app.py

#!/usr/bin/env python
# coding: utf-8
from fastai.vision.all import *
import gradio as gr

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 = "NSFW image classifier"
description = "A nsfw image classifier trained on the nsfw_data_scraper dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
interpretation='default'
enable_queue=True

gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512,512)),outputs=gr.outputs.Label(num_top_classes=5),title=title,description=description,interpretation=interpretation,enable_queue=enable_queue).launch()