# Installation Installing headless AugeLab Studio varies depending on your operating system. Follow the instructions below for your specific platform. ## Windows Using the AugeLab Studio installer manually sets up the headless runtime already and is the recommended way to install Headless Studio on Windows. ## Linux Download the Linux installer script from [account.augelab.com](https://account.augelab.com). The installer supports Debian and Debian-based distributions, including Ubuntu. It creates an isolated virtual environment at `~/studio_venv`, installs the selected `studio` package profile, and creates desktop launchers when UI mode is selected. {% hint style="warning" %} The installer does not install NVIDIA CUDA Toolkit or NVIDIA drivers. For AI/GPU mode, install the correct NVIDIA driver and **CUDA 12.8** on the machine first. {% endhint %} ### Full installation Use this for the regular desktop + headless installation: ```bash chmod +x installer.sh ./installer.sh --ui ``` This installs `studio[ui]`, creates `~/studio_venv`, adds the `augelab_studio` launcher, and creates desktop entries. After installation, run: ```bash augelab_studio ``` ### Full installation with AI/GPU support Install NVIDIA driver and **CUDA 12.8** first. Then run: ```bash chmod +x installer.sh ./installer.sh --ui --ai ``` This installs `studio[ui,gpu]`.
Headless only Use this when you only need the Python API and do not need the desktop UI: ```bash chmod +x installer.sh ./installer.sh --headless ``` This installs `studio`. UI launcher and desktop entries are not created.
Headless with AI/GPU support Install NVIDIA driver and **CUDA 12.8** first. Then run: ```bash chmod +x installer.sh ./installer.sh --headless --ai ``` This installs `studio[gpu]`. UI launcher and desktop entries are not created.
Interactive install Run the installer without mode flags to choose install mode interactively: ```bash chmod +x installer.sh ./installer.sh ``` The installer asks whether to install headless or UI mode, then whether to include the AI/GPU extra.
Non-interactive install with environment variables Use environment variables when running from automation: ```bash INSTALL_UI=1 INSTALL_AI=0 ./installer.sh INSTALL_UI=1 INSTALL_AI=1 ./installer.sh INSTALL_UI=0 INSTALL_AI=0 ./installer.sh INSTALL_UI=0 INSTALL_AI=1 ./installer.sh ``` `INSTALL_UI=1` selects UI mode. `INSTALL_AI=1` includes the AI/GPU extra.
Uninstall ```bash ./installer.sh --uninstall ``` This removes installer-created files: * `~/studio_venv` * `~/.local/bin/augelab_studio` * AugeLab Studio desktop entries * AugeLab Studio icons Parent directories are removed only if empty.
Manual Python install Use the installer when possible. If you need a manual Python environment, install into an isolated virtual environment instead of system Python: ```bash apt-get update -y && \ apt-get install -y --no-install-recommends \ libdmtx0b \ zbar-tools \ build-essential \ libgl1-mesa-glx \ curl \ ca-certificates \ && rm -rf /var/lib/apt/lists/* curl -fsSL https://astral.sh/uv/install.sh | sh uv venv -p 3.12 studio_venv uv pip install --python studio_venv/bin/python \ studio \ --extra-index-url https://pyrepo.augelab.com \ --extra-index-url https://download.pytorch.org/whl/cpu \ --index-strategy unsafe-best-match ``` For AI/GPU manual install, install NVIDIA driver and **CUDA 12.8** first, then replace `studio` with `studio[gpu]`.
## Docker with CPU/CUDA on x86\_64 For customer deployments, build the container image from a Dockerfile. AugeLab Studio is a closed-source application, so Docker installs the `studio` package from the AugeLab package index instead of building Studio from source. Use [Docker Example](/key-features/headless/docker-example.md) as the canonical Docker guide. It includes: * CPU Dockerfile * GPU/CUDA Dockerfile * `docker-compose.yml` * `.env` * scenario runner script * mounted output folder ### CPU Docker Use CPU Docker when your scenario does not need CUDA acceleration. The Docker example builds from `python:3.12-slim-bookworm` and installs `studio`. ### GPU/CUDA AugeLab Studio supports CUDA acceleration for headless scenarios. GPU Docker requires compatible NVIDIA drivers and NVIDIA Container Toolkit on the host. Use the GPU/CUDA Dockerfile in [Docker Example](/key-features/headless/docker-example.md). It builds from an NVIDIA CUDA runtime image and installs `studio[gpu]`. ## ARM64 (Raspberry Pi, Jetson Nano/AGX) AugeLab Studio supports ARM64 architecture for headless usage on Debian-based devices such as Raspberry Pi and NVIDIA Jetson series. Download the Linux ARM64 installer scripts from [account.augelab.com](https://account.augelab.com), then run the installer on the device. ### Full ARM64 installation ```bash chmod +x installer.sh ./installer.sh --ui ``` This installs `studio[ui]`, creates `~/studio_venv`, adds the `augelab_studio` launcher, and creates desktop entries. ### Full ARM64 installation with AI/GPU support Install the correct NVIDIA JetPack/CUDA stack for your device first. For Jetson devices, use the CUDA version that matches your JetPack release. ```bash chmod +x installer.sh ./installer.sh --ui --ai ``` This installs `studio[ui,gpu]`.
Headless ARM64 only ```bash chmod +x installer.sh ./installer.sh --headless ``` This installs `studio`. UI launcher and desktop entries are not created.
Headless ARM64 with AI/GPU support Install the correct NVIDIA JetPack/CUDA stack for your device first. For Jetson devices, use the CUDA version that matches your JetPack release. ```bash chmod +x installer.sh ./installer.sh --headless --ai ``` This installs `studio[gpu]`. UI launcher and desktop entries are not created.
ARM64 uninstall ```bash ./installer.sh --uninstall ```
{% hint style="info" %} The ARM64 installer supports Debian and Debian-based distributions. If your device uses another Linux family, contact AugeLab for deployment guidance. {% endhint %} For Jetson GPU/CUDA deployments, match the installer, JetPack, CUDA stack, and AugeLab package profile for your device. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.augelab.com/key-features/headless/installation.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.