class_docstr: Metric that calculates the mean Dice metric for each class.
  
  See more: https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient
  
  Parameters
  ----------
  threshold: float, default: 0.5
      prediction value per pixel above which the pixel is considered True.
  smooth: float, default: 1e-3
      smoothing factor to prevent division by zero when the mask is empty.
  average: str, default: none
      The method for averaging over the classes. If none, returns the result per class.
class_docstr_tok: ["Metric","that","calculates","the","mean","Dice","metric","for","each","class",".","See","more",":","https",":","\/\/en.wikipedia.org\/wiki\/S","%","C3","%","B8rensen","%","E2","%","80","%","93Dice_coefficient","Parameters","--","--","--","--","--","threshold",":","float",",","default",":","0.5","prediction","value","per","pixel","above","which","the","pixel","is","considered","True",".","smooth",":","float",",","default",":","1e-3","smoothing","factor","to","prevent","division","by","zero","when","the","mask","is","empty",".","average",":","str",",","default",":","none","The","method","for","averaging","over","the","classes",".","If","none",",","returns","the","result","per","class","."]
docstr: Reset metric state.
docstr_tok: ["Reset","metric","state","."]
code: def reset(self) -> None:
      """Reset metric state."""
      super().reset()
      self._evals = defaultdict(lambda: {"dice": 0, "count": 0})
  
file_path: deepchecks/deepchecks/vision/metrics_utils/semantic_segmentation_metrics.py
imports: from collections import defaultdict
  from typing import Tuple
  import numpy
  import torch
  from ignite.metrics import Metric
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.vision.metrics_utils.semantic_segmentation_metric_utils import format_segmentation_masks, segmentation_counts_micro, segmentation_counts_per_class
label_desc: Use image node_id 2 for calling the MeanDice obj's underlying member method code with example usage: obj.reset() without return types