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

learn = load_learner('pets_resnet50.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 = "宠物分类器"
description = "使用 fastai 在Oxford Pets数据集上训练的宠物品种分类器。"
article="<p style='text-align: center'><a href='https://ai.maogoujiaoliuqi.com/' target='_blank'>番石榴实验室</a></p>"
examples = ['staffordshire_bull_terrier_11.jpg']

gr.Interface(fn=predict,inputs=gr.Image(),outputs=gr.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples).launch()