app.py

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

temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath

learn = load_learner("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 = "Leak Detection"
description = "Analyze a photograph of a wellhead and predict whether or not there is a leak."
interpretation = "default"
enable_queue = True

gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(224, 224)),
    outputs=gr.outputs.Label(num_top_classes=2),
    title=title,
    description=description,
    interpretation=interpretation,
    enable_queue=enable_queue,
).launch()