app.py

import os
from huggingface_hub import from_pretrained_fastai

import gradio as gr

repo_id = "artificeresearch/spiritvision"
learner = from_pretrained_fastai(repo_id)
labels = learner.dls.vocab
HF_TOKEN = os.environ.get("HF_TOKEN")


def predict_fn(img):
    """
    :param img: img is a PIL image object
    :return: prediction and probabilities
    """
    img = img.convert('RGB')
    # print(f'{max(100 * probs):.2f}% {prediction} - {img}')
    pred, pred_idx, probs = learner.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}


gr.Interface(predict_fn,
             gr.inputs.Image(type='pil', shape=(512, 512)),
             outputs=gr.outputs.Label(num_top_classes=3), token=HF_TOKEN).launch()