app.py

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

learn = load_learner('lingerie.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 = "Lingerie brand classifier"
description = "This classifier can identify whether your lingerie is from Studio PIA, Atelier Bordelle or Edge O'Beyond. Trained w/ fast.ai and a bunch of pictures found w/ DuckDuckGo"
examples = ["b.png", "eob.jpg"]

interpretation ='default'

gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,examples=examples,interpretation=interpretation).launch(share=True)