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| from fastai.vision.all import load_learner | |
| import gradio as gr | |
| cap_labels = cap_labels = { | |
| 'baseball cap', | |
| 'beanie cap', | |
| 'fedora cap', | |
| 'cowboy hat', | |
| 'kepi cap', | |
| 'flat cap', | |
| 'trucker cap', | |
| # 'newsboy cap' | |
| 'pork pie hat', | |
| 'bowler hat', | |
| 'top hat', | |
| 'sun hat', | |
| 'boater hat', | |
| # 'ivy cap', | |
| 'bucket hat', | |
| 'balaclava cap', | |
| 'turban cap', | |
| 'taqiyah cap', | |
| 'rasta cap', | |
| 'visor cap' | |
| } | |
| version = 1 | |
| model_path = f"cap-recognizer-v{version}.pkl" | |
| model = load_learner(model_path) | |
| def recognize_image(image): | |
| pred, idx, probs = model.predict(image) | |
| return dict(zip(sorted(cap_labels), map(float, probs))) | |
| image = gr.inputs.Image(shape=(192, 192)) | |
| label = gr.outputs.Label() | |
| examples = [ | |
| 'test_images/test_0.jpg', | |
| 'test_images/test_1.jpg', | |
| 'test_images/test_2.jpg', | |
| 'test_images/test_3.jpg', | |
| 'test_images/test_4.jpg', | |
| 'test_images/test_5.jpg'] | |
| iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples) | |
| iface.launch(inline=False) |