Security · Computer vision
Plate Gate
License plate recognition that turns ordinary IP cameras into a smart parking log — every pass on video, every car accounted for.
- Status
- Live
- Year
- 2026
- What we delivered
- Computer vision pipeline · Web portal · Video storage · On-premises deployment · Monitoring & backups

- clean event per pass instead of dozens of frame reads
- 1
- clean event per pass instead of dozens of frame reads
- GPUs or proprietary hardware needed
- 0
- GPUs or proprietary hardware needed
- cameras in production, entry and exit
- 3
- cameras in production, entry and exit
The challenge
Residential complexes, business centres and private car parks need to know which cars come and go — but off-the-shelf ANPR systems are expensive, closed and locked to one vendor's hardware. Most sites already have IP cameras on the gates; they just record video nobody watches.
And before any system is trusted to open a barrier, its accuracy has to be proven on the site's own cameras, angles and lighting — headlights at night, glare, infrared switching — not on a vendor's demo footage.
The solution
Plate Gate connects to existing RTSP cameras and runs fully on-premises on open-source models. A YOLOv9 detector finds plates, a tracker follows each car across frames, and an OCR model reads every frame; voting across the whole track turns dozens of noisy reads into a single, confident event per pass, validated against Ukrainian plate formats.
The web portal shows a live journal with a photo and a short video clip of every pass, who is parked right now and for how long, anomalies worth checking, a registry of owners and their cars imported from Excel, and the health of the server and every camera. Operators can verify reads, and a built-in evaluation tool measures real accuracy by day, night, entry and exit.
Key capabilities
- 01
Works with existing cameras
Any RTSP IP camera or DVR channel. No vendor lock-in, no cloud, all data stays on site.
- 02
Video of every pass
A 5–20 s clip starting 2 s before the plate appears, streamed to the browser with seeking and cleaned up automatically.
- 03
Who's inside right now
Parking presence derived from entries and exits, with missed exits and one-character mismatches flagged instead of guessed.
- 04
Recognition zones
Draw the driveway on a live frame per camera; billboards and signs stop producing false reads, no restart needed.
- 05
Owner registry
Owners, units and cars imported from Excel with a dry run; every pass shows who the car belongs to.
- 06
Measured accuracy
Operator verification and an evaluation report by day/night and entry/exit — numbers, not promises.
Screens

The result
Plate Gate runs 24/7 in production with three cameras — one entry and two exits — on an ordinary office computer without a GPU.
The architecture already separates "what was seen" from "who is allowed in", so automatic barrier control is a configuration step on top of proven accuracy, not a rewrite.
Technology
- Python
- OpenCV
- ONNX Runtime
- YOLOv9
- FastAPI
- PostgreSQL
- MinIO
- go2rtc
- FFmpeg
- Docker Compose
Want something like this for your business?
Tell us about your idea or the process you want to automate. We'll propose a solution, a timeline and the first working version.
Next case
Spot Watch
Shows which parking spots in a residential courtyard are free right now — using the IP cameras already on site.