app.py

import gradio as gr    
from huggingface_hub import from_pretrained_keras
import numpy as np
import logging




#reloaded_model_eth = from_pretrained_keras('jmparejaz/Facial_eth_recognition')

def rgb2gray(rgb):
    return np.dot(rgb[...,:3], [0.2989, 0.5870, 0.1140]) 
 
def fun(a):
    reloaded_model = from_pretrained_keras('jmparejaz/Facial_Age-gender-eth_Recognition')
    #img=load_img(a, grayscale=True)
    logging.info("%s, %s "%(a.shape[0],a.shape[1])
    pred=reloaded_model.predict(a)
    return pred


gr.Interface(fn=fun, inputs="image", outputs=["label","text"]).launch()