This project implements a real-time attendance logging system using computer vision. It leverages facial recognition to track attendance and log it automatically from video feed.
- Real-time facial detection for attendance tracking.
- Logs attendance to a database.
- Uses pre-trained models for facial recognition.
- Supports live webcam input.
detector.py: The script for detecting faces in the video feed.recognizer.py: Handles facial recognition to match faces to known individuals.trainer.py: Used for training the model with facial data.viewer.py: View logged attendancesqlprp: To create databasetrained_model.yml: Stores the trained model for facial recognition.test.py: Extra features in developmentrequirements.txt: Lists necessary Python dependencies.
- Python 3.7 or higher.
- Required Python libraries listed in
requirements.txt.
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Clone the repository:
git clone https://github.com/vaibhavcode/cs-project.git cd cs-project -
Install dependencies: Install all required Python libraries:
pip install -r requirements.txt
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Train the model: If you haven't already, train the facial recognition model by running:
python trainer.py
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Run the application: Execute the attendance logging system:
python detector.py
- The system captures video frames from a webcam.
- Detected faces are matched against known individuals using a pre-trained model.
- If a match is found, the individual's attendance is logged in a database.
- The live video feed is displayed with detection boxes highlighting recognized faces.
- Vaibhav Khurana
- Avneta Malhotra
- Anoushak Saini
This project is licensed under the MIT License. Feel free to use, modify, and distribute the code under the terms of the license.
I would like to express my sincere gratitude to Mrs. Deepika Pareek for her invaluable support throughout our project.