# import gradio as gr

# def greet(name):
#     return "Hello " + name + "!!"

# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()

# Importing to fix missing function error

import os
import random
import shutil

from pathlib import Path
import urllib

import numpy as np
import pandas as pd
from PIL import Image
import matplotlib.pyplot as plt

import fastai==1.0.61
from fastai.vision import *

import gradio as gr
# from fastai.vision.all import *
import skimage

labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Food Classifier"
description = "A food classifier trained on the Food 101 dataset with fastai by Phan. Created as a demo for Gradio and HuggingFace Spaces."
examples = ['hamburger.jpg']
interpretation='default'
enable_queue=True

gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()