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

#import pathlib
#temp = pathlib.PosixPath
#pathlib.PosixPath = pathlib.WindowsPath

catergories = ('bunny girl', 'cat neko girl', 'fox kitsune girl', 'wolfgirl')

def load_model_and_predict(img):
    #img = PILImage.create(image_path)
    pred, idx, probs = learn.predict(img)
    #return pred, probs
    return dict(zip(catergories, map(float,probs)))

model_path = "export_resnet18_e12_3.pkl"
learn = load_learner(model_path)

image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label()

iface = gr.Interface(fn=load_model_and_predict, inputs=image, outputs=label, title='兽耳娘分类器', description='这是一个基于resnet18训练的玩具模型，可以将输入的~二次元~图画分类为：bunny girl/兔兔、cat neko girl/猫娘、fox kitsune girl/狐娘、wolfgirl/狼娘。 \n 每类均使用15张随机画作或冻鳗截图训练，该模型的分类正确率受裁剪方法、图画构图、角色姿势等多种因素影响，准确率难以保证，仅供娱乐。 \n 08/28/23')
iface.launch()