I am looking for a developer with proven experience in Computer Vision to build a real-time counting system using an RTSP stream from an industrial camera. The goal is to replace CountThings and develop our own solution based on YOLO + Object Tracking, capable of counting poultry moving on a conveyor line during the workday. The system must detect, track, and count each object that crosses a virtual line, display the count in real time, and expose the data in JSON through a REST API / WebSocket for integration into our internal dashboard. Technical Requirements (Mandatory): - Real-time video processing via RTSP - Object detection using YOLO (v8, v9, v10 or similar) - Object tracking using DeepSORT or ByteTrack - Line-crossing + ROI logic to prevent false counts - REST API (JSON) + WebSocket for live counts - Batch registration (Start/Stop) without video storage - Simple dashboard (Streamlit / Superset / Metabase / similar) - Code must be in Python (preferred) - Stable operation for 8–10 hours per day Deliverables: - Full source code (GitHub or similar) - Docker-ready deployment (preferred) - Working API (REST + optional WebSocket) - Real-time dashboard - Deployment & installation documentation - Tests using our RTSP stream Your Proposal MUST Include: 1. Links to similar projects (counting, tracking or RTSP real-time CV systems) 2. Which YOLO model you would use and why 3. Estimated delivery time 4. Budget proposal 5. Suggested improvements (optional) Estimated Timeline: MVP: 5–10 days | Production-ready version: 2–3 weeks Required Skills: Python, OpenCV, YOLO, DeepSORT/ByteTrack, RTSP/FFmpeg/GStreamer, experience delivering production-ready CV systems.