Metadata-Version: 2.1
Name: cupoch
Version: 0.2.11.0
Summary: ['Cupoch: Robotics with GPU computing']
Home-page: https://github.com/neka-nat/cupoch
Author: neka-nat
Author-email: nekanat.stock@gmail.com
License: MIT
Project-URL: Documentation, https://github.com/neka-nat/cupoch
Project-URL: Source code, https://github.com/neka-nat/cupoch
Project-URL: Issues, https://github.com/neka-nat/cupoch/issues
Keywords: robotics point-cloud mesh RGB-D collision visualization
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Win32 (MS Windows)
Classifier: Environment :: X11 Applications
Classifier: Framework :: Robot Framework
Classifier: Framework :: Robot Framework :: Library
Classifier: Framework :: Robot Framework :: Tool
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: C
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Education
Classifier: Topic :: Multimedia :: Graphics :: 3D Rendering
Classifier: Topic :: Multimedia :: Graphics :: Viewers
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: wheel

# Cupoch

## Core features

* 3D data processing and robotics computation using CUDA
    * KNN
        * [Optimizing LBVH-Construction and Hierarchy-Traversal to accelerate kNN Queries on Point Clouds using the GPU](https://epub.uni-bayreuth.de/5288/1/cgf.14177.pdf)
    * Point cloud registration
        * ICP
        * [Colored Point Cloud Registration](https://ieeexplore.ieee.org/document/8237287)
        * [Fast Global Registration](http://vladlen.info/papers/fast-global-registration.pdf)
        * [FilterReg](https://arxiv.org/abs/1811.10136)
    * Point cloud features
        * FPFH
        * SHOT
    * Point cloud keypoints
        * ISS
    * Point cloud clustering
        * [G-DBSCAN: A GPU Accelerated Algorithm for Density-based Clustering](https://www.sciencedirect.com/science/article/pii/S1877050913003438)
    * Point cloud/Triangle mesh filtering, down sampling
    * IO
        * Several file types(pcd, ply, stl, obj, urdf)
        * ROS message
    * Create Point Cloud from Laser Scan or RGBD Image
    * Visual Odometry
        * [Real-time visual odometry from dense RGB-D images](https://ieeexplore.ieee.org/document/6130321)
        * [Robust Odometry Estimation for RGB-D Cameras](https://ieeexplore.ieee.org/document/6631104)
    * Kinect Fusion
    * Stereo Matching
    * Collision checking
    * Occupancy grid
    * Distance transform
        * [Parallel Banding Algorithm to Compute Exact Distance Transform with the GPU](https://www.comp.nus.edu.sg/~tants/pba.html)
    * Path finding on graph structure
    * Path planning for collision avoidance
* Support memory pool and managed allocators
* Interactive GUI (OpenGL CUDA interop and [imgui](https://github.com/ocornut/imgui))
* Interoperability between cupoch 3D data and [DLPack](https://github.com/dmlc/dlpack)(Pytorch, Cupy,...) data structure

## Supported platforms

* Ubuntu 18.04
* Windows 10

With Python version: * 3.6 * 3.7 * 3.8 * 3.9

and CUDA version: * 10.1 * 10.2 (Ubuntu) * 11.0 (Windows)

## Resources

* https://github.com/neka-nat/cupoch
