Welcome to our Face Recognition project powered by TensorFlow! 🚀
This repository contains the tools and resources for building a state-of-the-art face recognition system. Whether you're a data scientist, computer vision enthusiast, or security professional, this project offers valuable insights and practical implementations for facial recognition.
- data_collect.ipynb: Use this notebook to collect and preprocess face data for training purposes.
- savedmodel.ipynb: Train and save your custom face recognition model as
new_saved_model.keras. - test.ipynb: Deploy and test your trained model in real-time face recognition scenarios.
- haarcascade_frontalface_default.xml: A crucial file for face detection using OpenCV's Haar Cascade classifier.
- keras_model.h5: Pre-trained face recognition model ready for deployment.
- labels.txt: Class labels for the recognized faces.
- images/: Additional images used for training or testing purposes.
- LICENSE: MIT License granting you the freedom to explore and innovate.
- README.md: You're currently reading it. Dive in for more project insights!
- Clone this repository to your local machine.
- Install TensorFlow, OpenCV, and other necessary dependencies.
- Explore the provided notebooks to understand the workflow and customize as needed.
- Train your model, test its performance, and fine-tune for optimal results.
- SuchitaSri18: Developer and maintainer of this project. GitHub Profile
- Special thanks to the TensorFlow and OpenCV communities for their invaluable contributions.
- We appreciate the creators of Haar Cascade classifier for enabling efficient face detection.
Join us on our quest for better face recognition technologies. Feel free to contribute, share insights, or collaborate on enhancing this project. Your expertise is welcome!