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--- |
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license: apache-2.0 |
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task_categories: |
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- image-segmentation |
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language: |
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- en |
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pretty_name: e |
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--- |
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# Noisy-Labels-Instance-Segmentation |
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### ReadMe: |
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Important! The original annotations should be in coco format. |
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To run the benchmark, run the following: |
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``` |
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python noise_annotations.py /path/to/annotations --benchmark {easy, medium, hard} (choose the benchmark level) --seed 1 |
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``` |
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For example: |
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``` |
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python noise_annotations.py /path/to/annotations --benchmark easy --seed 1 |
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``` |
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To run a custom noise method, run the following: |
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``` |
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python noise_annotations.py /path/to/annotations --method_name method_name --corruption_values [{'rand': [scale_proportion, kernel_size(should be odd number)],'localization': [scale_proportion, std_dev], 'approximation': [scale_proportion, tolerance], 'flip_class': percent_class_noise}]}] |
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``` |
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For example: |
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``` |
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python noise_annotations.py /path/to/annotations --method_name my_noise_method --corruption_values [{'rand': [0.2, 3], 'localization': [0.2, 2], 'approximation': [0.2, 5], 'flip_class': 0.2}] |
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``` |
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## Citation |
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If you use this benchmark in your research, please cite this project. |
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``` |
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@misc{grad2024benchmarkinglabelnoiseinstance, |
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title={Benchmarking Label Noise in Instance Segmentation: Spatial Noise Matters}, |
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author={Eden Grad and Moshe Kimhi and Lion Halika and Chaim Baskin}, |
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year={2024}, |
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eprint={2406.10891}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2406.10891}, |
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} |
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``` |
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## License |
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This project is released under the [Apache 2.0 license](https://github.com/eden500/Noisy-Labels-Instance-Segmentation/blob/main/LICENSE.txt). |
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Please make sure you use it with proper licenced Datasets. |
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We use [MS-COCO/LVIS](https://cocodataset.org/#termsofuse) and [Cityscapes](https://www.cityscapes-dataset.com/license/) |
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