{"id":25289089,"url":"https://github.com/ltriess/semantic_kitti_stats","last_synced_at":"2025-10-27T23:30:59.574Z","repository":{"id":40980003,"uuid":"204029982","full_name":"ltriess/semantic_kitti_stats","owner":"ltriess","description":":chart_with_downwards_trend: Get some nice plots with statistics about the Semantic KITTI 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Semantic KITTI Dataset Statistics\n[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)\n\nThis repository holds a script that allows an analysis of the [Semantic KITTI Dataset](http://semantic-kitti.org/) [1,2].\nThe main focus is on distance and label analysis.\nFor all statistics a csv file and a plot are generated.\n\nSome Examples:\n* see which label has how many points over the distance\n\n![teaser1](/figures/total_distance_label_matrix.png)\n\n* see how many points belong to a specific label in each sequence\n\n![teaser2](/figures/sequence_label_matrix.png)\n\n\n* ... and many more, such as the analysis per sequence or labels over azimuth and elevation angle\n\n\n## Contents\n* [Getting Started](#getting-started)\n* [Running the code](#running-the-code)\n* [License](#license)\n* [References](#references)\n\n\n## Getting Started\n\nThese instructions will get you a copy of the project up and running on your local machine.\n\n### Installing\n\n```\n$ git clone https://github.com/ltriess/semantic_kitti_stats.git\n$ cd semantic_kitti_stats\n$ pip install requirements.txt\n```\n\n### Get the Data\n\nDownload the data and unzip it in the same folder.\n* for the labels: [Semantic KITTI](http://semantic-kitti.org/dataset.html#download)\n* for the point clouds: [KITTI Odometry](http://www.cvlibs.net/datasets/kitti/eval_odometry.php)\n\n## Running the code\n\nThe main script is `analyse.py` which can be called according to\n\n```\nUsage: analyse_sequence.py [OPTIONS] PATH\n\nOptions:\n  --mode [compute|from_data]  If compute is selected, PATH must be the path to the dataset.\n                              All statistics will be calculated from the data. If from_data\n                              is selected, PATH must be a a folder in which csv files with\n                              the computed statistics are located.\n  --save_dir PATH             Path where to save the generated graphs. If not provided, show on display.\n  --help                      Show this message and exit.\n```\n\nThe script first iterates over all trainval sequences and generates separate statistics for each sequence.\nFinally, all the sequence statistics are combined and a total analysis as well as a sequence overview is generated.\nThere are two modes in which the script dan be called:\n\n* _compute_: PATH must point to the root directory of the dataset which contains the folders\ndataset/sequences/{00..10}/{velodyne/labels} according to how the dataset is extracted after the download.\nAll statistics will be computed from the dataset and then plots will be generated.\nIf _save_dir_ is set to a valid path, all the statistics will be saved to csv files for later usage.\n* _from_data_: PATH must point to the folder in which all the generated csv files are located.\nThis is useful when the statistics are available, but a redo of the plots is needed.\n\nIn both modes, if _save_dir_ is set, the plots are saved as png files to the specified location.\nIf it is not set, the plots will be displayed on the screen.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details\n\n## References\n[1] J. Behley and M. Garbade and A. Milioto and J. Quenzel and S. Behnke and C. Stachniss and J. Gall,\n\"SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences\", ICCV 2019\n\n[2] A. Geiger and P. Lenz and C. Stiller and R. Urtasun, Vision meets Robotics: The KITTI Dataset, IJRR 2013\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fltriess%2Fsemantic_kitti_stats","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fltriess%2Fsemantic_kitti_stats","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fltriess%2Fsemantic_kitti_stats/lists"}