app.py

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

learn = load_learner('model.pkl')

labels = learn.dls.vocab

custom_labels = {
    "Other": "Nimeshindwa kutambua picha",
    "rust": "Kutu ya majani ya Maharage",
    "anthra": "Ndui ya maharage",
    "healthy": "Mmea una afya"
}

def predict(img):
    img = PILImage.create(img)
    pred, pred_idx, probs = learn.predict(img)
    return {custom_labels[labels[i]]: float(probs[i]) for i in range(len(labels))}

examples = ['image.jpeg']
interpretation = 'default'
enable_queue = True

# Updated component usage
gr.Interface(fn=predict, inputs=gr.components.Image(), outputs=gr.components.Label(num_top_classes=3), examples=examples).launch()