code: def __init__(self, in_channels, model_name, **kwargs):
      super(EASTHead, self).__init__()
      self.model_name = model_name
      if self.model_name == "large":
          num_outputs = [128, 64, 1, 8]
      else:
          num_outputs = [64, 32, 1, 8]
  
      self.det_conv1 = ConvBNLayer(
          in_channels=in_channels,
          out_channels=num_outputs[0],
          kernel_size=3,
          stride=1,
          padding=1,
          if_act=True,
          act="relu",
          name="det_head1",
      )
      self.det_conv2 = ConvBNLayer(
          in_channels=num_outputs[0],
          out_channels=num_outputs[1],
          kernel_size=3,
          stride=1,
          padding=1,
          if_act=True,
          act="relu",
          name="det_head2",
      )
      self.score_conv = ConvBNLayer(
          in_channels=num_outputs[1],
          out_channels=num_outputs[2],
          kernel_size=1,
          stride=1,
          padding=0,
          if_act=False,
          act=None,
          name="f_score",
      )
      self.geo_conv = ConvBNLayer(
          in_channels=num_outputs[1],
          out_channels=num_outputs[3],
          kernel_size=1,
          stride=1,
          padding=0,
          if_act=False,
          act=None,
          name="f_geo",
      )
  
file_path: PaddleOCR/ppocr/modeling/heads/det_east_head.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  from paddle import nn
  import paddle.nn.functional
  from paddle import ParamAttr
label_desc: Use image node_id 1 to create a new EASTHead object from inherited base classes: nn with example: obj = EASTHead(in_channels, model_name)