app.py

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

learn = load_learner('bears_identifier_final.pkl')

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 = "Bear Classifier"
description = "A bear classifier trained on DDG images with Fastai. Created as demo for Gradio and HuggingFace Spaces."
article="<p style='text-align: center'><a href='#' target='_blank'>TBD</a></p>"
examples = ['grizzly.jpg']
interpretation='default'
enable_queue=True

gr.Interface(
    fn=predict, 
    inputs=gr.Image(), 
    outputs=gr.Label(num_top_classes=3),
    title=title,
    description=description,
    article=article,
    examples=examples,).launch(share=True)