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

# gradio==3.50

plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath

learn = load_learner('YomeRecognition.pkl')

labels = learn.dls.vocab # list of model classes

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))}

gr.Interface(
    fn=predict,
    inputs =gr.Image(),
    outputs=gr.Label(num_top_classes=5),
    title="😍 Sugar 🐶 Yome 🦮 Yang Chenchen 💕 Recognition 🐕",
    description="Classifier trainded on images of Yang Chenchen Yome, Wang Xinyao, and others. ",
    examples=['jpg/a.jpg', 'jpg/b.jpg', 'jpg/c.jpg',  'jpg/1.jpg', 'jpg/2.jpg', 'jpg/4.jpg', 'jpg/5.JPG', 'jpg/6.JPG', 'jpg/9.JPG'],
    ).launch()
    
    

# def greet(name):
#     return "Hello " + name + "!!"

# iface = gr.Interface(fn=predict, 
#                      inputs="text",                      
#                      outputs="text")
# iface.launch()