This project is a face recognition system built using deep learning techniques. It can identify and verify authorized faces using a trained neural network model.
The project focuses on model training, testing, and deployment-ready structure.
Due to privacy concerns, the complete training dataset is not included in this repository.
- Face recognition using a trained deep learning model
- Real-time or image-based face testing
- Modular and clean project structure
- Privacy-aware dataset handling
- Python
- TensorFlow / Keras
- OpenCV
- NumPy
- Scikit-learn
Face-Recognition-System/ │ ├── model/ │ └── face_recognition_final_model.h5 │ ├── src/ │ ├── model_train.py │ └── test_model.py │ ├── samples/ │ └── test_authorized.png │ ├── requirements.txt ├── README.md └── .gitignore
Install all required dependencies using:
Ensure the test image path is correctly set in test_model.py.
The training dataset is intentionally excluded to protect personal privacy.
To train the model:
- Create your own dataset folder
- Follow the same directory structure used in
model_train.py - Add labeled face images for training
The trained model file (.h5) is included using Git LFS or provided separately
due to GitHub file size limitations.
- Real-time face recognition using webcam
- Multiple face support
- Improved accuracy with larger datasets
- Deployment as a web or desktop application
Kabeer Ahmed AI Student | Machine Learning | Computer Vision