Open3D Version 0.4.0 (released 2018-10-25)
The Open3D team and the Open Source Vision Foundation (http://www.osvf.org) are proud to announce the release of the 0.4 version of the Open3D library.
This release brings support for RealSense RGB-D sensors to Open3D, enabling functionalities such as real-time RGB-D capturing and a new point cloud viewer. We have also added new documentation and examples using RealSense sensors to create 3D reconstructions.
We are also excited to introduce support for Jupyter notebooks with a brand new WebGL widget to perform advanced 3D visualization from the comfort of your browser.
One of our main goals is to leverage Open3D as a tool to simplify the use of state-of-the-art 3D pipelines like those used in computer vision and machine learning. With this goal in mind, we are proud to introduce the Open3D Ecosystem, a set of repositories that make use of Open3D to create powerful applications. The first member of this ecosystem is Open3D-PointNet [link], a version of the famous machine learning architecture [link] for point cloud classification and semantic segmentation, which is now fully usable from the commodity of Open3D routines.
From a project infrastructure perspective, we just finalized the integration with TravisCI to perform automatic unit testing. This is a large step forward in terms of quality control for Open3D and it will help to make our software more reliable while expediting its development. The team has made an enormous effort to define UnitTests for all the functionalities present in the library, a task that will be concluded in future releases.
Check out our release video [link] to see these functionalities in action!
For a detailed description of all the features of Open3D 0.4, please keep reading. We hope you enjoy this release and hope to hear from you. Please send us feedback at email@example.com and join our Discord network [link] to participate in the discussions.
The Open3D team
- [Added]: Used to indicate addition of new features
- [Changed]: Updates of existing functionalities
- [Deprecated]: Functionalities / features removed in future releases
- [Removed]: Functionalities / features removed in this release
- [Fixed]: For any bug fixes
- [Breaking] This functionality breaks the previous API and you need to check your code
Installation and project structure
- [Added] Automated wheel creation with cmake
- [Added] Automated make conda-package generation
- [Added] Support for arm(jetson tx2) platform (Thanks kuonangzhe!)
- [Fixed] Cmake install to solve problems with 3rd party header path
- [Fixed] glfw linking issue when built from source
- [Fixed] Bug in Ubuntu for the default install path
CORE features and applications
- [Added] RealSense support for live synchronized RGB-D capture (Thanks baptiste-mnh and LLDavid)
- [Added] Integration with Jupyter visualization WebGL widgets
- [Added] New methods for outliers removal: statistical outlier removal and radius outlier removal (Thanks Nicolas Chaulet!)
- [Added] Open3D-PointNet repository to Open3D Ecosystem
- [Fixed] Problem with the ENABLE_HEADLESS_RENDERING flag
- [Added] “Visible” parameter to Visualizer::CreateVisualizerWindow to enable off-screen windows
- [Added] Stanford dataset for 3D reconstruction system
- [Changed] Major update of the 3D reconstruction system to improve usability and robustness
Documentation and tutorials
- [Added] RealSense support documentation
- [Added] Jupyter examples to run PointNet using Open3D for point cloud classification
Testing and benchmarking
- [Added] Consistent Random number generation initialization (compiler independent)
- [Added] TravisCI support to automatic UnitTest evaluation
- [Added] PointCloud test cases
- [Added] TriangleMesh test cases
- [Added] LineSet test cases
- [Added] RGBDImage test cases
- [Added] KDTreeFlann test cases