> For the complete documentation index, see [llms.txt](https://docs.augelab.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.augelab.com/key-features/headless/installation.md).
# 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 drivers. For AI/GPU mode, install the NVIDIA driver on the host first. AugeLab Studio ships the CUDA runtimes it needs. On Jetson devices, use the JetPack/NVIDIA driver stack for your device.
{% 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 the NVIDIA driver 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 the NVIDIA driver 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 the NVIDIA driver first, then replace `studio` with `studio[gpu]`. AugeLab Studio ships the CUDA runtimes it needs.
## 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 JetPack/NVIDIA driver stack for your device first.
```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 JetPack/NVIDIA driver stack for your device first.
```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 deployments, match the installer, JetPack/NVIDIA driver stack, and AugeLab package profile for your device.