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

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 = "Pengenalan Ras Hewan Peliharaan Kucing dan Anjing"
description = "Selamat Datang di Aplikasi Pengklasifikasi ras Hewan Peliharaan yang di training pada kumpulan data Oxford Pets dengan Fastai :D"
article="<p style='text-align: center'><a href='https://wahyupebrianto.github.io/' target='_blank'>Blog post</a></p>"
examples = ['cat.jpg']

image = gr.Image(type="pil")#gr.inputs.Image(shape=(192, 192))
label = gr.Label(num_top_classes=3)#gr.outputs.Label()

gr.Interface(fn=predict,inputs=image,
             outputs=label,title=title,
             description=description,article=article,examples=examples).launch()