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Installation

Pre-built installers (recommended)

Download the latest build for your OS from the Releases page:

  • macOS — AutoPTZ-<version>-macos-arm64.dmg (Apple Silicon) or …-macos-x86_64.dmg (Intel). Open it and drag AutoPTZ to Applications. Signed + notarized releases open normally. If you build it yourself unsigned, the first launch needs: right-click the app → Open → Open (or System Settings → Privacy & Security → Open Anyway).
  • Windows — AutoPTZ-<version>-windows-x64-setup.exe. Run it; it installs Start-menu/desktop shortcuts and an uninstaller. SmartScreen may warn on the unsigned installer — More info → Run anyway.
  • Linux — AutoPTZ-<version>-linux-x86_64.AppImage. chmod +x it and run.

The app checks GitHub Releases on startup and from Help → Updates → Check Now…. When a newer version exists, AutoPTZ downloads the matching asset for your OS, starts it, and closes so the installer/new AppImage can finish. If that release does not include your OS asset, AutoPTZ opens the release page instead.

From source

Requires Python 3.12+.

git clone https://github.com/AutoPTZ/autoptz
cd autoptz
python3.12 -m venv .venv            # at the repo root, NOT inside autoptz/
source .venv/bin/activate           # Windows: .venv\Scripts\activate
python tools/install.py --editable
python -m autoptz
  • requirements/base.txt — full stack: ONNX Runtime, OpenCV, PySide6, PyAV, ultralytics, boxmot, insightface, PTZ libs, plus OS-specific camera helpers through pip environment markers.
  • requirements/ui.txt — UI-only (no ML stack), for quick UI work.
  • requirements/dev.txt — pytest, ruff, mypy.
  • tools/install.py — one readable install entry point that selects the right profile and prevents multiple onnxruntime* wheels from coexisting.

Accelerators

The installer defaults to safe local choices: CoreML through the base wheel on macOS, DirectML on Windows, NVIDIA on Linux when nvidia-smi is present, and CPU otherwise. Review or override it with:

python tools/install.py --dry-run
python tools/install.py --accelerator cpu --editable
python tools/install.py --accelerator directml --editable   # Windows
python tools/install.py --accelerator nvidia --editable     # Windows/Linux
python tools/install.py --accelerator openvino --editable

Manual accelerator installs are still possible: install requirements/base.txt, uninstall all onnxruntime* packages, then install exactly one of requirements/gpu-nvidia.txt, requirements/gpu-directml.txt, or requirements/openvino.txt.

Platform notes

  • macOS — requirements/base.txt installs PyObjC AVFoundation packages via markers, so native capture can bind cameras by stable uniqueID. NDI (cyndilib) still needs the NDI SDK runtime first.
  • Windows — DirectML is the default GPU path because it works without CUDA. Force --accelerator nvidia only on machines with CUDA 12.x + cuDNN 9.x, and TensorRT 10.x if you want TensorRT.
  • Linux — install Qt's system libs: libegl1 libgl1 libxkbcommon0 libdbus-1-3 and the libxcb-* set (see docs/building.md).

Verify

python -m autoptz --selftest --log-level INFO

Prints the selected execution provider and exercises the shared-memory + message plumbing.