import gradio as gr
from fastai.vision.all import *
import torch

learn = load_learner('food_classif_model_v1.pkl')

def predict_image(img):
    pred,los,prob = learn.predict(img)
    top_values, top_indx = torch.topk(prob, 3) # show 3 max values
    return pred
    # text_out = ''

    # if (top_values < 0.4).all():
    #     text_out = 'I do not know what is that'
    # else:    
    #     text_out = f'{food_indx[top_indx[0]]} = {top_values[0]}\n{food_indx[top_indx[1]]} = {top_values[1]}\n{food_indx[top_indx[2]]} = {top_values[2]}'
    # return text_out


# UI huggface

intrfce = gr.Interface(fn=predict_image,
             inputs=gr.Image(type="pil"),
             outputs=gr.Label()).launch()