app.py

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

learn = load_learner('export.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 = "Oral diseases Classifier"
description = "A Oral diseases classifier trained on the oral disease dataset with fastai. Created as a demo for diatex."
examples = ['ulc.jpeg','hypo1.jpeg','gingi.jpeg','discol2.jpeg', 'cari.jpeg', 'calc3.jpeg']
# interpretation='default'
# enable_queue=True
# article=article,examples=examples
gr.Interface(fn=predict,inputs=gr.Image(),outputs=gr.Label(num_top_classes=6),examples=examples,title=title,description=description).launch()