app.py

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

learn = load_learner('model.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 = "Horde or Aliance Classifier"
description = "Horde or Aliance Classifier created in Hugging Face Spaces"
article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
examples = ['horde.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()