app.py

# AUTOGENERATED! DO NOT EDIT! File to edit: 00_app.ipynb (unless otherwise specified).

__all__ = ['learn', 'predict', 'labels']

# Cell
learn = load_learner('export.pkl')

# Cell
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))}

# Cell
import gradio as gr
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)