class_docstr: SF3D Detector.
      
class_docstr_tok: ["SF3D","Detector","."]
code: def __init__(
      self,
      device,
      path_to_detector=None,
      verbose=False,
      filter_threshold=0.5,
  ):
      super(SFDDetector, self).__init__(device, verbose)
  
      # Initialise the face detector
      if path_to_detector is None:
          model_weights = load_url(models_urls["s3fd"])
      else:
          model_weights = torch.load(path_to_detector)
  
      self.fiter_threshold = filter_threshold
      self.face_detector = s3fd()
      self.face_detector.load_state_dict(model_weights)
      self.face_detector.to(device)
      self.face_detector.eval()
  
file_path: face-alignment/face_alignment/detection/sfd/sfd_detector.py
imports: import torch
  from torch.utils.model_zoo import load_url
  from ..core import FaceDetector
  from .net_s3fd import s3fd
  from .bbox import nms
  from .detect import detect, batch_detect
label_desc: Use image node_id 1 to create a new SFDDetector object from inherited base classes: FaceDetector with example: obj = SFDDetector(device, path_to_detector, verbose, filter_threshold)