import gradio as gr
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub

loaded_model = tf.keras.models.load_model(
       ('CatDogmodel2.h5'),
       custom_objects={'KerasLayer':hub.KerasLayer}
)

def model(image):
    im_scaled = image/255
    im_reshape = np.reshape(im_scaled,[1,160,160,3])
    pred = loaded_model.predict(im_reshape)
    pred_label = np.argmax(pred)
    if (pred_label == 0):
        return "The Image is of a Dog."
    if (pred_label == 1):
        return "The Image is of a Cat."

image = gr.inputs.Image(shape=(160,160))

iface = gr.Interface(fn=model, inputs=image, outputs='text')
iface.launch(debug=True)