Update README

Signed-off-by: Clement Fuji Tsang <cfujitsang@nvidia.com>

README.md

@@ -14,34 +14,31 @@ Note that Kaolin library is part of the larger [NVIDIA Kaolin effort](https://de
 Starting with v0.12.0, Kaolin supports installation with wheels:
 ```
 # Replace TORCH_VERSION and CUDA_VERSION with your torch / cuda versions
-pip install kaolin==0.16.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-{TORCH_VERSION}_cu{CUDA_VERSION}.html
+pip install kaolin==0.17.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-{TORCH_VERSION}_cu{CUDA_VERSION}.html
 ```
-For example, to install kaolin 0.16.0 over torch 2.0.0 and cuda 11.8:
+For example, to install kaolin 0.17.0 over torch 2.0.1 and cuda 11.8:
 ```
-pip install kaolin==0.16.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.0.0_cu118.html
+pip install kaolin==0.17.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.0.1_cu118.html
 ```
 
-## About the Latest Release (0.16.0)
+## About the Latest Release (0.17.0)
 
-In this version we added a [Physics section](https://kaolin.readthedocs.io/en/latest/modules/physics.html).
+In this version we added [sample_points_in_volume](https://kaolin.readthedocs.io/en/latest/modules/kaolin.ops.gaussian.html#kaolin.ops.gaussian.sample_points_in_volume) function used for "densifying" a gaussian splats, this can be used to improve [Physics simulation](https://kaolin.readthedocs.io/en/latest/modules/physics.html).
 
-In this new section we implemented [Simplicits](https://kaolin.readthedocs.io/en/latest/modules/kaolin.physics.html) a geometry-agnostic method for elastic simulation. See more information in [the project page](https://research.nvidia.com/labs/toronto-ai/simplicits/).
+We further improved physics training and simulation using [NVIDIA Warp](https://github.com/NVIDIA/warp) on some of our functions. We also added support for transmittance in the GLTF loader.
 
-We've also added a [math section](https://kaolin.readthedocs.io/en/latest/modules/kaolin.math.html) with quaternions math features.
+![](assets/no_densifier_small.gif) | ![](assets/with_densifier_small.gif)
+:---------------------------------:|:------------------------------------:
+Without Densifier                  |  With Densifier
 
-Finally we've improved workflow, with an [easy rendering API](https://kaolin.readthedocs.io/en/latest/modules/kaolin.render.easy_render.html), for quickly visualizing a model.
+Check our updated tutorials:
+* [Use Simplicit's Easy API to Simulate a Mesh](https://github.com/NVIDIAGameWorks/kaolin/blob/master/examples/tutorial/physics/simplicits_easy_api.ipynb)
+* [Interact with a Physics Simulation](https://github.com/NVIDIAGameWorks/kaolin/blob/master/examples/tutorial/physics/simplicits_interactive.ipynb)
+* [Use Simplicit's Full-Feature API](https://github.com/NVIDIAGameWorks/kaolin/blob/master/examples/tutorial/physics/simplicits_low_level_api.ipynb)
+* [Simulate a Gaussian Splat](https://gitlab-master.nvidia.com/Toronto_DL_Lab/kaolin/-/blob/master/examples/tutorial/physics/simplicits_inria_splatting.ipynb)
+* [Simulate a Muscle Activation on a Musculoskeletal Mesh](https://gitlab-master.nvidia.com/Toronto_DL_Lab/kaolin/-/blob/master/examples/tutorial/physics/simplicits_muscle_activation.ipynb)
 
-Check our new tutorials:
-[Use Simplicit's Easy API to Simulate a Mesh](https://github.com/NVIDIAGameWorks/kaolin/blob/master/examples/tutorial/physics/simplicits_easy_api.ipynb) In this notebook we show how to use the high-level Simplicit API to simulate an imported Mesh.
-[Interact with a Physics Simulation](https://github.com/NVIDIAGameWorks/kaolin/blob/master/examples/tutorial/physics/simplicits_interactive.ipynb) In this notebook we show to interact with the simulation by moving objects.
-[Use Simplicit's Full-Feature API](https://github.com/NVIDIAGameWorks/kaolin/blob/master/examples/tutorial/physics/simplicits_low_level_api.ipynb) In this notebook we show how to use the low-level API to simulate a pointcloud.
-
-
-[Easy rendering of Meshes](https://github.com/NVIDIAGameWorks/kaolin/blob/master/examples/tutorial/easy_mesh_render.ipynb) Use our new high-level API to load a mesh, create a camera and lighting parameters and render interactively.
-
-<a href="https://github.com/NVIDIAGameWorks/kaolin/tree/master/examples/tutorial/physics"><img src="./assets/physics_bulldozer.gif" alt="physics documentation" height="250" /></a>
-
-See [change logs](https://github.com/NVIDIAGameWorks/kaolin/releases/tag/v0.16.0) for details.
+See [change logs](https://github.com/NVIDIAGameWorks/kaolin/releases/tag/v0.17.0) for details.
 
 ## Contributing
 

docs/notes/installation.rst

@@ -13,9 +13,9 @@ Requirements
 ------------
 
 * Linux, Windows, or macOS (CPU-only)
-* Python >= 3.9, <= 3.11
+* Python >= 3.9, <= 3.12
 * `CUDA <https://developer.nvidia.com/cuda-toolkit>`_ >= 10.0 (with 'nvcc' installed) See `CUDA Toolkit Archive <https://developer.nvidia.com/cuda-toolkit-archive>`_ to install older version.
-* torch >= 2.0, <= 2.4.0
+* torch >= 2.0, <= 2.5.1
 
 Quick Start (Linux, Windows)
 ----------------------------
@@ -24,7 +24,7 @@ Quick Start (Linux, Windows)
 
 .. code-block:: bash
 
-    $ pip install kaolin==0.15.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-{TORCH_VER}_cu{CUDA_VER}.html
+    $ pip install kaolin==0.17.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-{TORCH_VER}_cu{CUDA_VER}.html
 
 .. Note::
     Replace *TORCH_VER* and *CUDA_VER* with any of the compatible options below.
@@ -35,6 +35,12 @@ Quick Start (Linux, Windows)
     +------------------+-----------+-----------+-----------+-----------+
     | **torch / CUDA** | **cu117** | **cu118** | **cu121** | **cu124** |
     +==================+===========+===========+===========+===========+
+    | **torch-2.5.1**  |           |     ✓     |     ✓     |     ✓     |
+    +------------------+-----------+-----------+-----------+-----------+
+    | **torch-2.5.0**  |           |     ✓     |     ✓     |     ✓     |
+    +------------------+-----------+-----------+-----------+-----------+
+    | **torch-2.4.1**  |           |     ✓     |     ✓     |     ✓     |
+    +------------------+-----------+-----------+-----------+-----------+
     | **torch-2.4.0**  |           |     ✓     |     ✓     |     ✓     |
     +------------------+-----------+-----------+-----------+-----------+
     | **torch-2.3.1**  |           |     ✓     |     ✓     |           |
@@ -55,14 +61,12 @@ Quick Start (Linux, Windows)
     +------------------+-----------+-----------+-----------+-----------+
     | **torch-2.0.1**  |     ✓     |     ✓     |           |           |
     +------------------+-----------+-----------+-----------+-----------+
-    | **torch-2.0.0**  |     ✓     |     ✓     |           |           |
-    +------------------+-----------+-----------+-----------+-----------+
 
 For example, to install kaolin for torch 2.0.0 and CUDA 11.8:
 
 .. code-block:: bash
 
-    $ pip install kaolin==0.16.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.0.0_cu118.html
+    $ pip install kaolin==0.17.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.0.0_cu118.html
 
 You can check https://nvidia-kaolin.s3.us-east-2.amazonaws.com/index.html to see all the wheels available.
 
@@ -74,7 +78,7 @@ Installation from source
 
     .. code-block:: bash
 
-        $ conda create --name kaolin python=3.8
+        $ conda create --name kaolin python=3.9
         $ conda activate kaolin
 
 1. Clone Repository
@@ -86,7 +90,7 @@ Clone and optionally check out an `official release <https://github.com/NVIDIAGa
 
     $ git clone --recursive https://github.com/NVIDIAGameWorks/kaolin
     $ cd kaolin
-    $ git checkout v0.16.0 # optional
+    $ git checkout v0.17.0 # optional
 
 2. Install dependencies
 ^^^^^^^^^^^^^^^^^^^^^^^
@@ -111,14 +115,14 @@ You can verify that CUDA is properly installed at the desired version with nvcc
 ^^^^^^^^^^^^^^^^^^
 
 Follow `official instructions <https://pytorch.org>`_ to install PyTorch of a supported version.
-Kaolin may be able to work with other PyTorch versions, but we only explicitly test within the version range 1.10.0 to 2.1.1.
+Kaolin may be able to work with other PyTorch versions, but we only explicitly test within the version range 2.0.1 to 2.5.1.
 See below for overriding PyTorch version check during install.
 
-Here is how to install the latest Pytorch version supported by Kaolin for cuda 11.8:
+Here is how to install the latest Pytorch version supported by Kaolin for cuda 12.4:
 
 .. code-block:: bash
 
-    $ pip install torch==2.1.1 --extra-index-url https://download.pytorch.org/whl/cu118
+    $ pip install torch==2.5.1 --extra-index-url https://download.pytorch.org/whl/cu124
 
 
 4. Optional Environment Variables