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constants.hpp
cv_utils.cpp
cv_utils.cpp
cv_utils.hpp
cv_utils.hpp
kdtree_tensor.cpp
kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
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ssim.hpp
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tile_bounds.hpp
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utils.cpp
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Repository files navigation

💦 OpenSplat

A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.

OpenSplat

OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.

Commercial use allowed and encouraged under the terms of the AGPLv3. ✅

Build

Requirements:

Then:

git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)

The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).

Run

To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]

Then run:

./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply

The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor

To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html

We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1

There's several parameters you can tune. To view the full list:

./opensplat --help

Project Goals

We recently released OpenSplat, so there's lots of work to do.

  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?

https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement

Contributing

We welcome contributions! Pull requests are welcome.

GPU Memory Notes

A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.

Credits

The methods used in OpenSplat are originally based on splatfacto.

License

The code in this repository, unless otherwise noted, is licensed under the AGPLv3.

The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.

About

Free and open source 3D gaussian splatting in C++ 💦

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var __re = new RegExp('^' + "github\\.com" + '

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constants.hpp
cv_utils.cpp
cv_utils.cpp
cv_utils.hpp
cv_utils.hpp
kdtree_tensor.cpp
kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
ssim.cpp
ssim.hpp
ssim.hpp
tile_bounds.hpp
tile_bounds.hpp
utils.cpp
utils.cpp
utils.hpp
utils.hpp
Repository files navigation
💦 OpenSplat
A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.
OpenSplat
OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.
Commercial use allowed and encouraged under the terms of the AGPLv3. ✅
Build
Requirements:
Then:
git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)
The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).
Run
To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]
Then run:
./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply
The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor
To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html
We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1
There's several parameters you can tune. To view the full list:
./opensplat --help
Project Goals
We recently released OpenSplat, so there's lots of work to do.
  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?
https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
Contributing
We welcome contributions! Pull requests are welcome.
GPU Memory Notes
A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.
Credits
The methods used in OpenSplat are originally based on splatfacto.
License
The code in this repository, unless otherwise noted, is licensed under the AGPLv3.
The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.
About
Free and open source 3D gaussian splatting in C++ 💦
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Readme
License
Activity
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constants.hpp
cv_utils.cpp
cv_utils.cpp
cv_utils.hpp
cv_utils.hpp
kdtree_tensor.cpp
kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
ssim.cpp
ssim.hpp
ssim.hpp
tile_bounds.hpp
tile_bounds.hpp
utils.cpp
utils.cpp
utils.hpp
utils.hpp
Repository files navigation
💦 OpenSplat
A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.
OpenSplat
OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.
Commercial use allowed and encouraged under the terms of the AGPLv3. ✅
Build
Requirements:
Then:
git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)
The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).
Run
To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]
Then run:
./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply
The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor
To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html
We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1
There's several parameters you can tune. To view the full list:
./opensplat --help
Project Goals
We recently released OpenSplat, so there's lots of work to do.
  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?
https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
Contributing
We welcome contributions! Pull requests are welcome.
GPU Memory Notes
A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.
Credits
The methods used in OpenSplat are originally based on splatfacto.
License
The code in this repository, unless otherwise noted, is licensed under the AGPLv3.
The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.
About
Free and open source 3D gaussian splatting in C++ 💦
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injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
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constants.hpp
cv_utils.cpp
cv_utils.cpp
cv_utils.hpp
cv_utils.hpp
kdtree_tensor.cpp
kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
ssim.cpp
ssim.hpp
ssim.hpp
tile_bounds.hpp
tile_bounds.hpp
utils.cpp
utils.cpp
utils.hpp
utils.hpp
Repository files navigation
💦 OpenSplat
A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.
OpenSplat
OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.
Commercial use allowed and encouraged under the terms of the AGPLv3. ✅
Build
Requirements:
Then:
git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)
The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).
Run
To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]
Then run:
./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply
The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor
To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html
We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1
There's several parameters you can tune. To view the full list:
./opensplat --help
Project Goals
We recently released OpenSplat, so there's lots of work to do.
  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?
https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
Contributing
We welcome contributions! Pull requests are welcome.
GPU Memory Notes
A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.
Credits
The methods used in OpenSplat are originally based on splatfacto.
License
The code in this repository, unless otherwise noted, is licensed under the AGPLv3.
The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.
About
Free and open source 3D gaussian splatting in C++ 💦
Resources
Readme
License
Activity
Stars
1 star
Watchers
0 watching
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0 forks
Report repository
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injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
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var __m = "youtube.com";
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constants.hpp
cv_utils.cpp
cv_utils.cpp
cv_utils.hpp
cv_utils.hpp
kdtree_tensor.cpp
kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
ssim.cpp
ssim.hpp
ssim.hpp
tile_bounds.hpp
tile_bounds.hpp
utils.cpp
utils.cpp
utils.hpp
utils.hpp
Repository files navigation
💦 OpenSplat
A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.
OpenSplat
OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.
Commercial use allowed and encouraged under the terms of the AGPLv3. ✅
Build
Requirements:
Then:
git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)
The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).
Run
To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]
Then run:
./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply
The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor
To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html
We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1
There's several parameters you can tune. To view the full list:
./opensplat --help
Project Goals
We recently released OpenSplat, so there's lots of work to do.
  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?
https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
Contributing
We welcome contributions! Pull requests are welcome.
GPU Memory Notes
A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.
Credits
The methods used in OpenSplat are originally based on splatfacto.
License
The code in this repository, unless otherwise noted, is licensed under the AGPLv3.
The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.
About
Free and open source 3D gaussian splatting in C++ 💦
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injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
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})();
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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constants.hpp
constants.hpp
cv_utils.cpp
cv_utils.cpp
cv_utils.hpp
cv_utils.hpp
kdtree_tensor.cpp
kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
ssim.cpp
ssim.hpp
ssim.hpp
tile_bounds.hpp
tile_bounds.hpp
utils.cpp
utils.cpp
utils.hpp
utils.hpp
Repository files navigation
💦 OpenSplat
A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.
OpenSplat
OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.
Commercial use allowed and encouraged under the terms of the AGPLv3. ✅
Build
Requirements:
Then:
git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)
The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).
Run
To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]
Then run:
./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply
The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor
To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html
We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1
There's several parameters you can tune. To view the full list:
./opensplat --help
Project Goals
We recently released OpenSplat, so there's lots of work to do.
  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?
https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
Contributing
We welcome contributions! Pull requests are welcome.
GPU Memory Notes
A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.
Credits
The methods used in OpenSplat are originally based on splatfacto.
License
The code in this repository, unless otherwise noted, is licensed under the AGPLv3.
The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.
About
Free and open source 3D gaussian splatting in C++ 💦
Resources
Readme
License
Activity
Stars
1 star
Watchers
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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README.md
constants.hpp
constants.hpp
cv_utils.cpp
cv_utils.cpp
cv_utils.hpp
cv_utils.hpp
kdtree_tensor.cpp
kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
ssim.cpp
ssim.hpp
ssim.hpp
tile_bounds.hpp
tile_bounds.hpp
utils.cpp
utils.cpp
utils.hpp
utils.hpp
Repository files navigation
💦 OpenSplat
A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.
OpenSplat
OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.
Commercial use allowed and encouraged under the terms of the AGPLv3. ✅
Build
Requirements:
Then:
git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)
The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).
Run
To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]
Then run:
./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply
The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor
To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html
We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1
There's several parameters you can tune. To view the full list:
./opensplat --help
Project Goals
We recently released OpenSplat, so there's lots of work to do.
  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?
https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
Contributing
We welcome contributions! Pull requests are welcome.
GPU Memory Notes
A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.
Credits
The methods used in OpenSplat are originally based on splatfacto.
License
The code in this repository, unless otherwise noted, is licensed under the AGPLv3.
The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.
About
Free and open source 3D gaussian splatting in C++ 💦
Resources
Readme
License
Activity
Stars
1 star
Watchers
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0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
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cv_utils.cpp
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cv_utils.hpp
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kdtree_tensor.cpp
kdtree_tensor.hpp
kdtree_tensor.hpp
model.cpp
model.cpp
model.hpp
model.hpp
nerfstudio.cpp
nerfstudio.cpp
nerfstudio.hpp
nerfstudio.hpp
opensplat.cpp
opensplat.cpp
opensplat.hpp
opensplat.hpp
optim_scheduler.cpp
optim_scheduler.cpp
optim_scheduler.hpp
optim_scheduler.hpp
point_io.cpp
point_io.cpp
point_io.hpp
point_io.hpp
project_gaussians.cpp
project_gaussians.cpp
project_gaussians.hpp
project_gaussians.hpp
rasterize_gaussians.cpp
rasterize_gaussians.cpp
rasterize_gaussians.hpp
rasterize_gaussians.hpp
simple_trainer.cpp
simple_trainer.cpp
spherical_harmonics.cpp
spherical_harmonics.cpp
spherical_harmonics.hpp
spherical_harmonics.hpp
ssim.cpp
ssim.cpp
ssim.hpp
ssim.hpp
tile_bounds.hpp
tile_bounds.hpp
utils.cpp
utils.cpp
utils.hpp
utils.hpp
Repository files navigation
💦 OpenSplat
A free and open source implementation of 3D gaussian splatting written in C++, focused on being portable, lean and fast.
OpenSplat
OpenSplat takes camera poses + sparse points and computes a scene file (.ply) that can be later imported for viewing, editing and rendering in other software.
Commercial use allowed and encouraged under the terms of the AGPLv3. ✅
Build
Requirements:
Then:
git clone https://github.com/pierotofy/OpenSplat OpenSplat
cd OpenSplat
mkdir build &&cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/libtorch/ .. && make -j$(nproc)
The software has been tested on Ubuntu 20.04 and Windows. With some changes it could run on macOS (help us by opening a PR?).
Run
To get started, download a dataset and extract it to a folder: [ banana ] [ train ] [ truck ]
Then run:
./opensplat /path/to/banana -n 2000
[...]
Wrote splat.ply
The output splat.ply can then be dragged and dropped in one of the many viewers such as https://playcanvas.com/viewer. You can also edit/cleanup the scene using https://playcanvas.com/supersplat/editor
To run on your own data, choose the path to an existing nerfstudio project. The project must have sparse points included (random initialization is not supported, see WebODM#7). You can generate nerfstudio projects from COLMAP by using nerfstudio's ns-process-data command: https://docs.nerf.studio/quickstart/custom_dataset.html
We have plans to add support for reading COLMAP projects directly in the near future. See WebODM#1
There's several parameters you can tune. To view the full list:
./opensplat --help
Project Goals
We recently released OpenSplat, so there's lots of work to do.
  • Support for running on AMD cards
  • Support for running on CPU-only
  • Improve speed / reduce memory usage
  • Distributed computation using multiple machines
  • Real-time training viewer output
  • Compressed scene outputs
  • Your ideas?
https://github.com/pierotofy/OpenSplat/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
Contributing
We welcome contributions! Pull requests are welcome.
GPU Memory Notes
A single gaussian takes ~2000 bytes of memory, so currenly you need ~2GB of GPU memory for each million gaussians.
Credits
The methods used in OpenSplat are originally based on splatfacto.
License
The code in this repository, unless otherwise noted, is licensed under the AGPLv3.
The code from splatfacto is originally licensed under the Apache 2.0 license and is © 2023 The Nerfstudio Team.
About
Free and open source 3D gaussian splatting in C++ 💦
Resources
Readme
License
Activity
Stars
1 star
Watchers
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0 forks
Report repository
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