class_docstr: This module implements the task- and model-specific estimator for PyTorch GOTURN (object tracking).
class_docstr_tok: ["This","module","implements","the","task-","and","model-specific","estimator","for","PyTorch","GOTURN","(","object","tracking",")","."]
docstr: Method `init` for GOT-10k trackers.
  
  :param image: Current image.
  :return: Predicted box.
docstr_tok: ["Method","`","init","`","for","GOT-10k","trackers",".",":","param","image",":","Current","image",".",":","return",":","Predicted","box","."]
code: def init(
      self, image: "PIL.JpegImagePlugin.JpegImageFile", box: np.ndarray
  ):
      """
      Method `init` for GOT-10k trackers.
  
      :param image: Current image.
      :return: Predicted box.
      """
      import torch
  
      self.prev = np.array(image) / 255.0
      if self.clip_values is not None:
          self.prev = self.prev * self.clip_values[1]
      self.box = torch.from_numpy(
          np.array([box[0], box[1], box[2] + box[0], box[3] + box[1]])
      ).to(self.device)
  
imports: import logging
  import time
  from typing import List, Dict, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from art.estimators.object_tracking.object_tracker import ObjectTrackerMixin
  from art.estimators.pytorch import PyTorchEstimator
label_desc: Use image node_id 15 for calling the PyTorchGoturn obj's underlying member method code with example usage: obj.init(image, box) without return types