I will build custom yolo object detection and real time tracking systems
AI Automation And Computer Vision Engineer
About this Gig
Need a high-performance Computer Vision solution optimized for speed and accuracy? I build production-ready real-time object detection and tracking pipelines using advanced deep learning frameworks.
Whether you are building a security surveillance system, an automated factory conveyor belt counter, or a retail analytics tool, I deliver clean, modular code designed to handle high frame rates efficiently.
What I Offer:
Custom YOLO Model Training (YOLOv8, YOLOv10, YOLOv11)
Real-Time Object Tracking (BoT-SORT, DeepSORT, ByteTRACK)
Multi-Class Detection & Regional Boundary Counting
Custom Dataset Annotation, Augmentation, and Curation
Integration with interactive Streamlit Dashboards or FastAPI Backends
You will receive a highly optimized, fully documented Python deployment script or a containerized system ready for your infrastructure.
Please message me before placing an order so we can discuss your frame rates, dataset structure, and project hardware requirements!
My Portfolio
FAQ
Which versions of YOLO do you work with, and can you deploy on custom hardware?
I work extensively with YOLOv8, YOLOv10, and YOLOv11. I optimize models depending on your target infrastructure, ensuring hardware-efficient deployment whether you are running inferences on an NVIDIA Jetson edge device, a cloud-based GPU instance, or standard CPU runtime environments.
Can your tracking pipelines handle overlapping objects or occlusion in crowded frames?
Yes. For precision tracking in crowded environments or handling temporary occlusion, I integrate deep tracking algorithms like BoT-SORT, ByteTrack, or DeepSORT with the YOLO backend. This ensures objects maintain consistent tracking IDs even when passing behind obstacles or overlapping in the frame.
Can you connect the vision pipeline to a web interface or an alert system?
Absolutely. I specialize in building complete end-to-end systems. I can integrate the tracking output with a real-time Streamlit dashboard for analytical visualizations, or configure a FastAPI backend to trigger instant Webhook alerts, database logs, or external API signals the millisecond a specifi

