face_verification.py

import argparse

import numpy as np
import cv2 as cv
from insightface.app import FaceAnalysis

app = FaceAnalysis(providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
app.prepare(ctx_id=0, det_size=(640, 640))


def face_verification(image_1, image_2, threshold):
    image_1 = cv.imread(image_1)
    image_1 = cv.cvtColor(image_1, cv.COLOR_BGR2RGB)
    image_2 = cv.imread(image_2)
    image_2 = cv.cvtColor(image_2, cv.COLOR_BGR2RGB)
    result_1 = app.get(image_1)
    result_2 = app.get(image_2)
    if len(result_1) == 1 and len(result_2) == 1:
        result_1 = result_1[0]['embedding']
        result_2 = result_2[0]['embedding']
        distance = np.sqrt(np.sum((result_1 - result_2)) ** 2)
        if distance < threshold:
            print(f'Face Verification: True, Distance: {distance}')
        else:
            print(f'Face Verification: False, Distance: {distance}')
    else:
        print('Images no have face or have more than one face')


if __name__ == '__main__':
    parser = argparse.ArgumentParser()

    parser.add_argument('--image_1', type=str, help='Image 1 path', default='./verification_test_images/img_1.jpg')
    parser.add_argument('--image_2', type=str, help='Image 2 path', default='./verification_test_images/img_2.jpg')
    parser.add_argument('--threshold', type=int, help='Threshold for similar faces', default=25)

    args = parser.parse_args()

    face_verification(args.image_1, args.image_2, args.threshold)