docs: update doc to highlight Pypi wheels (#235)

Author: dlesage-nvidia

README.md

@@ -79,9 +79,18 @@ Choose the installation method that meets your environment needs.
 
 #### Python Wheel File Installation
 
-Download the appropriate .whl file for your computer architecture, Python and CUDA version from the release assets of current CV-CUDA release. Release information of all CV-CUDA releases can be found [here][CV-CUDA GitHub Releases]. Once downloaded, execute the `pip install` command to install the Python wheel. For example:
+Check pypi.org projects for support for your platform of choice, [cvcuda-cu11][cvcuda-cu11] and [cvcuda-cu12][cvcuda-cu12] for CUDA 11 and CUDA 12, respectively.
+
+Use the following command to install the latest available version:
+   ```shell
+   pip install cvcuda_<cu_ver>
+   ```
+
+where <cu_ver> is the desired CUDA version.
+
+Alternatively, download the appropriate .whl file for your computer architecture, Python and CUDA version from the release assets of current CV-CUDA release. Release information of all CV-CUDA releases can be found [here][CV-CUDA GitHub Releases]. Once downloaded, execute the `pip install` command to install the Python wheel. For example:
    ```shell
-   pip install cvcuda_<cu_ver>-<x.x.x>-cp<py_ver>-cp<py_ver>-linux_<arch>.whl
+   pip install ./cvcuda_<cu_ver>-<x.x.x>-cp<py_ver>-cp<py_ver>-linux_<arch>.whl
    ```
 
 where `<cu_ver>` is the desired CUDA version, `<x.x.x>` is the CV-CUDA release version, `<py_ver>` is the desired Python version and `<arch>` is the desired architecture.
@@ -249,7 +258,7 @@ The new Python wheels for PyPI compliance must be built within the ManyLinux 201
 
 The built wheels can still be installed using `pip`. For example, to install the Python wheel built for CUDA 12.x, Python 3.10 and 3.11 on Linux x86_64 systems:
 ```shell
-pip install cvcuda_cu12-<x.x.x>-cp310.cp311-cp310.cp311-linux_x86_64.whl
+pip install ./cvcuda_cu12-<x.x.x>-cp310.cp311-cp310.cp311-linux_x86_64.whl
 ```
 
 ## Contributing
@@ -324,3 +333,5 @@ CV-CUDA is developed jointly by NVIDIA and ByteDance.
 [ByteDance]: https://www.bytedance.com/
 [CV-CUDA GitHub Releases]: https://github.com/CVCUDA/CV-CUDA/releases
 [CV-CUDA Samples]: https://github.com/CVCUDA/CV-CUDA/blob/main/samples/README.md
+[cvcuda-cu11]: https://pypi.org/project/cvcuda-cu11/
+[cvcuda-cu12]: https://pypi.org/project/cvcuda-cu12/

docs/sphinx/installation.rst

@@ -1,5 +1,5 @@
 ..
-  # SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+  # SPDX-FileCopyrightText: Copyright (c) 2022-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
   # SPDX-License-Identifier: Apache-2.0
   #
   # Licensed under the Apache License, Version 2.0 (the "License");
@@ -74,11 +74,19 @@ You can download the CV-CUDA tar, deb or wheel packages from `the asset section
 
 * Python Wheel File Installation
 
-    Download the appropriate .whl file for your computer architecture, Python and CUDA version from `the asset section of the latest release <https://github.com/CVCUDA/CV-CUDA/releases>`_
+    Check pypi.org projects for support for your platform of choice, `cvcuda-cu11 <https://pypi.org/project/cvcuda-cu11/>`_ and `cvcuda-cu12 <https://pypi.org/project/cvcuda-cu12/>`_ for CUDA 11 and CUDA 12, respectively.
+    Use the following command to install the latest available version::
+
+        pip install cvcuda_<cu_ver>
+
+    where <cu_ver> is the desired CUDA version.
+
+
+    Alternatively, download the appropriate .whl file for your computer architecture, Python and CUDA version from `the asset section of the latest release <https://github.com/CVCUDA/CV-CUDA/releases>`_
 
     Execute the following command to install appropriate CV-CUDA Python wheel ::
 
-        pip install cvcuda_<cu_ver>-<x.x.x>-cp<py_ver>-cp<py_ver>-linux_<arch>.whl
+        pip install ./cvcuda_<cu_ver>-<x.x.x>-cp<py_ver>-cp<py_ver>-linux_<arch>.whl
 
     where <cu_ver> is the desired CUDA version, <x.x.x> the CV-CUDA release version, <py_ver> the desired Python version and <arch> the desired architecture.
 

docs/sphinx/relnotes/v0.14.0-beta.rst

@@ -22,6 +22,11 @@ v0.14.0-beta
 Release Highlights
 ------------------
 
+Python x86_64 wheels are now available on PyPi, `cvcuda-cu11 <https://pypi.org/project/cvcuda-cu11/>`_ and `cvcuda-cu12 <https://pypi.org/project/cvcuda-cu12/>`_ for CUDA 11 and CUDA 12, respectively ::
+
+   pip install cvcuda-cu<CUDA_VERSION>
+
+
 CV-CUDA v0.14.0 includes the following changes:​
 
 * **New Features**:​
@@ -52,6 +57,8 @@ Compatibility and Known Limitations
 
 * We do not provide SBSA-compatible aarch64_cu11 packages yet, this will be addressed in an upcoming release.
 
+* Only x86_64 wheels are available on PyPi as of 02/28/25. SBSA/Grace CUDA 12 wheels will be added shortly.
+
 For the full list, see main README on `CV-CUDA GitHub <https://github.com/CVCUDA/CV-CUDA>`_.
 
 License