esammy / face-recognition-with-gradientboostclassifier

Face Recognition System

• Used MTCNN for face detection
• FaceNet Model is used to create a face embedding for each detected face.
• Developed a Linear Support Vector Machine for face classification

Pre-processing

• Face detection using MTCNN
• Detect face using and store it as dataset.npz
• Create face-embedding using Facenet_Keras model for all the images from dataset.npz and store it in embeddings.npz

Dataset

• The dataset (photos) used are placed in the dataset folder. splittted into train and val for training photos and validation photos respectively.

Getting Started

To begin using the face recognition code, follow these steps:

1. Clone the repository:

   git clone https://github.com/your-username/your-repository.git

2. Install the necessary dependencies:

   pip install -r requirement.txt

3. Run the application:

   python faceembed.py

   python classify.py

Contributing

We welcome contributions from the community! If you'd like to contribute to the Off-Campus Accommodation Portal, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Commit your changes and push them to your forked repository.
4. Submit a pull request describing your changes.

Contact

If you have any questions, suggestions, or feedback, please feel free to reach out to our team at [email protected].

Thank you for choosing the Off-Campus Accommodation Portal! We hope it provides a valuable service for students seeking off-campus accommodation.