipeline with AsyncVis.
class_docstr_tok: ["Asynchronous","Action","Prediction","and","Visualization","pipeline","with","AsyncVis","."]
docstr: Put task into task queue for prediction and visualization.
  Args:
      task (TaskInfo object): task object that contain
          the necessary information for action prediction. (e.g. frames)
docstr_tok: ["Put","task","into","task","queue","for","prediction","and","visualization",".","Args",":","task","(","TaskInfo","object",")",":","task","object","that","contain","the","necessary","information","for","action","prediction",".","(","e.g",".","frames",")"]
code: def put(self, task):
      """
      Put task into task queue for prediction and visualization.
      Args:
          task (TaskInfo object): task object that contain
              the necessary information for action prediction. (e.g. frames)
      """
      self.async_vis.get_indices_ls.append(task.id)
      self.model.put(task)
  
imports: import atexit
  import numpy
  import queue
  import torch
  import torch.multiprocessing
  import slowfast.utils.logging
  from slowfast.datasets import cv2_transform
  from slowfast.visualization.predictor import Predictor
label_desc: Use image node_id 2 for calling the AsyncDemo obj's underlying member method code with example usage: obj.put(task) without return types