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

learn = load_learner('model.pkl')

labels = learn.dls.vocab

def predict(img):
    pred,idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i,_ in enumerate(labels)}
    
with open("article.md") as f:
    article = f.read()

image = gr.inputs.Image(shape=(256,256))
label = gr.outputs.Label()
examples = ['house1.jpg','house2.jpg','house3.jpg','house4.jpg','house5.jpg']
title = "Storm Damaged House Classifier with fast.ai"
description = "Has your house possibly been damaged by recent storms, use fast.ai to detect damage to your home with this fine-tuned resnet 50 model"

intf = gr.Interface(fn=predict, inputs=image, outputs=label, examples=examples,title=title,description=description, article=article)

intf.launch()