VisionResearch is a cutting-edge facial recognition system leveraging TensorFlow and MobileNetV2 architecture. This project showcases the capabilities of convolutional neural networks (CNNs) to extract facial features and generate embeddings for applications ranging from security systems to personalized user experiences.
- High Accuracy Face Detection: Utilizes MTCNN for precise face detection.
- Robust Facial Feature Extraction: Employs a pre-trained MobileNetV2 model for feature extraction.
- Modular Design: The codebase is structured for easy extension and further development.
Before starting, ensure you have the following installed:
- Python 3.6 or higher
- pip
- virtualenv (optional but recommended)
```bash git clone https://github.com/R00TN3TSAGE/VisionResearch.git cd visionresearch ```
Create and activate a virtual environment:
-
macOS/Linux: ```bash python3 -m venv venv source venv/bin/activate ```
-
Windows: ```bash python -m venv venv .\venv\Scripts\activate ```
```bash pip install -r requirements.txt ```
Navigate to the `/src` directory and run the main script: ```bash python face_recognition.py ``` This script processes images in the `/images` directory, detecting faces and generating embeddings.
``` visionresearch/
├── models/ - Storage for pre-trained and custom model
├── images/ - Directory for sample images
├── src/ - Source code for the facial recognition system
│ └── face_recognition.py - Main script
├── requirements.txt - Project dependencies
└── README.md - Project documentation ```
Contributions to VisionResearch are welcome! Please fork the repository, create a feature branch, and submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.
- Your Name - rootnetsage@proton.me
- Project Link: https://github.com/R00TN3TSAGE/VisionResearch