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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)
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