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

# print versions
import sys
import torch
import fastai

# print("Python:", sys.version)
# print("PyTorch:", torch.__version__)
# print("Fastai:", fastai.__version__)

# load learner
import warnings
warnings.filterwarnings("ignore")
learn = load_learner('model-fastai-v2.8.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 = "Chihuahua vs Biscuit"
description = "Check if image is Chihuahua or Biscuit"
article="it was a joke with Dmitry when we started learn machine learning"
examples = ['chihuahua.jpg', 'biscuit.jpg']

demo = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs=gr.Label(num_top_classes=3),
    title=title,
    description=description,
    article=article,
    examples=examples)

demo.launch(server_name="0.0.0.0", server_port=7860, share=True)