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| from fastai.vision.all import * | |
| import gradio as gr | |
| # import pathlib | |
| # temp = pathlib.PosixPath | |
| # pathlib.PosixPath = pathlib.WindowsPath | |
| cap_labels = ( | |
| 'balaclava cap', | |
| 'baseball cap', | |
| 'beanie cap', | |
| 'boater hat', | |
| 'bowler hat', | |
| 'bucket hat', | |
| 'cowboy hat', | |
| 'fedora cap', | |
| 'flat cap', | |
| 'ivy cap', | |
| 'kepi cap', | |
| 'newsboy cap', | |
| 'pork pie hat', | |
| 'rasta cap', | |
| 'sun hat', | |
| 'taqiyah cap', | |
| 'top hat', | |
| 'trucker cap', | |
| 'turban cap', | |
| 'visor cap' | |
| ) | |
| model = load_learner('models/cap-recognizer-v1.pkl') | |
| def recognize_image(image): | |
| pred, idx, probs = model.predict(image) | |
| return dict(zip(cap_labels, map(float, probs))) | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label(num_top_classes=5) | |
| examples = [ | |
| 'unknown_00.jpg', | |
| 'unknown_01.jpg', | |
| 'unknown_02.jpg', | |
| 'unknown_03.jpg' | |
| ] | |
| iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples) | |
| iface.launch(inline=False) |