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

learn = load_learner('export.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 = "Bears Classifier"
description = "A simple bears classifier trained on the dataset created with fastai & bing search."
examples = ['grizzly.jpg']

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