app.py

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

learn = load_learner("gods-model.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 = "God Classifier"
description = "A Norse/Hindu God Classifier (fastai course exercise)"

gr.Interface(fn=predict,
             inputs=gr.inputs.Image(shape=(512, 512)),
             outputs=gr.outputs.Label(num_top_classes=2),
             title=title,
             description=description,
             examples=['hindu.jpg','norse.jpg'],
             interpretation='default',
             enable_queue=True).launch()