import numpy as np
import gradio as gr
from tensorflow import keras

from huggingface_hub import from_pretrained_keras
model = from_pretrained_keras("ISYS/MyNewModel")

def greet(img):
    img = np.expand_dims(img, axis=0)
    #return np.argmax(model.predict(img)[0])
    numb = np.argmax(model.predict(img)[0])
    return numb % 3

def rasp_numb(img):
    img = np.expand_dims(img, axis=0)
    return np.argmax(model.predict(img)[0])


output1 = gr.outputs.Text((np.argmax(model.predict(img)[0])% 3) )

output2 = gr.outputs.Text(np.argmax(model.predict(img)[0]))

demo = gr.Interface(fn=greet, inputs="sketchpad", outputs=[output1, output2])
demo.launch()