app.py

import gradio as gr
from fastai.vision.all import *
import skimage
learn = load_learner("model.pkl")

labels = learn.dls.vocab

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

image = gr.inputs.Image(shape = (128,128))
label = gr.outputs.Label(num_top_classes=7)
title = "Garbage Classifier"
description = "A Garbage classifier trained with fastai. Created as a demo for Gradio and HuggingFace Spaces."
examples = ['paper24.jpg']
interpretation='default'
enable_queue=True

iface = gr.Interface(fn=classify_garbage, inputs=image, outputs=label,examples=examples,title=title,description=description,interpretation=interpretation,enable_queue=enable_queue)
iface.launch(inline=False)