from fastai.vision.all import *
import gradio as gr
import pathlib
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath

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 = "Bear Classifier"
description = "A bear classifier trained on downloaded images of bear dataset with fastai."
article="<p style='text-align: center'><a href='https://shuowangphd.github.io' target='_blank'>Back to my personal webpage.</a></p>"
exa = ['grizzly.jpg','teddy.jpg']
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,article=article,examples=exa,
             interpretation=interpretation,
             enable_queue=enable_queue).launch(share=True)