app.py

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.jpg", 
    "crack_2.jpg", "red_arch.jpg", 
    "green.jpg", "red.jpg", "opening_door.jpg", 
    "inside.jpg", "cracked_3.jpg", "old.jpg", 
    "blue.jpg"]

examples = list(map(lambda x: "examples/" + x, examples))
#print(examples)


learn = load_learner('door_model.pkl')
labels = learn.dls.vocab

def predict(img_input):
    img = PILImage.create(img_input)
    pred,pred_idx,probs = learn.predict(img_input)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}


iface = gr.Interface(
    fn=predict,
    inputs=gr.Image(shape=(512, 512)),
    outputs=gr.Label(num_top_classes=3),
    title=title,
    description=description,
    examples=examples).queue().launch()