You will get a People Counting Solution from Video using YOLO and ByteTracker
Project details
This system leverages the power of YOLO for real-time object detection and ByteTrack for robust multi-object tracking in video streams. Designed to count the number of objects or people crossing a pre-defined line, the system finds extensive application in surveillance, traffic monitoring, and retail analytics. The innovative feature of this project is the web-based user interface that allows users to draw or adjust the detection line directly on the video feed. This flexibility ensures the system's adaptability to various scenarios and requirements.
Applications:
Traffic management and analysis
Retail store customer tracking
Security and surveillance in sensitive areas
Technology Stack:
Object Detection: YOLO (You Only Look Once)
Object Tracking: ByteTrack
Frontend: HTML, CSS, JavaScript (for the web UI)
Backend: Python Flask/Django (for integrating YOLO, ByteTrack, and handling video streams)
Database: SQL/NoSQL database (for storing crossing events and analytics)
Applications:
Traffic management and analysis
Retail store customer tracking
Security and surveillance in sensitive areas
Technology Stack:
Object Detection: YOLO (You Only Look Once)
Object Tracking: ByteTrack
Frontend: HTML, CSS, JavaScript (for the web UI)
Backend: Python Flask/Django (for integrating YOLO, ByteTrack, and handling video streams)
Database: SQL/NoSQL database (for storing crossing events and analytics)
Machine Learning Tools
OpenCV, Python, PyTorchWhat's included $1,000
These options are included with the project scope.
$1,000
- Delivery Time 10 days
- Number of Revisions 0
About Martin
MSc in AI, LLM, RAG, LLama, Langchain, Computer Vision, YOLO
Praha, Czech Republic - 3:54 am local time
With over seven years of experience and a master's degree in Artificial Intelligence from Charles University, I excel in delivering advanced AI solutions. Here’s how I can help you:
𝗛𝗼𝘄 𝗜 𝗖𝗮𝗻 𝗛𝗲𝗹𝗽 𝗬𝗼𝘂
LLM/Retrieval-Augmented Generation (RAG):
- Designing and implementing scalable RAG systems
- Structuring data for optimal retrieval and generation
- Fine-tuning Large Language Models (LLMs) to meet specific needs
- Addressing hallucinations in LLMs using LlamaIndex and cutting-edge methods
Computer Vision Solutions:
- Object Detection
- Tracking
- Face Recognition
- People Counting
🔧 Core Technologies
- Python
- LangChain
- LlamaIndex
- PyTorch
- YOLO
- OpenCV
🏆 Highlighted Projects
- People Counting Application: Created an app using YOLO and ByteTracker to count people via video surveillance.
- Esports Event Detector: Developed a system to detect players in FIFA, classify scenes, and recognize scores using OCR.
- AI Camera Surveillance System: Implemented face and action recognition features.
𝗪𝗵𝘆 𝗺𝗲?
- Expertise: Extensive experience in AI and ML, with a deep understanding of both the technical and business aspects.
- Efficiency: Proven track record of delivering well-tested, functional applications quickly and efficiently.
- Communication: Prioritize prompt communication and keep clients updated on project progress.
𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗴𝗲𝘁 𝘀𝘁𝗮𝗿𝘁𝗲𝗱?
- Consultation: Book a consultation to discuss your project in detail and explore how AI can enhance your business.
- Project Development: Reach out to start developing a functional LLM/RAG MVP (minimum viable product) to collect user feedback and generate revenue.
Feel free to send me a message with any questions. I look forward to working with you!
Steps for completing your project
After purchasing the project, send requirements so Martin can start the project.
Delivery time starts when Martin receives requirements from you.
Martin works on your project following the steps below.
Revisions may occur after the delivery date.
Application deployment on server or into cloud