import gradio as gr
from fastai.vision.all import load_learner, PILImage

# Cargar el modelo utilizando load_learner
learn = load_learner('model.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))}

# Crear la interfaz con título y descripción
gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=3),

     title="Brain and fruits classifier",

     description="This model identifies between real brains, prunes and walnuts in images.").launch()