code: def detect_from_image(self, tensor_or_path):
      image = self.tensor_or_path_to_ndarray(tensor_or_path)
  
      image_size = 256 if self.back_model else 128
      bboxlist = detect(
          self.face_detector,
          image,
          target_size=image_size,
          device=self.device,
      )[0]
  
      return bboxlist
  
file_path: face-alignment/face_alignment/detection/blazeface/blazeface_detector.py
imports: from torch.utils.model_zoo import load_url
  from ..core import FaceDetector
  from ...utils import load_file_from_url
  from .net_blazeface import BlazeFace
  from .detect import *
label_desc: Use image node_id 2 for calling the BlazeFaceDetector obj's underlying member method code with example usage: obj.detect_from_image(tensor_or_path) and returns: bboxlist