import face_recognition
from PIL import Image


document_image = "documento.jpg"
document_image_rotated_ok = "documento_ok.jpg"
selfie_image = face_recognition.load_image_file("selfie.jpg")

selfie_face_encoding = face_recognition.face_encodings(selfie_image)[0]

known_encodings = [
    selfie_face_encoding,
]


def rotate_image(validate_image):
    rotated_image = Image.open(validate_image)
    rotated = rotated_image.rotate(90)
    rotated.save(document_image_rotated_ok, "JPEG", quality=100, optimize=True, progressive=True)
    test_faces(document_image_rotated_ok)


def test_faces(check_image):
    test_face = face_recognition.load_image_file(check_image)
    try:
        face_recognition.face_encodings(test_face)[0]
    except:
        rotate_image(check_image)


def return_accuracy():
    tested_faces = face_recognition.load_image_file(document_image_rotated_ok)
    image_to_test_encoding = face_recognition.face_encodings(tested_faces)[0]

    face_distances = face_recognition.face_distance(known_encodings, image_to_test_encoding)

    for i, face_distance in enumerate(face_distances):
        print("{:.2}".format(1 - face_distance))
        print()


test_faces(document_image)
return_accuracy()