import gradio as gr
from huggingface_hub import from_pretrained_fastai
from fastai.learner import load_learner
from PIL import Image
from fastai.vision.all import load_learner


repo_id = "JuncalG/Practica1"

learner = from_pretrained_fastai(repo_id)
labels = learner.dls.vocab


def predict(img):
    pred, pred_idx, probs = learner.predict(img)
    return {str(learner.dls.vocab[i]): float(probs[i]) for i in range(len(probs))}

# Usar componentes nuevos (Gradio moderno)
demo = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"), 
    outputs=gr.Label(num_top_classes=5),
    examples=['af3b0115aad1.png', 'b191ba0a2b12.png']
)


demo.launch(share=True)