Class-Vision is an AI-powered system designed to automate classroom attendance and management using facial recognition technology. The project enhances accuracy, security, and real-time data analytics, providing a scalable and efficient solution for educational institutions.
- Automated Attendance Tracking: Automatically records attendance using facial recognition, reducing manual errors and preventing proxy attendance.
- Real-Time Data Analytics: Provides insights into attendance patterns and student participation.
- High Accuracy and Security: Leverages advanced models to ensure precise identification and secure access control.
- Scalability: Designed to accommodate institutions of all sizes, with the capability to expand as needed.
/src: Core codebase for facial recognition models, algorithms, and system logic./data: Datasets for model training, preprocessing scripts, and augmentation tools./models: Pre-trained models and benchmarks from various experiments./docs: Project documentation, including installation and usage instructions.
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Clone the repository:
git clone https://github.com/your-username/Class-Vision.git
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Navigate to the project directory:
cd Class-Vision -
Install dependencies:
pip install -r requirements.txt
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Run the application:
python src/main.py
To train the facial recognition model with your dataset:
python src/train.py --data_dir /data/faces --epochs 50 --batch_size 32To run the system using the pre-trained model:
python src/main.py --model /models/best_model.h5We welcome contributions! Fork the repository, create a new branch, and submit a pull request with detailed notes on your changes.
This project is licensed under the MIT License. See the LICENSE file for details.
For more information, please reach out to Aditya.