app.py

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


def label_func(f): return f.name[:2]

learn = from_pretrained_fastai("smaciu/bee-wings-classifier")

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="Honey Bee Wing Classifier"
description = "A bee wings classifier trained with fastai"
examples = ['ES-0003-2092-0.dw.png','HU-0001-2019-000007-R.dw.png','PL-0002-000187-R.dw.png']
enable_queue=True

gr.Interface(fn=predict,
             inputs=gr.inputs.Image(type='pil'),
             outputs=gr.outputs.Label(num_top_classes=3),
             title=title,
             description=description,
             examples=examples,
             enable_queue=enable_queue).launch()