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| import gradio as gr | |
| from fastai.vision.all import * | |
| learn_inf = load_learner('model.pkl') | |
| categories = learn_inf.dls.vocab | |
| def classify_image(img): | |
| pred,pred_idx,probs = learn_inf.predict(img) | |
| return dict(zip(categories, map(float, probs))) | |
| iface = gr.Interface( | |
| title = "Is it Huggable?", | |
| description = "An image classifier that tells if something's huggable or not?", | |
| article = "<p style='text-align: center'><a href='https://github.com/daspartho/is-it-huggable' target='_blank'>Github</a></p>", | |
| fn=classify_image, | |
| inputs=gr.Image(shape=(224,224)), | |
| outputs=gr.outputs.Label(), | |
| examples=['examples/dog.jpg', 'examples/cactus.jpg', 'examples/plushie.jpg', 'examples/snowman.jpg', 'examples/chainsaw.jpg', 'examples/shark.jpg','examples/bunny.jpg', 'examples/knife.jpg', 'examples/tiger.jpg', 'examples/trex.jpg'], | |
| live=True, | |
| enable_queue=True | |
| ) | |
| iface.launch() |