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docs: deploy.md: Fix spelling of "Synopsys GNU Toolchain" (#240)
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gmacario authored Jul 22, 2024
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# Deploying SSCMA on Grove - Vision AI

This example is a tutorial for deploying the models from [SSCMA](https://github.com/Seeed-Studio/ModelAssistant) to Grove - Vision AI module, based on the [Synopsys GUN Toolchain](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain) and [Tensorflow Lite Micro](https://github.com/tensorflow/tflite-micro) implementations.
This example is a tutorial for deploying the models from [SSCMA](https://github.com/Seeed-Studio/ModelAssistant) to Grove - Vision AI module, based on the [Synopsys GNU Toolchain](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain) and [Tensorflow Lite Micro](https://github.com/tensorflow/tflite-micro) implementations.

## Prerequisites

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- A USB cable

### Installing Synopsys GUN Toolchain
### Installing Synopsys GNU Toolchain

Grove - Vision AI uses the [Himax HX6537](https://www.himax.com.tw/zh/products/intelligent-sensing/always-on-smart-sensing/) chip, where we need to install the [ Synopsys GUN Toolchain](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain) in order to cross-compile the firmware afterwards, the installation is divided into the following steps.
Grove - Vision AI uses the [Himax HX6537](https://www.himax.com.tw/zh/products/intelligent-sensing/always-on-smart-sensing/) chip, where we need to install the [Synopsys GNU Toolchain](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain) in order to cross-compile the firmware afterwards, the installation is divided into the following steps.

1. First, download the pre-compiled toolchain from [Synopsys GUN Toolchain - GitHub Releases](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain/releases/).
1. First, download the pre-compiled toolchain from [Synopsys GNU Toolchain - GitHub Releases](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain/releases/).

```sh
wget https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain/releases/download/arc-2020.09-release/arc_gnu_2020.09_prebuilt_elf32_le_linux_install.tar.gz -P ~/ && \
tar -zxvf ~/arc_gnu_2020.09_prebuilt_elf32_le_linux_install.tar.gz --directory ~/
```

2. Then, specify the directory of the Synopsys GUN Toolchain executable in the PATH and add it to `~/.bashrc` to facilitate automatic import when shell starts.
2. Then, specify the directory of the Synopsys GNU Toolchain executable in the PATH and add it to `~/.bashrc` to facilitate automatic import when shell starts.

```sh
echo 'export PATH="$HOME/arc_gnu_2020.09_prebuilt_elf32_le_linux_install/bin:$PATH" # Synopsys GUN Toolchain' >> ~/.bashrc
echo 'export PATH="$HOME/arc_gnu_2020.09_prebuilt_elf32_le_linux_install/bin:$PATH" # Synopsys GNU Toolchain' >> ~/.bashrc
```

:::tip
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- If you find any issues in these examples, or wish to submit an enhancement request, please use [GitHub Issue](https://github.com/Seeed-Studio/ModelAssistant).

- For Synopsys GUN Toolchain related issues please refer to [Synopsys GUN Toolchain](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain).
- For Synopsys GNU Toolchain related issues please refer to [Synopsys GNU Toolchain](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain).

- For information about TensorFlow Lite Micro, please refer to [TFLite-Micro](https://github.com/tensorflow/tflite-micro).

- For SSCMA related information, please refer to [SSCMA](https://github.com/Seeed-Studio/ModelAssistant).

## Licensing

For Synopsys GUN Toolchain, it is released under the [GPLv3 License](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain/blob/arc-releases/COPYING).
For Synopsys GNU Toolchain, it is released under the [GPLv3 License](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain/blob/arc-releases/COPYING).

The TensorFlow library code and third-party code contain their own licenses, which are described in [TFLite-Micro](https://github.com/tensorflow/tflite-micro).

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