Example script using the Vision bonnet to detect faces in the camera frame and write the number of faces to a file.

face_detection_camera_with_file.py

#!/usr/bin/env python

import argparse

from aiy.vision.inference import CameraInference
from aiy.vision.models import face_detection
from examples.vision.annotator import Annotator
from picamera import PiCamera


def main():
  parser = argparse.ArgumentParser()
  parser.add_argument(
      '--num_frames',
      '-n',
      type=int,
      dest='num_frames',
      default=-1,
      help='Sets the number of frames to run for, otherwise runs forever.')
  args = parser.parse_args()

  with PiCamera() as camera:
    camera.sensor_mode = 4
    camera.resolution = (1640, 1232)
    camera.framerate = 30
    camera.start_preview()

    annotator = Annotator(camera, dimensions=(320, 240))
    scale_x = 320 / 1640
    scale_y = 240 / 1232

    def transform(bounding_box):
      x, y, width, height = bounding_box
      return (scale_x * x, scale_y * y, scale_x * (x + width),
              scale_y * (y + height))

    with CameraInference(face_detection.model()) as inference:
      for i, result in enumerate(inference.run()):
        if i == args.num_frames:
          break
        faces = face_detection.get_faces(result)
        annotator.clear()
        for face in faces:
          annotator.bounding_box(transform(face.bounding_box), fill=0)
        annotator.update()
        file = open("/home/pi/www/face_count.txt","w") 
        file.write('%d' % len(faces))
        print('Iteration #%d: num_faces=%d' % (i, len(faces)))
        file.close()

    camera.stop_preview()

if __name__ == '__main__':
  main()