CloudCompare | CloudCompare main repository | Image Editing library

by CloudCompare C++ Version: v2.13.alpha.230227 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | CloudCompare Summary

CloudCompare is a C++ library typically used in Media, Image Editing applications. CloudCompare has no bugs, it has no vulnerabilities and it has medium support. However CloudCompare has a Non-SPDX License. You can download it from GitHub.

CloudCompare main repository

Support

Quality

Security

License

Reuse

Support

CloudCompare has a medium active ecosystem.

It has 2750 star(s) with 931 fork(s). There are 132 watchers for this library.

It had no major release in the last 12 months.

There are 190 open issues and 771 have been closed. On average issues are closed in 25 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of CloudCompare is v2.13.alpha.230227

Quality

CloudCompare has 0 bugs and 0 code smells.

Security

CloudCompare has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

CloudCompare code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

CloudCompare has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

CloudCompare releases are available to install and integrate.

Installation instructions are available. Examples and code snippets are not available.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of CloudCompare

Get all kandi verified functions for this library.

CloudCompare Key Features

No Key Features are available at this moment for CloudCompare.

CloudCompare Examples and Code Snippets

No Code Snippets are available at this moment for CloudCompare.

Community Discussions

Trending Discussions on CloudCompare

How to specify boundary condition as DIRICHLET in pcl poisson surface reconstruction?

Compute eigenvalues for large point clouds as quickly as possible with R

Transform 3D Lidar-Points from cartesian coordinate-system to spherical coordinate-system and a stereographic projection

QUESTION

How to specify boundary condition as DIRICHLET in pcl poisson surface reconstruction?

Asked 2021-Dec-07 at 16:36

I'm doing a job of surface reconstruction. But I met an issue :

I want to use the DIRICHLET boundary condition in poisson, but it seems that the poisson of pcl doesn't support specifying boundary condition, it just uses NEUMANN boundary condition always.

So I wonder how to use the DIRICHLET boundary condition in pcl poisson.

BTW：My goal is to calculate the volume of a container. But my pointcloud isn't watertight, so I need the algorithm to 'image' the surface of holes. CloudCompare supports specifying boundary condition, and it works well. But in pcl, the effect of NEUMANN boundary condition is terrible.

The mesh generated by pcl poisson(NEUMANN condition) like below:
The mesh generated by cloudcompare(specified DIRICHLET condition) like below:

...

ANSWER

Answered 2021-Dec-07 at 16:36

The original PoissonRecon code is at this github repository. You can also find there prebuild executables for window command line (--bType to set the conidtion). This is available in the command line executable starting from version 9.0.

[--bType ] This integer specifies the boundary type for the finite elements. Valid values are: 1: Free boundary constraints 2: Dirichlet boundary constraints 3: Neumann boundary constraints The default value for this parameter is 3 (Neumann).

CloudCompare uses version 7.

PCL (1.12.0 at the moment of this post) uses version 4 of PoissonRecon.

Open3D (0.14.1 at the moment of this post) includes a wrapper over version 12, which supports both boundary conditions. It is however hard-coded to use NEUMANN. You should be able to easily change the enum and compile a version of Open3D that uses DIRICHLET condition (never tried this myself).

Alternatively (if you can't use the original console app or recompile Open3D), you can try to work with what you've got.

You can try to identify the "imaginary faces" based on the area of the faces (smaller density - larger triangle area) and remove them. The original repository offers a SurfaceTrimmer tool (another console project) that does just that (based on density value).
Close the remaining open mesh using either some hole-closing-method or convex-hull.

Source https://stackoverflow.com/questions/70195911

QUESTION

Compute eigenvalues for large point clouds as quickly as possible with R

Asked 2021-May-02 at 11:41

I have large point clouds (each with several million points) and want to compute geometric attributes for all points. In order to do so, I need to calculate eigenvalues. How can I do this as quickly as possible? My data is stored in *.las files and I read them in with the package lidR. I also use this package to calculate point metrics. According to this post, I implemented this version:

...

ANSWER

Answered 2021-May-02 at 11:41

The problem of point_metrics() is that it calls user's R code millions of times and this have a cost. Moreover it cannot be safely multithreaded. The function is good for prototyping but for production you must write your own code. For example you can reproduce the function segment_shape() with point_metrics() but segment_shape() is pure C++ and multi-threaded and is often an order of magnitude faster.

Let try with ~3 millions points. The two examples are not equivalent (different output) but the computation load is almost the same (eigen value decomposition).

Source https://stackoverflow.com/questions/67347461

QUESTION

Transform 3D Lidar-Points from cartesian coordinate-system to spherical coordinate-system and a stereographic projection

Asked 2020-Sep-25 at 13:35

I'm working on my master thesis to simulate hemispherical photographs from Lidar-Data. So my main goal is to project 3D Points (X,Y,Z) which are in a cartesian coordinate system to a stereographic projection (See picture 1, from: here). The coordinate-system of my Pointcloud is transformed so that the center point is located a (0,0,0) and all z-values are positive.

I'm coding in RStudio and I first tried to achieve a spherical projection of the Pointcloud by using the formula for cartesian to spherical coordinates listed on wikipedia.

...

ANSWER

Answered 2020-Sep-25 at 08:27

It's difficult to show this result in 3D, but I'll try my best.

Suppose we have a collection of points in the shape of a cross suspended over the camera, paralell to the ground:

Source https://stackoverflow.com/questions/64046096

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install CloudCompare

Linux: - Flathub: https://flathub.org/apps/details/org.cloudcompare.CloudCompare ``` flatpak install flathub org.cloudcompare.CloudCompare ``` - snapcraft: https://snapcraft.io/cloudcompare ``` sudo snap install cloudcompare ```.