find_faces.py

# This is a modified version of the find_faces code in DLIB, by Davis King
# The original version is here:
#  https://github.com/davisking/dlib/blob/master/python_examples/face_recognition.py

import dlib
from PIL import Image

def find_faces(face_file_path):
  # Load all the models we need: a detector to find the faces, a shape predictor
  # to find face landmarks so we can precisely localize the face
  detector = dlib.get_frontal_face_detector()
  sp = dlib.shape_predictor("/content/shape_predictor_5_face_landmarks.dat")

  # Load the image using Dlib
  img = dlib.load_rgb_image(face_file_path)

  # Ask the detector to find the bounding boxes of each face. The 1 in the
  # second argument indicates that we should upsample the image 1 time. This
  # will make everything bigger and allow us to detect more faces.
  dets = detector(img, 1)
  images = []

  num_faces = len(dets)
  if num_faces > 0:
    # Find the 5 face landmarks we need to do the alignment.
    faces = dlib.full_object_detections()
    # print("len(faces)", len(faces))
    for detection in dets:
      area = detection.area()
      if detection.area() > min_area:
        faces.append(sp(img, detection))

    # Get the aligned face images
    if len(faces) > 0:
      images = dlib.get_face_chips(img, faces, size=512, padding=1.25)
  return images