class_docstr: Load WiderFace records with 'anno_path'
  
  Args:
      dataset_dir (str): root directory for dataset.
      image_dir (str): directory for images.
      anno_path (str): WiderFace annotation data.
      data_fields (list): key name of data dictionary, at least have 'image'.
      sample_num (int): number of samples to load, -1 means all.
      with_lmk (bool): whether to load face landmark keypoint labels.
class_docstr_tok: ["Load","WiderFace","records","with","'anno_path'","Args",":","dataset_dir","(","str",")",":","root","directory","for","dataset",".","image_dir","(","str",")",":","directory","for","images",".","anno_path","(","str",")",":","WiderFace","annotation","data",".","data_fields","(","list",")",":","key","name","of","data","dictionary",",","at","least","have","'image","'",".","sample_num","(","int",")",":","number","of","samples","to","load",",","-1","means","all",".","with_lmk","(","bool",")",":","whether","to","load","face","landmark","keypoint","labels","."]
code: def __init__(
      self,
      dataset_dir=None,
      image_dir=None,
      anno_path=None,
      data_fields=["image"],
      sample_num=-1,
      with_lmk=False,
  ):
      super(WIDERFaceDataSet, self).__init__(
          dataset_dir=dataset_dir,
          image_dir=image_dir,
          anno_path=anno_path,
          data_fields=data_fields,
          sample_num=sample_num,
          with_lmk=with_lmk,
      )
      self.anno_path = anno_path
      self.sample_num = sample_num
      self.roidbs = None
      self.cname2cid = None
      self.with_lmk = with_lmk
  
file_path: PaddleDetection/ppdet/data/source/widerface.py
imports: import os
  import numpy
  from ppdet.core.workspace import register, serializable
  from .dataset import DetDataset
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 1 to create a new WIDERFaceDataSet object from inherited base classes: DetDataset with example: obj = WIDERFaceDataSet(dataset_dir, image_dir, anno_path, data_fields, sample_num, with_lmk)