class_docstr: An abstract class representing a face detector.
  
  Any other face detection implementation must subclass it. All subclasses
  must implement ``detect_from_image``, that return a list of detected
  bounding boxes. Optionally, for speed considerations detect from path is
  recommended.
code: def __init__(self, device, verbose):
      self.device = device
      self.verbose = verbose
  
      if verbose:
          if "cpu" in device:
              logger = logging.getLogger(__name__)
              logger.warning(
                  "Detection running on CPU, this may be potentially slow."
              )
  
      if (
          "cpu" not in device
          and "cuda" not in device
          and "mps" not in device
      ):
          if verbose:
              logger.error(
                  "Expected values for device are: {cpu, cuda, mps} but got: %s",
                  device,
              )
          raise ValueError
  
file_path: face-alignment/face_alignment/detection/core.py
imports: import logging
  import glob
  from tqdm import tqdm
  import numpy
  import torch
  from skimage import io
label_desc: Use image node_id 1 to create a new FaceDetector object from inherited base classes: object with example: obj = FaceDetector(device, verbose)