deepface2

from deepface import DeepFace
import os

os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'

def main():
    # Assuming img1_path and img2_path are defined elsewhere
    # and point to image files

    print('matching...')
    # result = DeepFace.verify(
    #     img1_path="bieber.jpeg",
    #     img2_path="bieber.jpg",
    #     model_name="ArcFace",
    #     detector_backend="retinaface"
    # )

    results = DeepFace.find(img_path="simi.png", db_path="imgs/",
    model_name="Facenet512",        # Match verify's default
    detector_backend="opencv",    # Match verify' s default
    distance_metric="euclidean",     # Match verify' s default
    enforce_detection=False,       # Match verify' s default (and find's typical behavior)
    align=True,
    )

    df = results[0] if isinstance(results, list) else results

    print(len(df))
    if len(df) == 0:
        exit()

    # Get the row with the smallest distance
    best_match = df.iloc[df['distance'].idxmin()]

    # Get the file path (identity)
    identity_path = best_match['identity']
    distance = best_match['distance']

    print(f"Best match: {identity_path} with distance {distance}")

if __name__ == '__main__':
    main()
    #print(DeepFace.verify(img1_path='menight.jpeg', img2_path='imgs/me2.jpeg'))