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

learn = load_learner('model.pkl')

categories = ['calling', 'clapping', 'cycling', 'dancing', 'drinking', 'eating', 'fighting', 'hugging',
              'laughing', 'listening_to_music', 'running', 'sitting', 'sleeping', 'texting', 'using_laptop']

def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return {cat: float(prob) for cat, prob in zip(categories, probs)}

demo = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(), 
    outputs=gr.Label(),
    examples=[
        'laughing.jpg',
        'dancing.jpg',
        'drinking.jpg'
    ]
)

demo.launch()