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better docs
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maturk committed Oct 5, 2023
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181 changes: 0 additions & 181 deletions docs/source/_C/cuda.rst

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3 changes: 1 addition & 2 deletions docs/source/apis/proj.rst
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Expand Up @@ -39,5 +39,4 @@ Citations
:style: unsrt
:filter: docname in docnames

.. autoclass:: ProjectGaussians
:members:
.. autoclass:: ProjectGaussians
3 changes: 1 addition & 2 deletions docs/source/apis/rast.rst
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Expand Up @@ -31,5 +31,4 @@ And
:math:`σ ∈ R^{2}` is the Mahalanobis distance (here referred to as sigma) which measures how many standard deviations away the center of a gaussian and the rendered pixel center is which is denoted by delta :math:`∆.`


.. autoclass:: RasterizeGaussians
:members:
.. autoclass:: RasterizeGaussians
18 changes: 18 additions & 0 deletions docs/source/apis/utils.rst
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Utils
===================================
In addition to the main projection and rasterization functions, a few CUDA kernel and helper functions are exposed to python with the following bindings:


.. currentmodule:: diff_rast

.. autoclass:: BinAndSortGaussians

.. autoclass:: ComputeCov2dBounds

.. autoclass:: GetTileBinEdges

.. autoclass:: SphericalHarmonics

.. autoclass:: MapGaussiansToIntersects

.. autoclass:: ComputeCumulativeIntersects
4 changes: 2 additions & 2 deletions docs/source/examples/simple_trainer.rst
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Expand Up @@ -10,7 +10,7 @@ and their differentiability on a single training image. This allows you to overf

Simply run the script with:

.. code-block:: python
.. code-block:: bash
:caption: simple_trainer.py
python examples/simple_trainer.py --height 256 --width 256 --num_points 2000 --save_imgs
Expand All @@ -23,6 +23,6 @@ to get a result similar to the one below:

You can also provide a path to your own custom image file using the ``--img_path`` flag:

.. code-block:: python
.. code-block:: bash
python examples/simple_trainer.py --img_path PATH_TO_IMG --save_imgs
Binary file modified docs/source/imgs/training.gif
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19 changes: 9 additions & 10 deletions docs/source/index.rst
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Expand Up @@ -6,13 +6,19 @@ diff_rast
:alt: Example training image

Overview
-------------
--------

*diff_rast* is an open-source library for CUDA accelerated rasterization of gaussians with python bindings. It is inspired by the SIGGRAPH paper "3D Gaussian Splatting for Real-Time Rendering of Radiance Fields" :cite:p:`kerbl3Dgaussians`.
This libary contains the neccessary components for efficient 3D to 2D projection, sorting, and alpha compositing of gaussians and their associated backward passes for inverse rendering.

Contributing
------------

This repository was born from the curiosity of people on the Nerfstudio team trying to understand a new rendering technique. We welcome contributions of any kind and are open to feedback, bug-reports, and improvements to help expand the capabilities of this software.


Links
------
-----

.. toctree::
:glob:
Expand All @@ -38,21 +44,14 @@ Links
apis/*


.. toctree::
:glob:
:maxdepth: 1
:caption: Cuda Backend

_C/*


.. toctree::
:glob:
:maxdepth: 1
:caption: Tests

tests/*


Citations
-------------
.. bibliography::
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12 changes: 6 additions & 6 deletions docs/source/tests/tests.rst
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Tests
===================================

.. currentmodule:: diff_rast

Testing and verifying CUDA implementations
--------------------------------------------

Expand All @@ -11,12 +9,14 @@ They are also ran with any pull-requests into main branch on our github reposito

The tests include:

.. code-block:: python
.. code-block:: bash
:caption: tests/
./test_project_gaussians.py
./test_map_gaussians.py
./test_cumulative_intersects.py
./test_bin_and_sort_gaussians.py
./test_cov2d_bounds.py
./test_cumulative_intersects.py
./test_get_tile_bin_edges.py
./test_map_gaussians.py
./test_project_gaussians
./test_sh.py

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