from keras.models import load_model
import numpy as np
import cv2


class GenderPrediction:
    def __init__(self):
        self.model = load_model("gender_v1.0.h5")

    def predict_gender(self, image):

        # chuyển ảnh về mức xám
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

        # resize ảnh phủ hợp với model
        target_size = (48, 48)
        resized_face = cv2.resize(gray, target_size)

        # normalize ảnh
        normalize_face = resized_face / 255.0

        # chuyển về cùng shape với input tensror (1,48,48)
        normalize_face = np.expand_dims(normalize_face, axis=0)

        # model output 'probabilities': array([[0.019824,0.98018]], dtype=float32)
        predictions = self.model.predict(normalize_face)
        threshold = 0.5
        predicted_class = 'Male' if predictions[0][1] >= threshold else 'Female'

        return predicted_class