Computer Vision Systems
Detection, verification, OCR, and real-time vision pipelines for production use cases.
What it covers
Design and build computer vision systems for identity verification, object detection, medical imaging, and roadside monitoring. Delivery covers model selection, training, inference APIs, and edge-ready deployment patterns using tools already proven in shipped work such as YOLOv5, InsightFace, OpenCV, and custom CNN pipelines.
Business value
Turn visual data into reliable automation — fewer manual checks, faster verification, and clearer operational signals.
Features
- Object detection and segmentation pipelines
- Face and biometric verification workflows
- Arabic/English OCR and document vision
- Real-time analytics and alert hooks
- API and edge deployment support
Process
- Scope & data review — Define the vision task, constraints, and available datasets or capture setup.
- Prototype & validate — Train or adapt models, measure quality, and validate inference paths.
- Ship & integrate — Package APIs, logging, and deployment so the system can run in production.
Technologies
- Python
- PyTorch
- YOLOv5
- InsightFace
- OpenCV
- EasyOCR
- FastAPI
- MongoDB
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