Kataglyphis-Inference-Engine

An inference engine with Flutter/Dart frontend and Rust/C++ backend, showcasing Gstreamer capabilities enhanced with AI. Read further if you are interested in cross platform AI inference.

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Official homepage

Overview

Kataglyphis-Inference-Engine bundles a Flutter/Dart frontend, a Rust/C++ inference core, and a rich set of camera streaming pipelines powered by GStreamer. The repository acts as an end-to-end reference for building cross-platform inference products that target desktop, web, and embedded devices.

Highlights & Key Features – Kataglyphis-Inference-Engine

🌟 Highlights

• 🎨 GStreamer native GTK integration – Leveraging users to write beautiful Linux AI inference apps.
• 📹 GStreamer WebRTC livestreaming with ready-to-use pipelines for USB, Raspberry Pi, and Orange Pi cameras.
• 🌉 flutter_rust_bridge integration – Ensures a seamless API boundary between Dart UI and Rust logic.
• 🐳 Containerized development flow plus native instructions for Windows, Linux, web. For details in my build environment look into Kataglyphis-ContainerHub
• 🐍 Python inference demos for rapid experimentation alongside the Rust core.

📊 Feature Status Matrix

Core Features

Infrastructure & Build

Testing & Quality Assurance

Frontend Platforms

Platform Summary

Legend:

• ✔️ Completed - Feature fully implemented and tested
• 🔶 In Progress - Active development underway
• ❌ Not Started - Planned but not yet begun
• N/A - Not applicable for this platform

Quick Start

1. Clone the repository with submodules:

NOTE: On Windows I use Git Bash instead of
Powershell or cmd

git clone --recurse-submodules --branch develop git@github.com:Kataglyphis/Kataglyphis-Inference-Engine.git
cd Kataglyphis-Inference-Engine

2. Initialize submodules if needed.
   If u used --recurse-submodules while cloning you are already good.
   Otherwise you can use this :smile:

   git submodule update --init --recursive
   

Refer to the detailed docs below for platform-specific requirements, camera streaming pipelines, and deployment workflows.

Im Projektroot ausführen: dart doc
Danach Static-Server installieren: dart pub global activate dhttpd
export PATH="$PATH":"$HOME/.pub-cache/bin"
Falls dhttpd nicht gefunden wird, einmal PATH ergänzen: $env:Path += ";$env:USERPROFILE\AppData\Local\Pub\Cache\bin"
Server starten: dhttpd --path doc/api --host 127.0.0.1 --port 8080
Im Browser öffnen: http://127.0.0.1:8080

Documentation

Build the full documentation website with dart doc. The generated site in doc/api now includes the guides from docs/source.

Tests

Testing infrastructure is under active development. Track progress on the roadmap or contribute test plans via pull requests.

Roadmap

Upcoming features and improvements will be documented in this repository.
Please have a look docs/source/roadmap.md for more deetails.

Contributing

Contributions are what make the open-source community amazing. Any contributions are greatly appreciated.

1. Fork the project.
2. Create your feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the branch (git push origin feature/AmazingFeature).
5. Open a Pull Request.

License

MIT (see here)

Acknowledgements

Thanks to the open-source community and all contributors!

Literature

Helpful tutorials, documentation, and resources:

Multimedia

• GStreamer

Rust

• GStreamer-rs tutorial
• gst-plugins-rs
• GStreamer WebRTC

Raspberry Pi

• GStreamer on Raspberry Pi
• libcamera
• libcamera on Raspberry Pi

CMake/C++

• clang-cl

Flutter/Dart

• Linux Native Textures
• flutter_rust_bridge
• Flutter on RISCV

Protocols

• WebRTC

Tooling

• tmux
• zellij
• psmux

Android

• Gstreamer+flutter+android

Contact

Jonas Heinle
Twitter: @Cataglyphis_
Email: cataglyphis@jonasheinle.de

Project Links:

• GitHub: Kataglyphis-Inference-Engine
• Homepage: Official Site