app.py

import tensorflow as tf
from keras.models import load_model
import gradio as gr
from matplotlib import pyplot as plt
import cv2
model = load_model('eee.keras')

def image_mod(image_mod):
    img = cv2.imread(image_mod)
    resize = tf.image.resize(img, (256, 256))
    plt.imshow(resize.numpy().astype(int))
    yhat = model.predict(np.expand_dims(resize,0))
    display = np.max(yhat)
    return display

gr.Interface(fn=image_mod,
             inputs=gr.Image(shape=(256, 256)),
             outputs=gr.Label(num_top_classes=3),
             examples=["Sunny_day_in_Hiroo.jpg","640px-Cloudy_Sky2.JPG","Foggy_day_of_Riga.jpg","Jida,_Zhuhai,_rainy_day.jpg","Odalys_Edenarc,_Arc_1800,_on_a_snowy_day,_2013.jpg"]).launch()