I will build custom yolov8 and yolov10 model for object detection and tracking
Unity game developer building 2D and 3D mobile games, AR apps and YOLO visions
About this Gig
Custom YOLOv8 and YOLOv10 object detection and tracking models built with Python, OpenCV, and deep learning for real-world computer vision.
Tired of models that miss objects, run slowly, or fail on your own data? Get an accurate, real-time AI model trained on your images and ready to use.
WHAT I OFFER:
- Custom YOLO model training
- Object detection and tracking
- Image segmentation
- Pose estimation
- Defect detection
- ANPR and license plates
- Face detection
- Player and sports tracking
- Object counting and zones
- Video analytics dashboard
SOFTWARE USED:
Python, YOLOv8, OpenCV, PyTorch, NumPy, Roboflow, Streamlit, Google Colab
DELIVERABLES:
- Trained model weights
- Python inference script
- Accuracy report
- Demo video output
- Setup guide and support
USE CASES:
- Factory / Workplace safety monitoring
- CCTV surveillance systems
- Retail analytics (people/object tracking)
- Smart automation systems
- Research or academic CV projects
HOW IT WORKS:
- Order and share your data
- Train and test the model
- Deliver results and code
WHY THIS GIG: High accuracy, fast inference, clean code, and support after delivery.
Message me for a consultation before placing your order.
Programming language:
Python
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Java
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NoSQL
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MLflow
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Julia
FAQ
What do you need from me to start?
Your images or videos, the objects you want to detect, and where the model will run (PC, server, camera, or mobile). No labeled data yet? Annotation can be added to your order.
What tools do you use?
Python, YOLOv8, YOLOv10, OpenCV, PyTorch, Roboflow, and FastAPI. Training runs on GPU, so you get a model that works fast on your own hardware.
Can you build a custom computer vision project outside these packages?
Yes. Custom orders are welcome for ANPR, face recognition, remote sensing, sports analytics, and AI mobile or web apps. Message me with your idea and you will get a custom offer.

