class_docstr: Tracker for MaskTrack R-CNN.
  
  Args:
      match_weights (dict[str : float]): The Weighting factor when computing
      the match score. It contains keys as follows:
  
          - det_score (float): The coefficient of `det_score` when computing
              match score.
          - iou (float): The coefficient of `ious` when computing match
              score.
          - det_label (float): The coefficient of `label_deltas` when
              computing match score.
class_docstr_tok: ["Tracker","for","MaskTrack","R-CNN",".","Args",":","match_weights","(","dict","[","str",":","float","]",")",":","The","Weighting","factor","when","computing","the","match","score",".","It","contains","keys","as","follows",":","-","det_score","(","float",")",":","The","coefficient","of","`","det_score","`","when","computing","match","score",".","-","iou","(","float",")",":","The","coefficient","of","`","ious","`","when","computing","match","score",".","-","det_label","(","float",")",":","The","coefficient","of","`","label_deltas","`","when","computing","match","score","."]
code: def __init__(
      self,
      match_weights: dict = dict(
          det_score=1.0, iou=2.0, det_label=10.0
      ),
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.match_weights = match_weights
  
file_path: mmdetection/mmdet/models/trackers/masktrack_rcnn_tracker.py
imports: from typing import List
  import torch
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures import DetDataSample
  from mmdet.structures.bbox import bbox_overlaps
  from .base_tracker import BaseTracker
label_desc: Use image node_id 1 to create a new MaskTrackRCNNTracker object from inherited base classes: BaseTracker with example: obj = MaskTrackRCNNTracker(match_weights)