Detect Faces with AWS Rekognition

detect_faces.py

#!/usr/bin/env python3
"""Upload all images and index faces with AWS Rekognition"""

import boto3
import csv
import logging
from os.path import split, splitext
from botocore.exceptions import ClientError

def search_faces(collection, files, outfname):
    outfile = open(outfname, 'w')
    outcsv = csv.writer(outfile)
    client = boto3.client('rekognition')
    for fname in files:
        logging.info('Searching %s', fname)
        mainname = splitext(split(fname)[-1])[0]
        image_data = open(fname, 'rb').read()
        try:
            response = client.search_faces_by_image(
                Image={
                    'Bytes': image_data
                },
                CollectionId=collection,
                MaxFaces=20
            )
            logging.debug("Resp = %s", response)
        except ClientError:
            logging.info("No face was found, skip")
            continue
        for matchdict in response['FaceMatches']:
            facedict = matchdict['Face']
            name, sourceid = facedict['ExternalImageId'].split('_')
            top = facedict['BoundingBox']['Top']
            left = facedict['BoundingBox']['Left']
            height = facedict['BoundingBox']['Height']
            width = facedict['BoundingBox']['Width']
            outcsv.writerow([mainname, name, sourceid, top, left, height, width])
    outfile.close()

def main():
    from glob import glob
    images = glob('full_hd.jpg')
    images.sort()
    search_faces('twice', images, 'twice_likey_test.csv')

if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    main()