Build a real-time object detection prototype using YOLO & OpenCV

I will build a working real-time object detection prototype tailored to your specific use case — person detection, footfall counting, product inspection, or custom object classes — using YOLOv8 and OpenCV.

This Offer is a focused proof of concept to validate the approach on your footage before committing to a full build.

What you receive:
→ Working Python script with YOLOv8 detection on your video input (file or webcam)
→ Detection of your specified object classes with bounding boxes and confidence scores
→ Basic count output per frame (e.g. person count, object count)
→ Short README explaining how to run it and extend it
→ Clean code — full IP ownership from day one

I have this running in production across restaurant chains, retail surveillance, and corporate monitoring environments. Demo: https://youtu.be/9cEGlz9ulHg

Note: This Offer covers the detection prototype. Full pipeline with tracking, database, dashboard, alerts, and deployment is quoted as a custom project after this stage.

Add-ons:
→ Add object tracking with unique IDs per person/object (+£75, same delivery)
→ Add WhatsApp alert when object detected (+£80, +1 day)