"FRAMS"- The Face Recognition Attendance Management System is an advanced solution created to automate the process of tracking attendance through facial recognition technology. This system makes use of Python programming language and machine learning algorithms to provide precise and effective attendance management capabilities. For recognizing faces, it relies on the LBPH (Local Binary Patterns Histograms) algorithm, while it utilizes the Haar Cascade Frontal Face algorithm for detecting faces. Moreover, to securely store and manage attendance records, the system integrates MySQL as its database management system.
git clone
Install the required dependencies using pip: pip install -r requirements.txt
The Local Binary Patterns Histograms (LBPH) algorithm is a widely used technique in facial recognition and image analysis. It works by extracting local binary patterns from an image and then generating histograms to represent those patterns. Here's a basic explanation of how it works:
The Haar Cascade Frontal Face algorithm is a popular method for detecting frontal faces in images or video streams. It is widely used in computer vision applications, particularly in tasks like face detection and facial recognition. Here's a basic explanation of how it works:
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If you would like to contribute to any of my projects, please fork this repository and create a new branch for your changes. Once you are finished, please submit a pull request.
1.Fork the repository. 2.Create a new branch for your feature or bug fix. 3.Make your changes and commit them. 4.Push to your fork and submit a pull request to the main repository.