Welcome to the People Tracking and Counting project powered by OpenCV! This project is a comprehensive solution for tracking and counting people in both images and videos. It goes beyond the basics, incorporating advanced features such as predicting the distance from the camera and determining the direction of individuals. Whether you're interested in surveillance, analytics, or research, this project provides a robust foundation.
- OpenCV: The core library driving image and video processing.
- Video Analysis: Techniques for extracting insights from video data.
- Camera Directions: Understanding the orientation and movement of the camera.
- Jupyter Notebooks: Interactive notebooks for seamless experimentation.
- Distance Calculation: Predicting the distance of individuals from the camera.
- People Counter: Keeping track of the total count of people.
- People Detection: Identifying and locating individuals in frames.
- People Counting: Accurate counting of people in both images and videos.
- People Tracking: Continuous tracking of individuals over time.
To dive into people tracking, explore the following Jupyter Notebooks :
- image_fullbody.ipynb
- video_fullbody.ipynb
This project is a creation of Walid BOUSSOU 🇲🇦, a highly motivated Computer Science Engineer passionate about software development, data analytics, and problem-solving. Connect with Walid for inquiries, collaborations, or to contribute to the project.
This project operates under the MIT License. Refer to the LICENSE file for detailed information.
Your feedback and contributions are invaluable! Feel free to open issues, submit pull requests, or reach out to Walid for discussions.
- Contact me in LinkedIn for questions.
