| from fastai.vision.all import * | |
| import gradio as gr | |
| import numpy as np | |
| 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): | |
| img = np.array(img) | |
| img = PILImage.create(img).resize((192, 192)) | |
| pred,idx,probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| image = gr.Image(type='pil') | |
| label = gr.Label() | |
| examples = ['laughing.jpg', 'dancing.jpg', 'drinking.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| intf.launch(inline=False) | |