import gradio as gr
from keras.models import model_from_json
from tensorflow.keras.preprocessing import image
import numpy as np






def predict_age_gender(image):
    json_file = open('xception.json', 'r')
    loaded_file_json = json_file.read()
    json_file.close()
    
    model = model_from_json(loaded_file_json)
    model.load_weights('xception_modelv2.h5')

    images = np.resize(image, new_shape=(1, 128, 128, 3))
    img_pixels = np.expand_dims(images, axis=0)
    img_pixels = images.astype('float')
    img_pixels = img_pixels.reshape((1, 128, 128, 3))
    img_pixels /= 255

    predict = model.predict(img_pixels)
    gender_predict = predict[0]
    age_predict = predict[1]
    return {'Gender': ['Fmale' if gender_predict > 0.5 else 'Male'], 'Age': age_predict[0][0]}


iface = gr.Interface(predict_age_gender, gr.Image(), gr.Text())
iface.launch()