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Your own lightweight camera system for home: records what happens, recognises people, vehicles and animals, sends notifications through Home Assistant and has its own web page for phone and laptop. Everything runs locally; no video goes to the cloud.
Uitkijk is Dutch for "lookout".
- Recording with the seconds before: a buffer of ~10 s, so you also see who was arriving.
- Detection of people, vehicles and (optionally) animals, with filters against plants, shadows and parked cars. Doubtful detections are double-checked on the sharp image; at night (infrared) and in bad weather everything is.
- Tracking per person and vehicle: how long in view and which way it went; a parked car does not start a recording.
- Faces (optional): teach it who your housemates are, and answer "Who is this?" from a notification.
- Dutch licence plates (optional); known cars get a name, a "home" sensor from their learned parking spot, and a plate the AI description mentions counts too. A plate seen on 3 or more days becomes a "regular visitor" and no longer triggers the daytime alert.
- Web page with recordings per day, search ("package", a name, a plate), daily summary, live view, masks and zones, "New" badges for recordings you have not opened, and "Nothing to worry about" to ignore a false alarm from then on.
- Archive on a NAS (optional): recordings move after 48 hours and are kept there longer. What the service has learned (faces, plates, parking spots, settings) is backed up there daily too.
- Intel iGPU (optional): object detection and face recognition via OpenVINO.
- Home Assistant via MQTT: sensors per camera and per zone, people/vehicles in view, "last seen" per person, snapshots (also without boxes), a daily summary and ready-made blueprints for notifications.
- Log in with a passkey (Face ID / Touch ID) when you make the page reachable over HTTPS with your own domain.
- A computer that is always on with Docker (a mini PC, a NAS with Docker, or a server). Two CPU cores and 2 GB of memory are enough for 3 cameras; with face recognition preferably 4 GB. An Intel CPU with an iGPU helps (hardware decoding) but is not required.
- Cameras with RTSP: e.g. Reolink, Foscam, Hikvision/Annke, Dahua/Amcrest, TP-Link Tapo/VIGI, UniFi Protect. Preferably with a second, low-resolution stream ("substream").
- Optional: Home Assistant with the Mosquitto broker (MQTT) for notifications.
git clone https://github.com/lexi1986/uitkijk.git cd uitkijk docker compose up -d docker compose logs camsvc | grep "setup code"Then open http://<ip-of-that-computer>:8080. The setup wizard asks for the setup code from the log and then helps you with:
- Cameras: pick the brand, enter IP address and login and press Test: you see an image right away. Another brand? Enter the RTSP address yourself.
- Home Assistant (optional): address and user of the MQTT server, with a test button.
- Options: face recognition, licence plates, live view.
- Storage: how long recordings are kept and how much space they may use.
- Address: how you open the page, and optionally your own domain for HTTPS and passkeys.
After Save and start the service restarts and shows your cameras. The first start takes a bit longer when you enabled face recognition (~500 MB of models to download).
Everything then lives in the folders data/ (settings, faces, plates) and clips/ (recordings). Back up data/ now and then. Per-camera settings, masks and zones are changed under Manage on the web page; all other options are listed in config.example.yaml.
git pull && docker compose up -d --buildThere is also a script that creates a Debian container on Proxmox and installs everything, see docs/GUIDE.md.
- Make sure the MQTT integration is set up in Home Assistant (with the Mosquitto app) and enter those details in the wizard. The cameras appear as devices by themselves, with sensors such as
binary_sensor.cam_front_door_personand a snapshot camera. - Import the blueprints for notifications (Settings → Automations → Blueprints → Import blueprint) with the link to the file in this repository:
| Blueprint | What |
|---|---|
| person_alert | Notification with photo when there is a person, with "Watch live" and "Recording" |
| doorbell | Recording and notification on a doorbell ring, with the name when someone is recognised |
| loitering | Urgent notification when an unknown person stays for a long time |
| who_is_this | Name an unknown face from the notification |
| unknown_vehicle | Unknown plate at night, or during the day after 15 minutes (not for regular visitors) |
| daily_summary | Summary of the day at 22:00 |
| presence | No alarm when a resident just arrived home |
| server_health | Notification on a crash, full disk or offline camera |
| weather | Stricter detection in rain, snow or strong wind |
For "Notification services" enter your phone's notify action, e.g. notify.mobile_app_sams_iphone (found under Developer tools → Actions).
Without your own domain the web page is open to everyone on your home network. To use it away from home, put a reverse proxy with HTTPS in front (Caddy, Nginx Proxy Manager, Traefik) or use a VPN (Tailscale, WireGuard). Enter your domain in the wizard; then you log in with a passkey. The one-time pairing code for the first passkey is in the log. Never expose port 8080 to the internet without such protection.
- Images, faces and plates stay on your own computer.
- If you film the public road or the neighbours, privacy rules apply (in the EU the GDPR): point cameras at your own property as much as possible, mask the rest, and do not keep recordings longer than needed. Recognising faces of anyone other than your housemates is especially sensitive.
- Optionally a local AI model (Ollama) can describe recordings; see the guide.
AGPL-3.0, see LICENSE. You may use, change and share it; whoever distributes a modified version or offers it as a service must make the source code available too. The models have their own licences, see MODELS.md. The InsightFace face model is for non-commercial use only.
More details (all options, API, hardware acceleration, Coral, AI descriptions): docs/GUIDE.md.