Smart Attendance App

Overview:

This application registers and fills student attendance smartly through Face Recognition using Computer Vision Algorithms such as Local Binary Patterns Histogram and HAAR cascade clasifier. It scans images of a student in real time and trains a classifier on those images to register the student. Then it predicts on a test image to fill the attendance for a given day.

Libraries used:

OpenCV: An open-source computer vision and machine learning software library used for real-time image and video processing.

Custom Tkinter: Allows for the creation of customizable and visually appealing graphical user interfaces using the Tkinter library in Python.

Pandas: A powerful data manipulation and analysis library in Python, known for its data structures like DataFrame and Series.

Pyttsx3: A text-to-speech conversion library in Python that works offline and supports multiple speech engines.

Numpy: A fundamental package for numerical computing in Python, providing support for arrays, matrices, and high-level mathematical functions.

Pillow: A Python Imaging Library (PIL) fork that adds support for opening, manipulating, and saving various image file formats.

Demonstrative visuals:

How to use this project

1. Clone this repostory:

git clone "https://github.com/ISHOOO/Smart-Attendance-App"

2. Ensure the presence of dependencies:

pip install -r requirements.txt

3. Run attendance.py

python attendance.py

4. Click on the Register a Student button to register a new student
5. Click on Take attendance to fill the attendance for an already registered student.
6. Click on View student info to view student's registered information
7. Click on View Attendance to view student's attendance data.