code: def __init__(
      self, args, device, distributed: bool = False, local_rank: int = 0
  ):
      super(SegDetectorModel, self).__init__()
      # from decoders.seg_detector_loss import SegDetectorLossBuilder
      from ..decoders.seg_detector_loss import SegDetectorLossBuilder
  
      self.model = BasicModel(args)
      # for loading models
      self.model = parallelize(self.model, distributed, local_rank)
      self.criterion = SegDetectorLossBuilder(
          args["loss_class"],
          *args.get("loss_args", []),
          **args.get("loss_kwargs", {}),
      ).build()
      self.criterion = parallelize(
          self.criterion, distributed, local_rank
      )
      self.device = device
      self.to(self.device)
  
file_path: EasyOCR/easyocr/DBNet/model/model.py
imports: import os
  import torch
  import torch.nn
  import torch.nn.functional
  from ..None import backbones
  from ..None import decoders
label_desc: Use image node_id 1 to create a new SegDetectorModel object from inherited base classes: nn with example: obj = SegDetectorModel(args, device, distributed, local_rank)