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add readme

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  license: mit
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  license: mit
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+ ## Dataset for clothes segmentation
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+ ![plot](https://firebasestorage.googleapis.com/v0/b/aestyapp.appspot.com/o/user_looks%2FScreenshot%202024-03-10%20at%205.59.03%E2%80%AFPM.png?alt=media&token=0c3930b0-503c-443d-87cc-95d072126d34)
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+ Based on [iMaterialist Dataset](https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6/data) with several adjustments:
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+ 1. Filtered images with more than 1 person with no labeled clothes
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+ 2. Compressed number of classes to 8: `'background', 'upperbody', 'upperbody_up', 'lowerbody', 'wholebody', 'wholebody_up', 'shoes', 'accesories'`
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+ 3. Simple structure with 2 folders: images 512x512 in `.jpg` and corresponding segmaps 512x512 in `.npy`
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+ 4. You can find example class and data vizualisation in `dataset.ipynb`
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+
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+ If you find any bugs, please contact me on: [email protected]