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# rocJPEG changelog
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Documentation for rocJPEG is available at
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[https://rocm.docs.amd.com/projects/rocJPEG/en/latest/](TBD)
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[https://rocm.docs.amd.com/projects/rocJPEG/en/latest/](https://rocm.docs.amd.com/projects/rocJPEG/en/latest/)
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## rocJPEG 0.3.0 (Unreleased)
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## Additions
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* Changelog.md
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## Optimizations
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* Setup Script - Error Check install & cleanup
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## rocJPEG 0.6.0
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### Changes
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* Dependencies - Updates to core dependencies
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* LibVA Headers - Use public headers
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* mesa-amdgpu-va-drivers - RPM Package available on RPM from ROCm 6.2
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* add the RocJpegDecodeParams struct for passing the decode parameters
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### Fixes
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* Package deps
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* RHEL/SLES - Additional required packages `mesa-amdgpu-dri-drivers libdrm-amdgpu`
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### Tested configurations
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* Linux
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* Ubuntu - `20.04` / `22.04`
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* RHEL - `8` / `9`
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* ROCm:
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* rocm-core - `6.1.0.60100-64`
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* amdgpu-core - `1:6.1.60100-1741643`
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* libva-dev - `2.7.0-2` / `2.14.0-1`
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* mesa-amdgpu-va-drivers - `1:24.1.0`
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* mesa-amdgpu-dri-drivers - `24.1.0.60200`
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* rocJPEG Setup Script - `V2.1.0`
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* Supported initial enablement of the rocJPEG library
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* Supported JPEG chroma subsampling:
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* YUV 4:4:4
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* YUV 4:4:0
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* YUV 4:2:2
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* YUV 4:2:0
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* YUV 4:0:0
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* Supported various output image format:
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* Native (i.e., native unchanged output from VCN Hardware, it can be either packed YUV or planar YUV)
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* YUV planar
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* Y only
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* RGB
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* RGB planar
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* Supported single-image and batch-image decoding
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* Supported Different partition modes on MI300 series
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* Supported region-of-interest (ROI) decoding
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* Supported color space conversion from YUV to RGB
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+15
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@@ -10,9 +10,7 @@ rocJPEG provides APIs and samples that you can use to easily access the JPEG dec
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features of your media engines (VCNs). It also allows interoperability with other compute engines on
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the GPU using Video Acceleration API (VA-API)/HIP. To learn more, see :doc:`what-is-rocJPEG`
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You can access rocJPEG code on our `GitHub repository <https://github.com/ROCm/rocJPEG>`_.
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Our documentation is structured as follows:
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The code is open and hosted at `GitHub repository <https://github.com/ROCm/rocJPEG>`_.
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.. grid:: 2
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:gutter: 3
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@@ -22,22 +20,28 @@ Our documentation is structured as follows:
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* :doc:`Quick-start <./install/quick-start>`
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* :doc:`rocJPEG installation <./install/install>`
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The documentation is structured as follows:
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.. grid:: 2
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:gutter: 3
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.. grid-item-card:: Tutorials
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* `GitHub samples <https://github.com/ROCm/rocJPEG/tree/develop/samples>`_
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.. grid-item-card:: How to
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* :doc:`Use rocJPEG <how-to/using-rocjpeg>`
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.. grid-item-card:: API reference
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* :doc:`API library <../doxygen/html/files>`
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* :doc:`Functions <../doxygen/html/globals>`
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* :doc:`Data structures <../doxygen/html/annotated>`
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.. grid-item-card:: How to
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* :doc:`Use rocJPEG <how-to/using-rocjpeg>`
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.. grid-item-card:: Tutorials
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* `GitHub samples <https://github.com/ROCm/rocJPEG/tree/develop/samples>`_
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To contribute to the documentation, refer to
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`Contributing to ROCm <https://rocm.docs.amd.com/en/latest/contribute/contributing.html>`_.
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You can find licensing information on the
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`Licensing <https://rocm.docs.amd.com/en/latest/about/license.html>`_ page.
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`Licensing <https://rocm.docs.amd.com/en/latest/about/license.html>`_ page.
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@@ -9,15 +9,6 @@ Installation
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rocJPEG is a high performance JPEG decode SDK for AMD GPUs. Using the rocJPEG API,
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you can access the JPEG decoding features available on your GPU.
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Supported JPEG chroma subsampling
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========================================
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* YUV 4:4:4
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* YUV 4:4:0
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* YUV 4:2:2
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* YUV 4:2:0
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* YUV 4:0:0
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Prerequisites
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========================================
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@@ -196,23 +187,17 @@ Docker
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You can find rocJPEG Docker containers in our
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`GitHub repository <https://github.com/ROCm/rocJPEG/tree/develop/docker>`_.
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Documentation
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========================================
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Run the following code to build our documentation locally.
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.. code:: shell
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cd docs
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pip3 install -r sphinx/requirements.txt
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python3 -m sphinx -T -E -b html -d _build/doctrees -D language=en . _build/html
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For more information on documentation builds, refer to the
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:doc:`Building documentation <rocm:contribute/building>` page.
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Hardware capabilities
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===================================================
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* Supported JPEG chroma subsampling
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* YUV 4:4:4
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* YUV 4:4:0
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* YUV 4:2:2
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* YUV 4:2:0
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* YUV 4:0:0
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The following table shows the capabilities of the VCN and total number of JPEG cores for each supported GPU
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architecture.
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