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

learn = load_learner('modelo50.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 = "Bleach - Qual potencial de guerra? - RestNet50"
description = "Reconhecer os 5 Potenciais (Bleach)"
examples = ['Aizen.jpg', 'Ichigo.jpg', 'Zaraki.jpg','Ichibe.jpg', 'Urahara.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,
             examples=examples,
             interpretation=interpretation,
             enable_queue=enable_queue).launch()