Welcome to the ESP32-CAM Face Recognition project! This repository demonstrates how to utilize the ESP32-CAM module for face recognition tasks with the help of Edge Impulse's powerful AI tools. Perfect for makers, hobbyists, and developers looking to integrate machine learning with microcontroller projects.
This project leverages the ESP32-CAM's capabilities along with Edge Impulse to perform real-time face recognition. By following this guide, you will be able to set up and run a face recognition system that can identify and classify faces accurately.
- Real-time Face Recognition: Capture and recognize faces on the fly.
- Edge Impulse Integration: Utilize a cloud-based platform for training and deploying machine learning models.
- ESP32-CAM Module: Use a low-cost, compact camera module for AI-powered image processing.
- User-Friendly Setup: Detailed instructions to get started quickly.
- ESP32-CAM Module: The central hardware component used for capturing images and running the recognition model.
- FTDI Adapter: For programming the ESP32-CAM (if needed).
- Arduino IDE: To upload the firmware to the ESP32-CAM.
- Edge Impulse Account: For training and deploying the machine learning model.
- Security Systems: Implement face recognition for access control.
- Smart Home: Create a personalized experience by recognizing family members.
- Interactive Displays: Use face recognition for interactive exhibits or user engagement.
Feel free to contribute by submitting issues, suggestions, or pull requests. Your input is valuable and helps improve the project for everyone!
This project is licensed under the MIT License. See the LICENSE file for more details.
For any questions or support, please open an issue in the repository or contact us through GitHub Discussions.
Happy coding and face recognition with your ESP32-CAM! 🚀