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

learn = load_learner('dog_breed.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 = "Doge Breed Classifier"
description = "A dog breed classifier trained on duckduckgo images with fastai."
interpretation='default'
enable_queue=True

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