Displaying 1 to 20 from 23 results

pcl - Point Cloud Library (PCL)

  •    C++

The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. We are financially supported by a consortium of commercial companies, with our own non-profit organization, Open Perception. We would also like to thank individual donors and contributors that have been helping the project.

semantic-segmentation-editor - Web labeling tool for bitmap images and point clouds

  •    Javascript

A web based labeling tool for creating AI training data sets (2D and 3D). The tool has been developed in the context of autonomous driving research. It supports images (.jpg or .png) and point clouds (.pcd). It is a Meteor app developed with React, Paper.js and three.js. (Optional) You can modify settings.json to customize classes data.

potree - WebGL point cloud viewer for large datasets

  •    Javascript

Install dependencies, as specified in package.json, and create a build in ./build/potree. Go to http://localhost:1234/examples/ to test the examples.

Open3D - Open3D: A Modern Library for 3D Data Processing

  •    C++

Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. We welcome contributions from the open-source community. For more, please visit the Open3D documentation.

loam_velodyne - Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar

  •    C++

Ask questions here. Issues #71 and #7 address this problem. The current known solution is to build the same version of PCL that you have on your system from source, and set the CMAKE_PREFIX_PATH accordingly so that catkin can find it. See this issue for more details.

mcl_3dl - A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s)

  •    C++

mcl_3dl is a ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map. The node receives the reference pointcloud as an environment map and localizes 6-DOF (x, y, z, yaw, pitch, roll) pose of measured pointclouds assisted by a motion prediction using odometry.

3d-bat - 3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

  •    Javascript

1. Step: draw bounding box in the camera image 2. Step: choose current bounding box by activating it 3. Step: You can move it in image space or even change its size by drag and droping 4. Step: Switch into PCD MODE into birds-eye-view 5. Step: Place 3D label into 3D scene to corresponding 2D label 6. Step: Adjust label: 1. drag and dropping directly on label to change position or size 2. use control bar to change position and size (horizontal bar -> rough adjustment, vertical bar -> fine adjustment) 3. Go into camera view to check label with higher intensity and bigger point size 7. Step: Choose label from drop down list 8. Step: Repeat steps 1-7 for all objects in the scene 9. Step: Save labels into file 10. Step: Click on 'HOLD' button if you want to keep the same label positions and sizes 11. Step: click on 'Next camera image'

plasio - In-browser LAS/LAZ point cloud renderer.

  •    Javascript

plasio is a project by Uday Verma and Howard Butler that implements point cloud rendering capability in a browser. Specifically, it provides a functional implementation of the ASPRS LAS format, and it can consume LASzip-compressed data using LASzip NaCl module. Plasio is Chrome-only at this time, but it is hoped that other contributors can step forward to bring it to other browsers. It is expected that most WebGL-capable browers should be able to support plasio, and it contains nothing that is explicitly Chrome-specific beyond the optional NaCL LASzip module. We just haven't tested it beyond Mac and Windows Chrome Canary at this time.

cpd - C++ implementation of the Coherent Point Drift point set registration algorithm.

  •    C++

Coherent Point Drift (CPD) is a point-set registration algorithm, originally developed by Andriy Myronenko et al. This is a C++ library that runs CPD. CPD can be compared to Iterative Closest Point, another point-set registration algorithm that is widely used. While ICP minimizes point-to-point distances, CPD uses a Gaussian Mixture Model to minimize the error between a point and all other points. If you're thinking that this is very computationally intensive, you're right — both the CPD algorithm and the underlying error calculations take a lot of time, which is why we've created fgt to speed up those Gauss transforms. We hope this library provides a freer and more performant alternative to the original reference Matlab implementation.

lopocs - Light OpenSource PointCloud Server

  •    Python

LOPoCS is a point cloud server written in Python, allowing to load Point Cloud from a PostgreSQL database thanks to the pgpointcloud extension. Note that LOPoCS is currently the only 3DTiles server able to stream data from pgpointcloud. This is possible thanks to the python module py3dtiles.

py3dtiles - Python module to manage 3DTiles format

  •    Python

Python module to manage 3DTiles format. For now, only the Point Cloud and the Batched 3D Model specifications are supported.

aframe-pointcloud-component - A Point Cloud component for [A-Frame](https://aframe.io).

  •    Javascript

A Point Cloud component for A-Frame. You might have to also adjust the scale, position and rotation properties in order to fit the point cloud to your scene.

geotrellis-pointcloud - GeoTrellis PointCloud library to work with any pointcloud data on Spark

  •    Scala

GeoTrellis PointCloud uses PDAL bindings to work with PointCloud data. PDAL is Point Data Abstraction Library. GDAL for point cloud data.

MVStudio - An integrated SfM (Structure from Motion) and MVS (Multi-View Stereo) solution.

  •    C++

MVStudio is a lightweight, easy to use, and integrated SfM (Structure from Motion) and MVS (Multi-View Stereo) solution. It is intended for learning/researching 3D computer vision. Prebuilt executables (for macOS, Linux, and Windows) can be downloaded here.

SensatUrban - 🔥Urban-scale point cloud dataset (CVPR 2021)

  •    C++

This dataset is an urban-scale photogrammetric point cloud dataset with nearly three billion richly annotated points, which is five times the number of labeled points than the existing largest point cloud dataset. Our dataset consists of large areas from two UK cities, covering about 6 km^2 of the city landscape. In the dataset, each 3D point is labeled as one of 13 semantic classes, such as ground, vegetation, car, etc.. The 3D point clouds are generated from high-quality aerial images captured by a professional-grade UAV mapping system. In order to fully and evenly cover the survey area, all flight paths are pre-planned in a grid fashion and automated by the flight control system (e-Motion).

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