import cv2
import numpy as np
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.image import img_to_array, load_img
from tensorflow.keras.losses import MeanSquaredError
from tensorflow.keras.utils import get_custom_objects

def mse(y_true, y_pred):
    return MeanSquaredError()(y_true, y_pred)

get_custom_objects().update({"mse": mse})

def predict_age(model, image_path):
    img = load_img(image_path, target_size=(128, 128))
    img_array = img_to_array(img) / 255.0
    
    img_array = np.expand_dims(img_array, axis=0)
    
    predicted_age = model.predict(img_array)
    
    return predicted_age[0][0]

def main():
    model_path = "face_aging_model.h5"
    image_path = "visage.jpg"
    
    model = load_model(model_path, custom_objects={"mse": mse})
    
    age = predict_age(model, image_path)
    print(f"L'âge prédit est: {age}")

if __name__ == "__main__":
    main()