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


title = "Open/Closed Door Classifier"
description = "A classifier trained using fastai on search images of open and closed doors." \
    "Created for Lesson 2 in the fastai course."

examples = ['open-door.jpeg', 
    'crack_2.jpg', 'red_arch.jpg', 
    'green.jpg', 'red.jpg', 'opening_door.jpg', 
    'inside.jpg', 'cracked_3.jpg', 'old.jpg', 
    'blue.jpg', 'closed-door.jpeg', 'crack_1.jpg']


learn = load_learner('door_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))}



iface = gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(512, 512)),
    outputs=gr.outputs.Label(num_top_classes=3),
    title=title,
    description=description,
    examples=examples,
    interpretation="default",
    enable_queue=True).launch(share=True)