compare_image.py

# -*- coding: utf-8 -*-
from __future__ import print_function
import os
import re
import scipy.misc
import warnings
import face_recognition.api as face_recognition
import sys

def scan_known_people(known_people_folder):
    known_names = []
    known_face_encodings = []

    basename = known_people_folder 
    img = face_recognition.load_image_file(known_people_folder)
    encodings = face_recognition.face_encodings(img)
    if len(encodings) == 1:
        known_names.append(basename)
        known_face_encodings.append(encodings[0])   
    return known_names, known_face_encodings


def test_image(image_to_check, known_names, known_face_encodings):
    unknown_image = face_recognition.load_image_file(image_to_check)

    # Scale down image if it's giant so things run a little faster
    if unknown_image.shape[1] > 1600:
        scale_factor = 1600.0 / unknown_image.shape[1]
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            unknown_image = scipy.misc.imresize(unknown_image, scale_factor)

    unknown_encodings = face_recognition.face_encodings(unknown_image)
    if len(unknown_encodings)==1:
        for unknown_encoding in unknown_encodings:
            result = face_recognition.compare_faces(known_face_encodings, unknown_encoding)
            distance = face_recognition.face_distance(known_face_encodings, unknown_encoding)
            # print("True") if True in result else print("False ")
    if(distance):
        return distance[0],result[0]
    else:
        return 0,0



def image_files_in_folder(folder):
    return [os.path.join(folder, f) for f in os.listdir(folder) if re.match(r'.*\.(jpg|jpeg|png)', f, flags=re.I)]


def main(known_people_folder, image_to_check):
    known_names, known_face_encodings = scan_known_people(known_people_folder)
    distance,result=test_image(image_to_check, known_names, known_face_encodings)
    return distance,result

if __name__ == "__main__":

  main(sys.argv[1],sys.argv[2])