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 dict(zip(categories, map(float,probs)))



image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['laughing.jpg', 'dancing.jpg', 'drinking.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)