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Copy file name to clipboardExpand all lines: docs/source/docs/contributing/building-photon.md
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[pnpm](https://pnpm.io/) is the package manager used to download dependencies for the UI. To install pnpm, follow [the instructions on the official pnpm website](https://pnpm.io/installation).
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**Cross-Compilation Toolchains (Optional):**
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If you plan to deploy PhotonVision to a coprocessor like a Raspberry Pi, you will need to install the appropriate cross-compilation toolchain for your platform. For `linuxarm64` devices, this can be accomplished by running `./gradlew installArm64Toolchain` in the root folder of the project.
If you work on other projects that use different versions of the same linters as PhotonVision, you may find it beneficial to use a [venv](https://docs.python.org/3/library/venv.html) instead of installing the linters globally. This will allow you to have different versions of the same linter installed for different projects.
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The correct versions for each linter can be found under the linting workflow located [here](https://github.com/PhotonVision/photonvision/tree/main/.github/workflows). For *doc8*, the version can be found in `docs/requirements.txt`. If you've linted, and are still unable to pass CI, please check the versions of your linters.
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## Frontend
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### Linting the frontend
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In order to lint the frontend, run `pnpm -C photon-client lint && pnpm -C photon-client format`. This should be done from the base level of the repo.
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## Backend
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### wpiformat installation
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To lint the backend, PhotonVision uses *wpiformat* and *spotless*. Spotless is included with gradle, which means installation is not needed. To install wpiformat, run `pipx install wpiformat`. To install a specific version, run `pipx install wpiformat==<version>`.
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### Linting the backend
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To lint, run `./gradlew spotlessApply` and `wpiformat`.
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## Documentation
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### doc8 installation
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To install *doc8*, the python tool we use to lint our documentation, run `pipx install doc8`. To install a specific version, run `pipx install doc8==<version>`.
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### Linting the documentation
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To lint the documentation, run `doc8 docs` from the root level of the docs.
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## Alias
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The following [alias](https://www.computerworld.com/article/1373210/how-to-use-aliases-in-linux-shell-commands.html) can be added to your shell config, which will allow you to lint the entirety of the PhotonVision project by running `pvLint`. The alias will work on Linux, macOS, Git Bash on Windows, and WSL.
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```sh
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alias pvLint='wpiformat -v && ./gradlew spotlessApply && pnpm -C photon-client lint && pnpm -C photon-client format && doc8 docs'
Copy file name to clipboardExpand all lines: docs/source/docs/objectDetection/opi.md
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Only quantized models are supported, so take care when exporting to select the option for quantization.
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PhotonVision now ships with a {{ '[Python Notebook](https://github.com/PhotonVision/photonvision/blob/{}/scripts/rknn_conversion.ipynb)'.format(git_tag_ref) }} that you can use in [Google Colab](https://colab.research.google.com) or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rknn_conversion.ipynb` notebook without needing to manually download anything.
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PhotonVision now ships with a {{ '[Python Notebook](https://github.com/PhotonVision/photonvision/blob/{}/scripts/rknn_conversion.ipynb)'.format(git_tag_ref) }} that you can use in [Google Colab](https://colab.research.google.com) or in a local **Linux**environment (since `rknn-toolkit2` only supports Linux). In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rknn_conversion.ipynb` notebook without needing to manually download anything.
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Please ensure that the model you are attempting to convert is among the {ref}`supported models <docs/objectDetection/opi:Supported Models>` and using the PyTorch format.
Copy file name to clipboardExpand all lines: docs/source/docs/objectDetection/rubik.md
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Only quantized models are supported, so take care when exporting to select the option for quantization.
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PhotonVision now ships with a {{ '[Python Notebook](https://github.com/PhotonVision/photonvision/blob/{}/scripts/rubik_conversion.ipynb)'.format(git_tag_ref) }} that you can use in [Google Colab](https://colab.research.google.com) or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rubik_conversion.ipynb` notebook without needing to manually download anything.
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PhotonVision now ships with a {{ '[Python Notebook](https://github.com/PhotonVision/photonvision/blob/{}/scripts/rubik_conversion.ipynb)'.format(git_tag_ref) }} that you can use in [Google Colab](https://colab.research.google.com), [Kaggle](https://kaggle.com/code), or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rubik_conversion.ipynb` notebook without needing to manually download anything.
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Please ensure that the model you are attempting to convert is among the {ref}`supported models <docs/objectDetection/rubik:Supported Models>` and using the PyTorch format.
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