We propose to create a demo project in Flutter that integrates the dlib-face-recognition library written in Rust using the method channel. The project will demonstrate the integration of dlib-face-recognition with Flutter for both iOS and Android platforms, enabling users to take a photo from the camera or pick an image from the gallery and pass it to Rust for face detection. The Rust library will then return the result of face detection to the Flutter app through the method channel. The demo project will showcase the feasibility of using Rust for high-performance face detection in Flutter apps, which can be useful in various industries, including security and surveillance. The project will involve creating a platform-specific code in Flutter to capture or pick an image, creating a Rust library for face detection, and passing the result back to the Flutter app using the method channel. The project will include detailed documentation and code examples to assist other developers in integrating dlib-face-recognition with Flutter. Additionally, we will conduct testing to ensure the accuracy and reliability of the face detection algorithm in various lighting and environmental conditions. Overall, this demo project will provide valuable insights and information on integrating Rust libraries with Flutter, which can be useful for developers looking to create high-performance and efficient mobile apps.