| Name | vedo JSON |
| Version |
2025.5.3
JSON |
| download |
| home_page | None |
| Summary | A python module for scientific visualization, analysis of 3D objects and point clouds. |
| upload_time | 2025-01-30 13:12:44 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | MIT License
Copyright (c) 2017 Marco Musy
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
|
| keywords |
vtk
numpy
3d
visualization
mesh
volume
point-cloud
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://en.wikipedia.org/wiki/MIT_License)
[](https://anaconda.org/conda-forge/vedo)
[](https://repology.org/project/vedo/versions)
[](https://doi.org/10.5281/zenodo.4587871)
[](https://pepy.tech/project/vedo)
[](https://circleci.com/gh/marcomusy/vedo)
Your friendly python module
for scientific analysis and **v**isualization of **3d** **o**bjects.<br>
## 💾 Installation
```bash
pip install vedo
```
<details>
<summary>additional installation details <i><b>[click to expand]</b></i> </summary>
- To install the latest _dev_ version of `vedo`:
```bash
pip install -U git+https://github.com/marcomusy/vedo.git
```
- To install from the conda-forge channel:
```bash
conda install -c conda-forge vedo
```
</details>
## 📙 Documentation
The webpage of the library with documentation is available [**here**](https://vedo.embl.es).
📌 **Need help? Have a question, or wish to ask for a missing feature?**
Do not hesitate to ask any questions on the [**image.sc** forum](https://forum.image.sc/)
or by opening a [**github issue**](https://github.com/marcomusy/vedo/issues).
## 🎨 Features
The library includes a [large set of working examples](https://github.com/marcomusy/vedo/tree/master/examples)
for a wide range of functionalities
<details>
<summary>working with polygonal meshes and point clouds <i><b>[click to expand]</b></i> </summary>
<i>
- Import meshes from VTK format, STL, Wavefront OBJ, 3DS, Dolfin-XML, Neutral, GMSH, OFF, PCD (PointCloud),
- Export meshes as ASCII or binary to VTK, STL, OBJ, PLY ... formats.
- Analysis tools like Moving Least Squares, mesh morphing and more..
- Tools to visualize and edit meshes (cutting a mesh with another mesh, slicing, normalizing, moving vertex positions, etc..).
- Split mesh based on surface connectivity. Extract the largest connected area.
- Calculate areas, volumes, center of mass, average sizes etc.
- Calculate vertex and face normals, curvatures, feature edges. Fill mesh holes.
- Subdivide faces of a mesh, increasing the number of vertex points. Mesh simplification.
- Coloring and thresholding of meshes based on associated scalar or vectorial data.
- Point-surface operations: find nearest points, determine if a point lies inside or outside of a mesh.
- Create primitive shapes: spheres, arrows, cubes, torus, ellipsoids...
- Generate glyphs (associate a mesh to every vertex of a source mesh).
- Create animations easily by just setting the position of the displayed objects in the 3D scene. Add trailing lines and shadows to moving objects is supported.
- Straightforward support for multiple sync-ed or independent renderers in the same window.
- Registration (alignment) of meshes with different techniques.
- Mesh smoothing.
- Delaunay triangulation in 2D and 3D.
- Generate meshes by joining nearby lines in space.
- Find the closest path from one point to another, traveling along the edges of a mesh.
- Find the intersection of a mesh with lines, planes or other meshes.
- Interpolate scalar and vectorial fields with Radial Basis Functions and Thin Plate Splines.
- Add sliders and buttons to interact with the scene and the individual objects.
- Visualization of tensors.
- Analysis of Point Clouds
- Moving Least Squares smoothing of 2D, 3D and 4D clouds
- Fit lines, planes, spheres and ellipsoids in space
- Identify outliers in a distribution of points
- Decimate a cloud to a uniform distribution.
</i>
</details>
<details>
<summary>working with volumetric data and tetrahedral meshes</summary>
<i>
- Import data from VTK format volumetric TIFF stacks, DICOM, SLC, MHD and more
- Import 2D images as PNG, JPEG, BMP
- Isosurfacing of volumes
- Composite and maximum projection volumetric rendering
- Generate volumetric signed-distance data from an input surface mesh
- Probe volumes with lines and planes
- Generate stream-lines and stream-tubes from vectorial fields
- Slice and crop volumes
- Support for other volumetric structures (structured and grid data)
</i>
</details>
<details>
<summary>plotting and histogramming in 2D and 3D</summary>
<i>
- Polygonal 3D text rendering with Latex-like syntax and unicode characters, with 30 different fonts.
- Fully customizable axis styles
- donut plots and pie charts
- Scatter plots in 2D and 3D
- Surface function plotting
- 1D customizable histograms
- 2D hexagonal histograms
- Polar plots, spherical plots and histogramming
- Draw latex-formatted formulas in the rendering window.
- Quiver, violin, whisker and stream-line plots
- Graphical markers analogous to matplotlib
</i>
</details>
<details>
<summary>integration with other libraries</summary>
<i>
- Integration with the [Qt5](https://www.qt.io/) framework.
- Support for [FEniCS/Dolfin](https://fenicsproject.org/) platform for visualization of PDE/FEM solutions.
- Interoperability with the [trimesh](https://trimsh.org/), [pyvista](https://github.com/pyvista/pyvista) and [pymeshlab](https://github.com/cnr-isti-vclab/PyMeshLab) libraries.
- Export 3D scenes and embed them into a [web page](https://vedo.embl.es/examples/fenics_elasticity.html).
- Embed 3D scenes in *jupyter* notebooks with [K3D](https://github.com/K3D-tools/K3D-jupyter) (can export an interactive 3D-snapshot page [here](https://vedo.embl.es/examples/geo_scene.html)).
</i>
</details>
### ⌨ Command Line Interface
Visualize a polygonal mesh or a volume from a terminal window simply with:
```bash
vedo https://vedo.embl.es/examples/data/embryo.tif
```
<details>
<summary>volumetric files (slc, tiff, DICOM...) can be visualized in different modes <i><b>[click to expand]</b></i> </summary>
|Volume 3D slicing<br>`vedo --slicer embryo.slc`| Ray-casting<br>`vedo -g`| 2D slicing<br>`vedo --slicer2d`|
|:--------|:-----|:--------|
|  |  |  |
</details>
Type `vedo -h` for the complete list of options.<br>
## 🐾 Gallery
`vedo` currently includes 300+ working [examples](https://github.com/marcomusy/vedo/tree/master/examples) and [notebooks](https://github.com/marcomusy/vedo/tree/master/examples/notebooks). <br>
Run any of the built-in examples. In a terminal type: `vedo -r warp2`
Check out the example galleries organized by subject here:
<a href="https://vedo.embl.es/#gallery" target="_blank">
</a>
## ✏ Contributing
Any contributions are **greatly appreciated**!
If you have a suggestion that would make this better,
please fork the repo and create a pull request. This is how:
```bash
# 1. Fork the repository on GitHub then clone your fork locally:
git clone https://github.com/your-username/vedo.git
# 2. Create a new branch for your feature or bugfix:
git checkout -b feature/my-feature
# 3. Make your changes and commit them:
git commit -m "Description of my feature"
# 4. Push your changes to your fork:
git push origin feature/my-feature
# 5. Open a Pull Request on the main repository.
```
You can also simply open an issue with the tag "enhancement".
## 📜 References
**Scientific publications leveraging `vedo`:**
- X. Diego *et al.*:
*"Key features of Turing systems are determined purely by network topology"*,
Phys. Rev. X 8, 021071,
[DOI](https://journals.aps.org/prx/abstract/10.1103/PhysRevX.8.021071).
- M. Musy, K. Flaherty *et al.*:
*"A Quantitative Method for Staging Mouse Limb Embryos based on Limb Morphometry"*,
Development (2018) 145 (7): dev154856,
[DOI](http://dev.biologists.org/content/145/7/dev154856).
- F. Claudi, A. L. Tyson, T. Branco, *"Brainrender. A python based software for visualisation
of neuroanatomical and morphological data."*,
eLife 2021;10:e65751,
[DOI](https://doi.org/10.7554/eLife.65751).
- J. S. Bennett, D. Sijacki,
*"Resolving shocks and filaments in galaxy formation simulations: effects on gas properties and
star formation in the circumgalactic medium"*,
Monthly Notices of the Royal Astronomical Society, Volume 499, Issue 1,
[DOI](https://doi.org/10.1093/mnras/staa2835).
- J.D.P. Deshapriya *et al.*,
*"Spectral analysis of craters on (101955) Bennu"*.
Icarus 2020,
[DOI](https://doi.org/10.1016/j.icarus.2020.114252).
- A. Pollack *et al.*,
*"Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data
for geologically realistic structural models: Patua Geothermal Field case study"*,
Geothermics, Volume 95, September 2021,
[DOI](https://doi.org/10.1016/j.geothermics.2021.102129).
- X. Lu *et al.*,
*"3D electromagnetic modeling of graphitic faults in the Athabasca
Basin using a finite-volume time-domain approach with unstructured grids"*,
Geophysics,
[DOI](https://doi.org/10.1190/geo2020-0657.1).
- M. Deepa Maheshvare *et al.*,
*"A Graph-Based Framework for Multiscale Modeling of Physiological Transport"*,
Front. Netw. Physiol. 1:802881,
[DOI](https://www.frontiersin.org/articles/10.3389/fnetp.2021.802881/full).
- F. Claudi, T. Branco,
*"Differential geometry methods for constructing manifold-targeted recurrent neural networks"*,
bioRxiv 2021.10.07.463479,
[DOI](https://doi.org/10.1101/2021.10.07.463479).
- J. Klatzow, G. Dalmasso, N. Martínez-Abadías, J. Sharpe, V. Uhlmann,
*"µMatch: 3D shape correspondence for microscopy data"*,
Front. Comput. Sci., 15 February 2022.
[DOI](https://doi.org/10.3389/fcomp.2022.777615)
- G. Dalmasso *et al.*, *"4D reconstruction of murine developmental trajectories using spherical harmonics"*,
Developmental Cell 57, 1–11 September 2022,
[DOI](https://doi.org/10.1016/j.devcel.2022.08.005).
- D.J.E Waibel *et al.*, *"Capturing Shape Information with Multi-scale Topological Loss Terms for 3D Reconstruction"*,
Lecture Notes in Computer Science, vol 13434. Springer, Cham.
[DOI](https://doi.org/10.1007/978-3-031-16440-8_15).
- N. Lamb *et al.*, *"DeepJoin: Learning a Joint Occupancy, Signed Distance, and Normal Field Function for Shape Repair"*,
ACM Transactions on Graphics (TOG), vol 41, 6, 2022.
[DOI](https://dl.acm.org/doi/abs/10.1145/3550454.3555470)
- J. Cotterell *et al.*, *"Cell 3D Positioning by Optical encoding (C3PO) and its application to spatial transcriptomics"*, bioRxiv 2024.03.12.584578;
[DOI](https://doi.org/10.1101/2024.03.12.584578)
**Have you found this software useful for your research? Star ✨ the project and cite it as:**
M. Musy <em>et al.</em>,
"<code>vedo</code>, a python module for scientific analysis and visualization of 3D objects and point clouds",
Zenodo, 2021, <a href="https://doi.org/10.5281/zenodo.7019968">doi: 10.5281/zenodo.7019968</a>.
[](https://www.embl.es)
Raw data
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"requires_python": ">=3.7",
"maintainer_email": "Marco Musy <marco.musy@embl.es>",
"keywords": "vtk, numpy, 3d, visualization, mesh, volume, point-cloud",
"author": null,
"author_email": "Marco Musy <marco.musy@embl.es>",
"download_url": "https://files.pythonhosted.org/packages/44/49/20397d87790a2be57b6e639e50efa9827d83ce328cb6cd1a0e183f46ce64/vedo-2025.5.3.tar.gz",
"platform": null,
"description": "\n\n\n\n[](https://en.wikipedia.org/wiki/MIT_License)\n[](https://anaconda.org/conda-forge/vedo)\n[](https://repology.org/project/vedo/versions)\n[](https://doi.org/10.5281/zenodo.4587871)\n[](https://pepy.tech/project/vedo)\n[](https://circleci.com/gh/marcomusy/vedo)\n\n\nYour friendly python module\nfor scientific analysis and **v**isualization of **3d** **o**bjects.<br>\n\n\n## \ud83d\udcbe Installation\n```bash\npip install vedo\n```\n\n<details>\n<summary>additional installation details <i><b>[click to expand]</b></i> </summary>\n\n- To install the latest _dev_ version of `vedo`:\n\n```bash\npip install -U git+https://github.com/marcomusy/vedo.git\n```\n\n\n- To install from the conda-forge channel:\n\n```bash\nconda install -c conda-forge vedo\n```\n\n</details>\n\n\n## \ud83d\udcd9 Documentation\nThe webpage of the library with documentation is available [**here**](https://vedo.embl.es).\n\n\ud83d\udccc **Need help? Have a question, or wish to ask for a missing feature?**\nDo not hesitate to ask any questions on the [**image.sc** forum](https://forum.image.sc/)\nor by opening a [**github issue**](https://github.com/marcomusy/vedo/issues).\n\n\n## \ud83c\udfa8 Features\nThe library includes a [large set of working examples](https://github.com/marcomusy/vedo/tree/master/examples)\nfor a wide range of functionalities\n\n<details>\n<summary>working with polygonal meshes and point clouds <i><b>[click to expand]</b></i> </summary>\n<i>\n\n- Import meshes from VTK format, STL, Wavefront OBJ, 3DS, Dolfin-XML, Neutral, GMSH, OFF, PCD (PointCloud),\n- Export meshes as ASCII or binary to VTK, STL, OBJ, PLY ... formats.\n- Analysis tools like Moving Least Squares, mesh morphing and more..\n- Tools to visualize and edit meshes (cutting a mesh with another mesh, slicing, normalizing, moving vertex positions, etc..).\n- Split mesh based on surface connectivity. Extract the largest connected area.\n- Calculate areas, volumes, center of mass, average sizes etc.\n- Calculate vertex and face normals, curvatures, feature edges. Fill mesh holes.\n- Subdivide faces of a mesh, increasing the number of vertex points. Mesh simplification.\n- Coloring and thresholding of meshes based on associated scalar or vectorial data.\n- Point-surface operations: find nearest points, determine if a point lies inside or outside of a mesh.\n- Create primitive shapes: spheres, arrows, cubes, torus, ellipsoids...\n- Generate glyphs (associate a mesh to every vertex of a source mesh).\n- Create animations easily by just setting the position of the displayed objects in the 3D scene. Add trailing lines and shadows to moving objects is supported.\n- Straightforward support for multiple sync-ed or independent renderers in the same window.\n- Registration (alignment) of meshes with different techniques.\n- Mesh smoothing.\n- Delaunay triangulation in 2D and 3D.\n- Generate meshes by joining nearby lines in space.\n- Find the closest path from one point to another, traveling along the edges of a mesh.\n- Find the intersection of a mesh with lines, planes or other meshes.\n- Interpolate scalar and vectorial fields with Radial Basis Functions and Thin Plate Splines.\n- Add sliders and buttons to interact with the scene and the individual objects.\n- Visualization of tensors.\n- Analysis of Point Clouds\n- Moving Least Squares smoothing of 2D, 3D and 4D clouds\n- Fit lines, planes, spheres and ellipsoids in space\n- Identify outliers in a distribution of points\n- Decimate a cloud to a uniform distribution.\n\n</i>\n</details>\n\n<details>\n<summary>working with volumetric data and tetrahedral meshes</summary>\n<i>\n\n- Import data from VTK format volumetric TIFF stacks, DICOM, SLC, MHD and more\n- Import 2D images as PNG, JPEG, BMP\n- Isosurfacing of volumes\n- Composite and maximum projection volumetric rendering\n- Generate volumetric signed-distance data from an input surface mesh\n- Probe volumes with lines and planes\n- Generate stream-lines and stream-tubes from vectorial fields\n- Slice and crop volumes\n- Support for other volumetric structures (structured and grid data)\n\n</i>\n</details>\n\n<details>\n<summary>plotting and histogramming in 2D and 3D</summary>\n<i>\n\n- Polygonal 3D text rendering with Latex-like syntax and unicode characters, with 30 different fonts.\n- Fully customizable axis styles\n- donut plots and pie charts\n- Scatter plots in 2D and 3D\n- Surface function plotting\n- 1D customizable histograms\n- 2D hexagonal histograms\n- Polar plots, spherical plots and histogramming\n- Draw latex-formatted formulas in the rendering window.\n- Quiver, violin, whisker and stream-line plots\n- Graphical markers analogous to matplotlib\n\n</i>\n</details>\n\n<details>\n<summary>integration with other libraries</summary>\n<i>\n\n- Integration with the [Qt5](https://www.qt.io/) framework.\n- Support for [FEniCS/Dolfin](https://fenicsproject.org/) platform for visualization of PDE/FEM solutions.\n- Interoperability with the [trimesh](https://trimsh.org/), [pyvista](https://github.com/pyvista/pyvista) and [pymeshlab](https://github.com/cnr-isti-vclab/PyMeshLab) libraries.\n- Export 3D scenes and embed them into a [web page](https://vedo.embl.es/examples/fenics_elasticity.html).\n- Embed 3D scenes in *jupyter* notebooks with [K3D](https://github.com/K3D-tools/K3D-jupyter) (can export an interactive 3D-snapshot page [here](https://vedo.embl.es/examples/geo_scene.html)).\n\n</i>\n</details>\n\n\n### \u2328 Command Line Interface\nVisualize a polygonal mesh or a volume from a terminal window simply with:\n```bash\nvedo https://vedo.embl.es/examples/data/embryo.tif\n```\n\n\n<details> \n<summary>volumetric files (slc, tiff, DICOM...) can be visualized in different modes <i><b>[click to expand]</b></i> </summary>\n\n\n|Volume 3D slicing<br>`vedo --slicer embryo.slc`| Ray-casting<br>`vedo -g`| 2D slicing<br>`vedo --slicer2d`|\n|:--------|:-----|:--------|\n|  |  |  |\n\n\n</details>\n\n\nType `vedo -h` for the complete list of options.<br>\n\n## \ud83d\udc3e Gallery\n`vedo` currently includes 300+ working [examples](https://github.com/marcomusy/vedo/tree/master/examples) and [notebooks](https://github.com/marcomusy/vedo/tree/master/examples/notebooks). <br>\n\nRun any of the built-in examples. In a terminal type: `vedo -r warp2`\n\nCheck out the example galleries organized by subject here:\n\n<a href=\"https://vedo.embl.es/#gallery\" target=\"_blank\">\n\n\n\n</a>\n\n\n## \u270f Contributing\n\nAny contributions are **greatly appreciated**!\nIf you have a suggestion that would make this better,\nplease fork the repo and create a pull request. This is how:\n```bash\n# 1. Fork the repository on GitHub then clone your fork locally:\ngit clone https://github.com/your-username/vedo.git\n# 2. Create a new branch for your feature or bugfix:\ngit checkout -b feature/my-feature\n# 3. Make your changes and commit them:\ngit commit -m \"Description of my feature\"\n# 4. Push your changes to your fork:\ngit push origin feature/my-feature\n# 5. Open a Pull Request on the main repository.\n```\nYou can also simply open an issue with the tag \"enhancement\".\n\n\n## \ud83d\udcdc References\n\n**Scientific publications leveraging `vedo`:**\n\n- X. Diego *et al.*:\n*\"Key features of Turing systems are determined purely by network topology\"*,\nPhys. Rev. X 8, 021071,\n[DOI](https://journals.aps.org/prx/abstract/10.1103/PhysRevX.8.021071).\n- M. Musy, K. Flaherty *et al.*:\n*\"A Quantitative Method for Staging Mouse Limb Embryos based on Limb Morphometry\"*,\nDevelopment (2018) 145 (7): dev154856,\n[DOI](http://dev.biologists.org/content/145/7/dev154856).\n- F. Claudi, A. L. Tyson, T. Branco, *\"Brainrender. A python based software for visualisation\nof neuroanatomical and morphological data.\"*,\neLife 2021;10:e65751,\n[DOI](https://doi.org/10.7554/eLife.65751).\n- J. S. Bennett, D. Sijacki,\n*\"Resolving shocks and filaments in galaxy formation simulations: effects on gas properties and\nstar formation in the circumgalactic medium\"*,\nMonthly Notices of the Royal Astronomical Society, Volume 499, Issue 1,\n[DOI](https://doi.org/10.1093/mnras/staa2835).\n- J.D.P. Deshapriya *et al.*,\n*\"Spectral analysis of craters on (101955) Bennu\"*.\nIcarus 2020,\n[DOI](https://doi.org/10.1016/j.icarus.2020.114252).\n- A. Pollack *et al.*,\n*\"Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data\nfor geologically realistic structural models: Patua Geothermal Field case study\"*,\nGeothermics, Volume 95, September 2021,\n[DOI](https://doi.org/10.1016/j.geothermics.2021.102129).\n- X. Lu *et al.*,\n*\"3D electromagnetic modeling of graphitic faults in the Athabasca\n Basin using a finite-volume time-domain approach with unstructured grids\"*,\nGeophysics,\n[DOI](https://doi.org/10.1190/geo2020-0657.1).\n- M. Deepa Maheshvare *et al.*,\n*\"A Graph-Based Framework for Multiscale Modeling of Physiological Transport\"*,\nFront. Netw. Physiol. 1:802881,\n[DOI](https://www.frontiersin.org/articles/10.3389/fnetp.2021.802881/full).\n- F. Claudi, T. Branco,\n*\"Differential geometry methods for constructing manifold-targeted recurrent neural networks\"*,\nbioRxiv 2021.10.07.463479,\n[DOI](https://doi.org/10.1101/2021.10.07.463479).\n- J. Klatzow, G. Dalmasso, N. Mart\u00ednez-Abad\u00edas, J. Sharpe, V. Uhlmann,\n*\"\u00b5Match: 3D shape correspondence for microscopy data\"*,\nFront. Comput. Sci., 15 February 2022.\n[DOI](https://doi.org/10.3389/fcomp.2022.777615)\n- G. Dalmasso *et al.*, *\"4D reconstruction of murine developmental trajectories using spherical harmonics\"*,\nDevelopmental Cell 57, 1\u201311 September 2022,\n[DOI](https://doi.org/10.1016/j.devcel.2022.08.005).\n- D.J.E Waibel *et al.*, *\"Capturing Shape Information with Multi-scale Topological Loss Terms for 3D Reconstruction\"*,\nLecture Notes in Computer Science, vol 13434. Springer, Cham. \n[DOI](https://doi.org/10.1007/978-3-031-16440-8_15).\n- N. Lamb *et al.*, *\"DeepJoin: Learning a Joint Occupancy, Signed Distance, and Normal Field Function for Shape Repair\"*,\nACM Transactions on Graphics (TOG), vol 41, 6, 2022.\n[DOI](https://dl.acm.org/doi/abs/10.1145/3550454.3555470)\n- J. Cotterell *et al.*, *\"Cell 3D Positioning by Optical encoding (C3PO) and its application to spatial transcriptomics\"*, bioRxiv 2024.03.12.584578;\n[DOI](https://doi.org/10.1101/2024.03.12.584578)\n\n\n**Have you found this software useful for your research? Star \u2728 the project and cite it as:**\n\nM. Musy <em>et al.</em>,\n\"<code>vedo</code>, a python module for scientific analysis and visualization of 3D objects and point clouds\",\nZenodo, 2021, <a href=\"https://doi.org/10.5281/zenodo.7019968\">doi: 10.5281/zenodo.7019968</a>.\n\n\n[](https://www.embl.es)\n\n\n",
"bugtrack_url": null,
"license": "MIT License\n \n Copyright (c) 2017 Marco Musy\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.\n ",
"summary": "A python module for scientific visualization, analysis of 3D objects and point clouds.",
"version": "2025.5.3",
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