About This Service
Computer Vision Development with YOLO and OpenCV in the UAE
I build production computer vision systems for UAE businesses: object detection and counting with YOLO, image processing pipelines in OpenCV, image classification, and OCR integration for documents, labels and number plates. The systems run on live camera feeds or batch imagery and output structured data — counts, alerts, dashboards — that operations teams in Dubai, Abu Dhabi and Sharjah can act on the same day.
A large share of my work is CCTV and video analytics on cameras you already own: footfall counting for retail stores and malls, queue length monitoring, zone occupancy in warehouses, and safety compliance detection such as helmets and high-visibility vests on industrial sites. I fine-tune YOLO on footage from your actual cameras — your lighting, angles and crowd density — because a model trained only on public datasets will miscount in a real Deira shop or a Jebel Ali warehouse. Accuracy is reported on your footage before go-live, with precision and recall numbers you can hold me to.
Deployment is matched to your constraints, not the other way around. Where internet is unreliable or footage must stay on site, I deploy to edge hardware — NVIDIA Jetson boxes at the camera, or optimised CPU-only inference with ONNX/OpenVINO when there is no GPU budget at all. Where scale matters, the same pipeline runs on a UAE-hosted cloud GPU. Typical clients are retail chains tracking conversion against footfall, warehouse operators automating stock and pallet counts, and facilities teams that need safety-compliance evidence without an employee watching screens all day.
What's included
- Feasibility test on your footage — A proof-of-detection on sample video from your actual cameras before the full build starts.
- Custom-trained YOLO model — Detection or counting model fine-tuned on your scenes, objects and lighting conditions.
- OpenCV processing pipeline — Frame capture, tracking, zone logic and de-duplication so one person is not counted five times.
- OCR integration where needed — Text extraction from labels, plates or documents wired into the same pipeline.
- Edge or cloud deployment — Jetson, CPU-only ONNX/OpenVINO, or UAE-hosted GPU — chosen by your bandwidth, privacy and budget constraints.
- Dashboard and alerts — Counts, heat data and rule-based alerts delivered to a dashboard, webhook or your existing BI tool.
How it works
- 1Site and footage assessment
You share sample video; I confirm camera placement and resolution can support the accuracy you need, and flag fixes if not.
- 2Model training
I annotate representative frames and fine-tune YOLO until precision and recall on your held-out footage meet the agreed target.
- 3Pipeline and deployment
The OpenCV pipeline, tracking logic and outputs are built and deployed to edge hardware or cloud, integrated with your systems.
- 4Live validation
We run the system against ground-truth counts on real days, tune thresholds, and hand over with monitoring in place.
Why work with me
| With me | Typical agency | |
|---|---|---|
| Model trained on your cameras' footage | generic pretrained only | |
| Accuracy verified against ground truth | ||
| Works with existing CCTV hardware | new cameras required | |
| Edge option when footage must stay on site | cloud only |