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

learn = load_learner('cuttest_dogs_model.pkl')

labels = learn.dls.vocab # list of model classes
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))}

gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(512, 512)),
    outputs=gr.outputs.Label(num_top_classes=5),
    title="The Cuttest Dogs Classifier 🐶🐕🦮🐕‍🦺",
    description="Classifier trainded on images of huskies, retrievers, pomeranians, corgis and samoyeds. Created as a demo for Deep Learning app using HuggingFace Spaces & Gradio.",
    examples=['husky.jpg', 'retriever.jpg', 'corgi.jpg', 'pomeranian.jpg', 'samoyed.jpg'],
    enable_queue=True).launch()