Projects using OpenCV in Lahore

Projects using OpenCV in LahoreProjects using OpenCV in Lahore

Cover image for 👋 Hi, I'm Ahmad Yasin,

👋 Hi, I'm Ahmad Yasin, Founder & CEO of Nexariza AI — a global AI engineering and intelligent software company building AI agents, generative AI solutions, automation systems, computer vision applications, and custom SaaS products for businesses worldwide. In this short intro, I share who we are, what we do, and why we're passionate about helping businesses harness the power of AI to solve real problems. 🚀 What Nexariza AI does: ✅ Custom AI Agents & Automation ✅ Generative AI Solutions ✅ Computer Vision Systems ✅ Custom Software & SaaS Development 🌍 Work with us / Partner with us: 🔗 Website: https://nexariza.com (https://nexariza.com)📩 Email: contact@nexariza.com (mailto:contact@nexariza.com)💬 WhatsApp: +92 370 7348001 🔗 LinkedIn: linkedin.com/company/nexariza 🔗 All links: linktr.ee/nexariza_ai 📚 Also check out Nexariza Learning Hub for free AI, ML & programming tutorials — subscribe so you don't miss what's next! #NexarizaAI #AIAgency #ArtificialIntelligence #AIAutomation #FounderStory #TechEntrepreneur #AIAgents #GenerativeAI #SaaS #StartupJourney

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Cover image for Developed an AI-powered KYC verification

Developed an AI-powered KYC verification feature that compares a user's National ID/CNIC photo with their selfie using facial embeddings. The system detects and processes both images, generates face embeddings, compares facial similarity, and automatically determines whether the identity match meets the verification criteria.

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Cover image for The system continuously monitors examination

The system continuously monitors examination halls through live camera feeds, analyzes student behavior, and flags suspicious activities such as mobile phone usage, abnormal head movements, gaze deviation, multiple faces, and unauthorized interactions.

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Cover image for Self Driving Cars Lane Change Warning System

Self Driving Cars Lane Change Warning System

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Cover image for Yolo v10 - Object Detection and tracking

Yolo v10 - Object Detection and tracking

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Cover image for Satellite imagery is the ultimate

Satellite imagery is the ultimate stress test for Computer Vision. It is not just about detection; it is about architecting precision across massive, high-resolution datasets where every pixel counts. I have been building AI pipeline to segment parking lots, walkways, and structures from aerial data. The challenge is not just the mode, it is the Infrastructure: - Tiling & Inference: Processing massive dimensions without losing small-object context. - Robust Pre-processing: Using OpenCV to handle varying lighting and atmospheric "noise." - Cloud Orchestration: Turning heavy segmentation models into responsive, scale-ready tools. It is about turning raw pixels into a reliable data layer for the business. Currently opening 20 hours/week for long-term partnerships in Computer Vision & AI Systems.

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Cover image for An end-to-end OCR pipeline combining

An end-to-end OCR pipeline combining YOLOv11s for real-time document region detection with EasyOCR for multilingual text extraction from scanned documents and images.

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Cover image for Lie Detector

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Cover image for Project Title: Embedded Linux Face

Project Title: Embedded Linux Face Recognition Security System — Dubai Client Category: Computer Vision · Edge AI · IoT Short Description: Production-grade 1:1 face verification system deployed on an industrial Linux PC in Dubai. Integrates SCRFD + AdaFace (ONNX Runtime) with ONVIF IP camera, Wiegand 48-bit access hardware, and GPIO alarm outputs. Supports 20,000-face offline database. Runs as a Linux daemon. Full offline deployment. Services Delivered: Computer Vision Engineering Embedded Linux Development Edge AI Deployment IoT Hardware Integration System Architecture Tech Stack: Python · SCRFD · AdaFace · ONNX Runtime · ONVIF · SQLite · Wiegand · GPIO · Ubuntu Linux Outcome: Live production system managing physical access control in Dubai. Client received a deployed, tested, auto-restarting daemon with full remote management capability. Links: nexariza.com (http://nexariza.com) | contact@nexariza.com (mailto:contact@nexariza.com)

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Cover image for AI Surveillance & Activity Recognition

AI Surveillance & Activity Recognition System Built a real-time AI-powered surveillance platform for intelligent monitoring, object detection, and security analytics. The system leverages deep learning and computer vision to detect people, vehicles, unattended objects, and suspicious activities across multiple camera streams. Key Features Real-time person, vehicle, and object detection Automatic Number Plate Recognition (ANPR) Facial recognition and identity verification Multi-object tracking using ByteTrack Unattended baggage and boundary breach detection Crowd monitoring and suspicious activity recognition Real-time alerts and monitoring dashboard Optimized for high-performance GPU deployment

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Cover image for Computer Vision - Detection and Segmentation with Yolo V9

Computer Vision - Detection and Segmentation with Yolo V9

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Cover image for A real-time multi-object detection and

A real-time multi-object detection and tracking system built with YOLOv8. It detects objects in video streams and assigns persistent IDs across frames, enabling real-time tracking for surveillance and motion analysis.

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Cover image for Dill Plant Disease Detection

Dill Plant Disease Detection

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Cover image for A face recognition system that

A face recognition system that identifies and verifies individuals from images and live video streams using deep learning-based facial embeddings and similarity matching.

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Cover image for Face + Fingerprint Door Unlock System

Face + Fingerprint Door Unlock System

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Cover image for A real-time facial landmark detection

A real-time facial landmark detection system built with OpenCV and MediaPipe. It tracks 468 facial landmarks from live video, enabling applications such as facial analysis, eye tracking, expression analysis, and AR overlays.

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