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Copy file name to clipboardExpand all lines: CHANGELOG.md
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The full documentation for MIVisionX is available at [https://rocm.docs.amd.com/projects/MIVisionX/en/latest/doxygen/html/index.html](https://rocm.docs.amd.com/projects/MIVisionX/en/latest/doxygen/html/index.html)
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## (unreleased) MIVisionX 3.2.0
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### Changed
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* Setup: OpenCV package install for Ubuntu
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### Known issues
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* Installation on CentOS/RedHat/SLES requires the manual installation of the `FFMPEG` & `OpenCV` dev packages.
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* Hardware decode requires the ROCm `graphics` usecase.
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### Upcoming changes
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* Optimized audio augmentations support for VX_RPP
Copy file name to clipboardExpand all lines: README.md
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[Neural net model compiler and optimizer](model_compiler/README.md#neural-net-model-compiler--optimizer) converts pre-trained neural net models to MIVisionX runtime code for optimized inference.
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## rocAL
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The ROCm Augmentation Library - [rocAL](rocAL/README.md) is designed to efficiently decode and process images and videos from a variety of storage formats and modify them through a processing graph programmable by the user.
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rocAL is now available as an independent module at [https://github.com/ROCm/rocAL](https://github.com/ROCm/rocAL). rocAL is deprecated in MIVisionX.
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## Toolkit
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[MIVisionX Toolkit](toolkit/README.md) is a comprehensive set of helpful tools for neural net creation, development, training, and deployment. The Toolkit provides useful tools to design, develop, quantize, prune, retrain, and infer your neural network work in any framework. The Toolkit has been designed to help you deploy your work on any AMD or 3rd party hardware, from embedded to servers.
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> [!IMPORTANT]
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> Some modules in MIVisionX can be built for `CPU ONLY`. To take advantage of `Advanced Features And Modules` we recommend using `AMD GPUs` or `AMD APUs`.
> * On `Ubuntu 22.04` - Additional package required: `libstdc++-12-dev`
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>
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> ```shell
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> sudo apt install libstdc++-12-dev
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>```
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>[!NOTE]
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> All package installs are shown with the `apt` package manager. Use the appropriate package manager for your operating system.
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## Installation instructions
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* Install ROCm `6.1.0` or later with [amdgpu-install](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/amdgpu-install.html) with `--usecase=rocm`
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* Use **either**[Package install](#package-install)**or**[Source install](#source-install) as described below.
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>[!IMPORTANT]
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> Use **either** [package install](#package-install) **or** [source install](#source-install) as described below.
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#### Package install
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