class_docstr: Extract RoI features from a single level feature map.
  
  If there are multiple input feature levels, each RoI is mapped to a level
  according to its scale. The mapping rule is proposed in
  `FPN <https://arxiv.org/abs/1612.03144>`_.
  
  Args:
      roi_layer (dict): Specify RoI layer type and arguments.
      out_channels (int): Output channels of RoI layers.
      featmap_strides (int): Strides of input feature maps.
      finest_scale (int): Scale threshold of mapping to level 0. Default: 56.
code: def __init__(
      self, roi_layer, out_channels, featmap_strides, finest_scale=56
  ):
      super(SingleRoIExtractor, self).__init__(
          roi_layer, out_channels, featmap_strides
      )
      self.finest_scale = finest_scale
  
file_path: insightface/detection/scrfd/mmdet/models/roi_heads/roi_extractors/single_level_roi_extractor.py
imports: import torch
  from mmcv.runner import force_fp32
  from mmdet.models.builder import ROI_EXTRACTORS
  from .base_roi_extractor import BaseRoIExtractor
label_desc: Use image node_id 1 to create a new SingleRoIExtractor object from inherited base classes: BaseRoIExtractor with example: obj = SingleRoIExtractor(roi_layer, out_channels, featmap_strides, finest_scale)