{"id":13723817,"url":"https://github.com/Kitware/VeloView","last_synced_at":"2025-05-07T17:31:38.273Z","repository":{"id":25874269,"uuid":"29314440","full_name":"Kitware/VeloView","owner":"Kitware","description":"VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS. This repository is a mirror of https://gitlab.kitware.com/LidarView/VeloView-Velodyne.","archived":false,"fork":false,"pushed_at":"2021-09-29T13:16:39.000Z","size":45775,"stargazers_count":319,"open_issues_count":61,"forks_count":165,"subscribers_count":40,"default_branch":"master","last_synced_at":"2025-04-05T11:09:17.277Z","etag":null,"topics":["hdl","lidar","lidar-camera-calibration","lidar-data-manipulation","lidar-measurements","sensor-data","sensor-streaming","velodyne","velodyne-hdl-sensors","velodyne-sensor"],"latest_commit_sha":null,"homepage":"http://www.paraview.org/VeloView/","language":"C++","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Kitware.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-01-15T19:36:37.000Z","updated_at":"2025-04-01T14:06:00.000Z","dependencies_parsed_at":"2022-08-07T11:16:06.784Z","dependency_job_id":null,"html_url":"https://github.com/Kitware/VeloView","commit_stats":null,"previous_names":[],"tags_count":65,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kitware%2FVeloView","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kitware%2FVeloView/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kitware%2FVeloView/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kitware%2FVeloView/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Kitware","download_url":"https://codeload.github.com/Kitware/VeloView/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252926675,"owners_count":21826348,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["hdl","lidar","lidar-camera-calibration","lidar-data-manipulation","lidar-measurements","sensor-data","sensor-streaming","velodyne","velodyne-hdl-sensors","velodyne-sensor"],"created_at":"2024-08-03T01:01:45.975Z","updated_at":"2025-05-07T17:31:35.330Z","avatar_url":"https://github.com/Kitware.png","language":"C++","funding_links":[],"categories":["Data Visualization and Mission Control"],"sub_categories":["Point Cloud"],"readme":"# Introduction\n\nLidarView performs real-time visualization of live captured 3D LiDAR data\nfrom Velodyne's HDL sensors (HDL-32E and HDL-64E).\n\nLidarView can playback pre-recorded data stored in .pcap files. The HDL\nsensor sweeps an array of lasers (32 or 64) 360\u0026deg; and a vertical field of\nview of 40\u0026deg;/26\u0026deg; with 5-20Hz and captures about a million points per\nsecond (HDL-32E: ~700,000pt/sec; HDL-64E: ~1.3Million pt/sec).\nLidarView displays the distance measurements from the HDL as point cloud\ndata and supports custom color maps of multiple variables such as\nintensity-of-return, time, distance, azimuth, and laser id. The data can\nbe exported as XYZ data in CSV format or screenshots of the currently\ndisplayed point cloud can be exported with the touch of a button.\n\n# Features\n\n-   Input from live sensor stream or recorded .pcap file\n-   Visualization of LiDAR returns in 3D + time including 3d position\n    and attribute data such as timestamp, azimuth, laser id, etc\n-   Spreadsheet inspector for LiDAR attributes\n-   Record to .pcap from sensor\n-   Export to CSV or VTK formats\n-   Record and export GPS and IMU data (*New in 2.0*)\n-   Ruler tool (*New in 2.0*)\n-   Visualize path of GPS data (*New in 2.0*)\n-   Show multiple frames of data simultaneously (*New in 2.0*)\n-   Show or hide a subset of lasers (*New in 2.0*)\n\n# How to Get\n\nBinary installers for VeloView are available on this page: [https://gitlab.kitware.com/LidarView/VeloView-Velodyne/-/releases](https://gitlab.kitware.com/LidarView/VeloView-Velodyne/-/releases)\n\nVeloView has the same runtime requirements as LidarView, see [INSTALLATION.md](https://gitlab.kitware.com/LidarView/lidarview-core/-/blob/master/Documentation/INSTALLATION.md)\n\n# How to Build\n\nVeloView compilation follows the same steps as LidarView, see [Developper Guide](https://gitlab.kitware.com/LidarView/lidarview-core/-/blob/master/Documentation/LidarView_Developer_Guide.md)\n\nThe source code for VeloView is made available under the Apache 2.0\nlicense.\n\n# How to Use\n\nTake a look at: [VeloView User Guide](https://gitlab.kitware.com/LidarView/VeloView-Velodyne/-/blob/master/Documentation/VeloView_User_Guide.pdf)\n\nGet started with SLAM using this Guide : [How to SLAM](https://gitlab.kitware.com/keu-computervision/slam/-/blob/master/paraview_wrapping/doc/How_to_SLAM_with_LidarView.md)\n\nSee LidarView \u0026 SLAM in action in the [LidarView 2021 Webinar Video](https://vimeo.com/524848891)\n\nSample data for VeloView can be obtained from\n[MIDAS](http://www.midasplatform.org/) in the\n[Velodyne LiDAR\ncollection](http://midas3.kitware.com/midas/community/29).\n\n# Configuration Tips\n\nFor \"sensor streaming\" (live display of sensor data) it\nis important to change the network settings of the Ethernet adapter\nconnected to the sensor from automatic IP address to manual IP address\nselection and choose:\n\n* HDL-32E\n  * IP address: 192.168.1.70 (70 as example, any number except 201 works)\n  * Gateway: 255.255.255.0\n* HDL-64E\n  * IP address: 192.168.3.70 (70 as example, any number except 43 works)\n  * Gateway: 192.168.3.255\n\nIn order for sensor streaming to work properly, it is important to\ndisable firewall restrictions for the Ethernet port. Disable the\nfirewall completely for the ethernet device connected to the sensor or\nexplicitly allow data from that Ethernet port of (including both public\nand private networks).\n\nWhen opening pre-recorded data or live sensor streaming data one is\nprompted to choose a calibration file.\n\n* For HDL-32E data no calibration\nfile is needed (the HDL-32E calibration values are already incorporated\nin LidarView) therefore select \"NONE\".\n* For HDL-64E data the correct\ncalibration file for that sensor needs to be chosen. The calibration\nfile can be found on the individual product CD that was sent with the\nHDL-64E sensor.\n\n# For Github users\n\n[Github](https://github.com/Kitware/VeloView) is a mirror of the\n[official repository](https://gitlab.kitware.com/LidarView/VeloView-Velodyne).\nWe do not actively monitor issues or pull request on Github. Please use the\n[official repository](https://gitlab.kitware.com/LidarView/VeloView-Velodyne) to report issues or contributes fixes.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FKitware%2FVeloView","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FKitware%2FVeloView","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FKitware%2FVeloView/lists"}