app.py

import gradio as gr
from fastai.learner import load_learner 
from fastai.vision.all import * 
from gradio.components import Image, Label  # Use Label para o output

# ... (restante do seu código)

learn = load_learner('export.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 = "Agromarkers Classificador de Doença da Soja"
description = "Uma classificador de doenças treinado por IA "
article="<p style='text-align: center'><a href='https://www.agromarkers.com.br' target='_blank'>Home - Agromarkers</a></p>"

output = Label(num_top_classes=3)

gr.Interface(
    fn=predict,
    inputs=Image(type="pil", image_mode="RGB"),
    outputs=output,  # Use Label para a saída
    title=title,
    description=description,
    article=article
).launch(share=False)