I will build opencv and yolo computer vision projects


About this gig
Are you looking for professional Computer Vision or YOLO-based AI applications?
I will develop real-time computer vision systems using Python, OpenCV, YOLOv8, and deep learning techniques for detection, tracking, counting, and automation tasks.
Services I Offer:
Object Detection using YOLO
Vehicle Detection & Counting
Face Detection Systems
Real-Time Video Processing
AI Surveillance Applications
Image Processing Solutions
OpenCV Automation Projects
Custom Computer Vision Applications
Features:
Real-time detection and tracking
Accurate AI models
Clean and organized code
Video and camera integration
Performance optimization
Deployment support
Technologies:
Python, OpenCV, YOLOv8, TensorFlow, NumPy, Pandas, Streamlit, Deep Learning.
Why Choose Me?
MS Data Science background
Computer Vision specialization
Professional project structure
Fast communication
Client-focused development
Please contact me before placing an order to discuss your project requirements.
Get to know Hamza Zafar
Machine Learning and Python Automation Developer
- FromPakistan
- Member sinceAug 2022
- Avg. response time1 hour
Languages
Urdu, English
My Portfolio
FAQ
What kind of computer vision projects do you develop?
I develop AI-powered computer vision applications including object detection, vehicle counting, face detection, tracking systems, video analytics, and real-time OpenCV or YOLO-based solutions.
Which technologies do you use for development?
I mainly use Python, OpenCV, YOLOv8, TensorFlow, Streamlit, NumPy, Pandas, and deep learning frameworks for AI application development.
Can you work with custom datasets or videos?
Yes, I can work with custom images, datasets, CCTV footage, drone videos, and real-time camera streams depending on your project requirements.
Will I receive the complete source code?
Yes, all packages include complete source code with organized project structure and setup instructions.
Do you provide deployment or setup support?
Yes, I can help with local deployment, Streamlit deployment, and project setup guidance based on the selected package.

