A Python-based GUI application for detecting and displaying motion in specimen video files using OpenCV and Tkinter.
A simple and efficient Python application designed for detecting motion in video files. Leveraging OpenCV for motion detection algorithms and Tkinter for the graphical user interface, this project offers an intuitive tool for analyzing movements within video files, suitable for educational purposes, security monitoring, or any project requiring motion analysis.
- User-friendly interface to browse and select video files.
- Real-time display of motion detection results.
- Detailed metrics on motion within the video, including average movement calculations.
- Lightweight and easily adaptable for various use cases.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
- Python 3.x installed on your system.
- OpenCV, NumPy, PIL, and Tkinter libraries installed.
- Clone the repository to your local machine or download the ZIP file.
pip install opencv-python numpy pillow
Ensure Tkinter is installed (it comes pre-installed with Python).
To run the Motion Detection App, navigate to the project directory and execute: python app.py
Upon launching the application, click "Browse" to select a video file. Press "Run" to initiate motion detection. The interface will display the video and highlight areas of motion, alongside metrics related to the detected movement.
Python 3.x OpenCV NumPy PIL (Pillow) Tkinter
This project is licensed under the MIT License - see the LICENSE.md file for details. The MIT License is a permissive license that is short and to the point. It allows people to do anything they want with your code (as long as they provide attribution back to you and don’t hold you liable).