docstr: YOLOv3 network, see https://arxiv.org/abs/1804.02767
  
  Args:
      backbone (nn.Layer): backbone instance
      neck (nn.Layer): neck instance
      yolo_head (nn.Layer): anchor_head instance
      bbox_post_process (object): `BBoxPostProcess` instance
      data_format (str): data format, NCHW or NHWC
      for_mot (bool): whether return other features for multi-object tracking
          models, default False in pure object detection models.
docstr_tok: ["YOLOv3","network",",","see","https",":","\/\/arxiv.org\/abs\/1804.02767","Args",":","backbone","(","nn.Layer",")",":","backbone","instance","neck","(","nn.Layer",")",":","neck","instance","yolo_head","(","nn.Layer",")",":","anchor_head","instance","bbox_post_process","(","object",")",":","`","BBoxPostProcess","`","instance","data_format","(","str",")",":","data","format",",","NCHW","or","NHWC","for_mot","(","bool",")",":","whether","return","other","features","for","multi-object","tracking","models",",","default","False","in","pure","object","detection","models","."]
code: def __init__(
      self,
      backbone="DarkNet",
      neck="YOLOv3FPN",
      yolo_head="YOLOv3Head",
      post_process="BBoxPostProcess",
      data_format="NCHW",
      for_mot=False,
  ):
      """
      YOLOv3 network, see https://arxiv.org/abs/1804.02767
  
      Args:
          backbone (nn.Layer): backbone instance
          neck (nn.Layer): neck instance
          yolo_head (nn.Layer): anchor_head instance
          bbox_post_process (object): `BBoxPostProcess` instance
          data_format (str): data format, NCHW or NHWC
          for_mot (bool): whether return other features for multi-object tracking
              models, default False in pure object detection models.
      """
      super(YOLOv3, self).__init__(data_format=data_format)
      self.backbone = backbone
      self.neck = neck
      self.yolo_head = yolo_head
      self.post_process = post_process
      self.for_mot = for_mot
      self.return_idx = isinstance(post_process, JDEBBoxPostProcess)
  
file_path: PaddleDetection/ppdet/modeling/architectures/yolo.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
  from ..post_process import JDEBBoxPostProcess
label_desc: Use image node_id 1 to create a new YOLOv3 object from inherited base classes: BaseArch with example: obj = YOLOv3(backbone, neck, yolo_head, post_process, data_format, for_mot)