app.py

import gradio as gr
from fastai.vision.all import *
learn = load_learner('20250123_squish_model.pkl')

#labels = learn.dls.vocab
labels=['Comfort Food Squishable',
        'Plague-related Squishable',
        'Standard Squish',
        'Undercover Squishable!'
        ]

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 = "Squishable Type Classifier"
description = "A squishable classifier trained with fastai. Do you have a Standard Squish? Undercover? Comfort Food? Let's find out! <br> Created as a demo for Gradio and HuggingFace Spaces."
article="<p style='text-align: center'><a href='https://rlearsch.github.io/' target='_blank'>Blog post</a></p>"

gr.Interface(fn=predict,
             inputs=gr.components.Image(height=214, width=214),
             outputs=gr.components.Label(num_top_classes=3),
             title=title,
             description=description,
             article=article,
             ).queue(max_size=3
            ).launch()