app.py

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

# Load your learner
learn = load_learner('export.pkl')

# Define the prediction function
def predict(img):
    img = PILImage.create(img)  # Convert image into PILImage
    pred, pred_idx, probs = learn.predict(img)  # Make prediction
    labels = learn.dls.vocab  # Get the labels
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

# Define the Gradio interface
interface = gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=3))

# Launch the interface
interface.launch(share=True)