You will get a real-time YOLOv8 object detection and tracking system for videos
Project details
You will get a real-time object detection and tracking system using YOLOv8, capable of analyzing live camera feeds or pre-recorded videos with exceptional accuracy and speed. This project is ideal for security surveillance, traffic monitoring, retail analytics, and automation systems.
With strong expertise in Computer Vision, Deep Learning, and Model Optimization, I will build a full end-to-end solution — including data annotation, preprocessing, YOLOv8 training, object tracking integration (DeepSORT or ByteTrack), and performance tuning.
The final delivery includes the trained YOLOv8 model, Python scripts for real-time tracking, and full documentation, ensuring seamless setup and customization.
My focus is on delivering production-ready, optimized, and scalable solutions that transform raw video input into actionable insights — helping your project achieve accurate, fast, and reliable AI-driven video analysis.
With strong expertise in Computer Vision, Deep Learning, and Model Optimization, I will build a full end-to-end solution — including data annotation, preprocessing, YOLOv8 training, object tracking integration (DeepSORT or ByteTrack), and performance tuning.
The final delivery includes the trained YOLOv8 model, Python scripts for real-time tracking, and full documentation, ensuring seamless setup and customization.
My focus is on delivering production-ready, optimized, and scalable solutions that transform raw video input into actionable insights — helping your project achieve accurate, fast, and reliable AI-driven video analysis.
AI Development Type
Deep Learning, Model TuningAI Tools
Deeplearning4j, Keras, Open Neural Network Exchange, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$25
|
Standard
$30
|
Advanced
$35
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | ||
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | - | - | |
Taxonomy | - | - | - |
About Ahmed
Data Scientist | Machine Learning, Deep Learning & AI Solutions
Giza, Egypt - 5:23 am local time
My approach begins with understanding the data, ensuring it is clean, structured, and ready for analysis. From there, I apply statistical techniques and machine learning methods to identify patterns, build predictive models, and optimize performance for reliable results. I have experience working with both structured and unstructured data, and I know how to design models that adapt to different challenges.
Beyond analysis and modeling, I also focus on making solutions practical and accessible. Whether it’s developing a predictive system, creating a deep learning model, or delivering well-organized reports, I make sure the outcomes are clear, actionable, and aligned with client goals. I also work on building user-friendly applications that integrate AI models, allowing clients to use advanced technologies in an easy and effective way.
What I offer:
Comprehensive data analysis and visualization to uncover trends and insights.
Development of machine learning models for accurate and reliable predictions.
Deep learning solutions for complex data such as images, text, or large datasets.
Web scraping and data collection to build clean, structured datasets.
Delivery of easy-to-use, data-driven applications that support decision-making.
My objective is to provide solutions that are not only technically accurate but also impactful helping clients make informed decisions, improve efficiency, and achieve long-term success through data-driven strategies.
Steps for completing your project
After purchasing the project, send requirements so Ahmed can start the project.
Delivery time starts when Ahmed receives requirements from you.
Ahmed works on your project following the steps below.
Revisions may occur after the delivery date.
Upload sample videos & feed details
Share 3–10 short videos (or live camera stream URL) showing your target scene and objects. Mention what objects should be detected and tracked.