from io import BytesIO
from typing import Annotated

import gradio as gr
import numpy as np
from deepface import DeepFace


def get_face_type(file):
    try:
        attribute = DeepFace.analyze(
            img_path=file,
            actions=['age', 'gender'],
        )
        gender = attribute[0]['dominant_gender']
        age = attribute[0]['age']
        if gender == 'Man':
            if age < 10:
                face_type = 7
            elif age < 20:
                face_type = 3
            elif age < 30:
                face_type = 12
            elif age < 40:
                face_type = 1
            elif age < 50:
                face_type = 15
            elif age < 60:
                face_type = 5
            elif age < 70:
                face_type = 10
            else:
                face_type = 8
        elif gender == 'Woman':
            if age < 10:
                face_type = 14
            elif age < 20:
                face_type = 0
            elif age < 30:
                face_type = 4
            elif age < 40:
                face_type = 6
            elif age < 50:
                face_type = 13
            elif age < 60:
                face_type = 2
            elif age < 70:
                face_type = 9
            else:
                face_type = 11
        else:
            return "Face could not be detected."
        return f"face type:{face_type}---gender:{gender}---age:{age}"
    except Exception as e:
        print(e)
        return f"Face could not be detected."


if __name__ == '__main__':
    demo = gr.Interface(fn=get_face_type, inputs="image", outputs="label")
    demo.launch(share=False)