Repository: choushunn/awesome-RK3588
Branch: develop
Commit: 6c5741f67e11
Files: 5
Total size: 27.6 KB

Directory structure:
gitextract_z83rnb1p/

├── .gitignore
├── LICENSE
├── README.md
├── README_CN.md
└── contributing.md

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FILE CONTENTS
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FILE: .gitignore
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FILE: LICENSE
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================================================
FILE: README.md
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English | [简体中文](README_CN.md)

# Awesome RK3588 | [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

[<img src="https://www.rock-chips.com/templets/new_2014_9/images//logo.png" align="right" width="100">](https://www.rock-chips.com/)

RK3588 is Rockchip's flagship 8K SoC with quad Cortex-A76, quad Cortex-A55, and 6 TOPS NPU. This list curates essential development resources. :rocket:

## Contents
- [Official Resources](#official-resources)
- [RKNN & AI Tools](#rknn--ai-tools)
- [Large Language Models](#large-language-models)
- [Operating Systems](#operating-systems)
- [Projects](#projects)
- [Development Boards](#development-boards)
- [Documentation](#documentation)
- [Development Tools](#development-tools)
- [Sample Code](#sample-code)
- [Community](#community)

## Official Resources
1. [Rockchip Linux ↗](https://github.com/rockchip-linux) - Official kernel, u-boot, MPP
2. [RKNN SDK Documentation ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/doc) - Latest SDK guides
3. [RKNPU2 Tutorial ↗](https://www.bilibili.com/video/BV1Kj411D78q) - RKNPU2 from entry to practice
4. [Rockchip Resource Portal ↗](https://console.zbox.filez.com/l/I00fc3) - SDK downloads (code: rknn)

## RKNN & AI Tools
### Core SDK
1. **[RKNN-Toolkit2 ↗](https://github.com/airockchip/rknn-toolkit2)** - Model conversion & evaluation (v2.3.2+)
2. **[RKNPU2 Runtime ↗](https://github.com/rockchip-linux/rknpu2)** - NPU runtime libraries
3. **[RKNN-Toolkit-Lite2 ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/rknn-toolkit-lite2)** - On-device Python API
4. **[librga ↗](https://github.com/airockchip/librga)** - 2D graphics acceleration

### Model Zoo
1. **[RKNN Model Zoo ↗](https://github.com/airockchip/rknn_model_zoo)** - 30+ pre-trained models (YOLO11, SAM, Whisper, CLIP)
2. **[RKLLM ↗](https://github.com/airockchip/rknn-llm)** - LLM deployment stack

## Large Language Models
*RK3588 supports edge LLM deployment with RKLLM*
1. **Supported Models**: TinyLlama 1.1B (~10-15 tokens/sec), Qwen2 0.5B, Whisper
2. **[RKLLM Toolkit ↗](https://github.com/airockchip/rknn-llm)** - Convert and deploy LLMs

## Operating Systems
1. **[Ubuntu Rockchip ↗](https://github.com/Joshua-Riek/ubuntu-rockchip)** - Ubuntu 22.04/24.04 LTS (recommended)
2. **[Armbian ↗](https://www.armbian.com/)** - Official RK3588 support
3. **[Buildroot RK3588 ↗](https://github.com/Military-Vehicle-Detection/buildroot-rk3588)** - Minimal Buildroot
4. **[NixOS RK3588 ↗](https://github.com/ryan4yin/nixos-rk3588)** - NixOS for Orange Pi/ROCK 5A

## Projects
1. **[YOLOv8 C++ ↗](https://github.com/cqu20160901/yolov8_rknn_Cplusplus)** - Production YOLOv8 inference
2. **[rknn-multi-threaded ↗](https://github.com/leafqycc/rknn-multi-threaded)** - Multi-threaded NPU (+40% perf)
3. **[YOLOv5+DeepSORT ↗](https://github.com/Zhou-sx/yolov5_Deepsort_rknn)** - Real-time tracking
4. **[GStreamer MPP ↗](https://github.com/rockchip-linux/gstreamer-rockchip)** - Hardware-accelerated video
5. **[FFmpeg RKMPP ↗](https://github.com/rockchip-linux/ffmpeg-rockchip)** - 8K video codec

## Development Boards
### Consumer/Maker
1. **[Orange Pi 5 Series ↗](http://www.orangepi.org/)** - Best value (4-16GB, PCIe 3.0)
2. **[Radxa ROCK 5 ↗](https://radxa.com/products/rock5)** - Industrial grade, dual Ethernet
3. **[LubanCat RK3588 ↗](https://doc.embedfire.com/products/link/zh/latest/linux/ebf_lubancat.html)** - Rich IO, Chinese docs

### Industrial
1. **ITOP-3588 ↗** - Beijing Xunwei, full support
2. **FireFly ITX-3588J ↗** - Mini-ITX embedded form factor

## Documentation
### Technical
1. **[RK3588 Datasheet ↗](https://www.rock-chips.com/uploads/pdf/2022.8.26/191/RK3588%20Brief%20Datasheet.pdf)** - Official specs (6 TOPS, 8K@60fps)
2. **[RKNN User Guide ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/doc)** - Conversion & deployment
3. **[RKNPU2 API Reference ↗](https://github.com/rockchip-linux/rknpu2/blob/master/doc/Rockchip_RKNPU_User_Guide_RKNN_API_V2.0.0.pdf)** - C/C++ API

### Board-Specific
1. **[Radxa ROCK 5 Docs ↗](https://docs.radxa.com/rock5)** - Excellent English docs
2. **[LubanCat Manual ↗](https://doc.embedfire.com/linux/rk3588/quick_start/zh/latest/)** - Best Chinese docs

## Development Tools
1. **[RKDevTool ↗](https://github.com/rockchip-linux/rkdeveloptool)** - Firmware flashing
2. **[RKNN-Toolkit2 Docker ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/docker)** - Pre-configured environment
3. **NPU Monitor**: `cat /sys/kernel/debug/rknpu/load`

## Sample Code
1. **[RKNN Model Zoo ↗](https://github.com/airockchip/rknn_model_zoo)** - 30+ official model demos
2. **[rknn_api_demo ↗](https://github.com/rockchip-linux/rknpu2/tree/master/rknn_api_demo)** - Minimal C API examples
3. **[RKLLM Examples ↗](https://github.com/airockchip/rknn-llm/tree/main/examples)** - LLM chatbot demos

## Community
### International
1. **[Radxa Forum ↗](https://forum.radxa.com/)** - ROCK series community
2. **[Armbian Forum ↗](https://forum.armbian.com/forum/29-rockchip-3588-3566-3568-3399/)** - OS-level support
3. **[Orange Pi Forum ↗](http://www.orangepi.org/orangepibbsen/)** - Official Orange Pi forum

### Chinese
1. **[iTOP-RK3588 Forum ↗](http://bbs.topeetboard.com/forum.php?mod=forumdisplay&fid=55)** - Beijing Xunwei support
2. **[LubanCat Community ↗](https://forums.embedfire.com/c/lubancat/21)** - Wildfire Electronics

---

## Contribute 🤝

Got a pull request? Open it, and we'll review it as soon as possible. If you have any suggestions or find any bugs and feel free to bring your fresh ideas to the table! [Contribution Guidelines](contributing.md)

- [Open Issues](https://github.com/choushunn/awesome-RK3588/issues)
- [Open Pull Requests](https://github.com/choushunn/awesome-RK3588/pulls)
- [Open Discussions](https://github.com/choushunn/awesome-RK3588/discussions)

This project exists thanks to all the people who contribute. [[Contribute](contributing.md)].

<a href="https://github.com/choushunn/awesome-RK3588/graphs/contributors"><img src="https://contrib.rocks/image?repo=choushunn/awesome-RK3588&max=200&columns=24" width=850px /></a>

================================================
FILE: README_CN.md
================================================
[English](README.md) | 简体中文

# Awesome RK3588 | [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

[<img src="https://www.rock-chips.com/templets/new_2014_9/images//logo.png" align="right" width="100">](https://www.rock-chips.com/)

RK3588是瑞芯微旗舰级8K SoC芯片，配备四核Cortex-A76、四核Cortex-A55及6 TOPS NPU。本列表整理了开发必备资源。:rocket:

## 目录
- [官方资源](#官方资源)
- [RKNN与AI工具](#rknn与ai工具)
- [大语言模型](#大语言模型)
- [操作系统](#操作系统)
- [项目](#项目)
- [开发板](#开发板)
- [文档](#文档)
- [开发工具](#开发工具)
- [示例代码](#示例代码)
- [社区](#社区)

## 官方资源
1. [Rockchip Linux ↗](https://github.com/rockchip-linux) - 官方内核、u-boot、MPP
2. [RKNN SDK文档 ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/doc) - 最新SDK指南
3. [RKNPU2教程 ↗](https://www.bilibili.com/video/BV1Kj411D78q) - RKNPU2从入门到实践
4. [瑞芯微资源门户 ↗](https://console.zbox.filez.com/l/I00fc3) - SDK下载（提取码：rknn）

## RKNN与AI工具
### 核心SDK
1. **[RKNN-Toolkit2 ↗](https://github.com/airockchip/rknn-toolkit2)** - 模型转换与评估（v2.3.2+）
2. **[RKNPU2 Runtime ↗](https://github.com/rockchip-linux/rknpu2)** - NPU运行时库
3. **[RKNN-Toolkit-Lite2 ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/rknn-toolkit-lite2)** - 设备端Python API
4. **[librga ↗](https://github.com/airockchip/librga)** - 2D图形加速库

### 模型库
1. **[RKNN Model Zoo ↗](https://github.com/airockchip/rknn_model_zoo)** - 30+预训练模型（YOLO11、SAM、Whisper、CLIP）
2. **[RKLLM ↗](https://github.com/airockchip/rknn-llm)** - 大语言模型部署栈

## 大语言模型
*RK3588支持边缘LLM部署，需使用RKLLM栈*
1. **支持模型**：TinyLlama 1.1B（约10-15 token/秒）、Qwen2 0.5B、Whisper
2. **[RKLLM Toolkit ↗](https://github.com/airockchip/rknn-llm)** - LLM转换与部署工具

## 操作系统
1. **[Ubuntu Rockchip ↗](https://github.com/Joshua-Riek/ubuntu-rockchip)** - Ubuntu 22.04/24.04 LTS（推荐）
2. **[Armbian ↗](https://www.armbian.com/)** - 官方RK3588支持
3. **[Buildroot RK3588 ↗](https://github.com/Military-Vehicle-Detection/buildroot-rk3588)** - 极简Buildroot
4. **[NixOS RK3588 ↗](https://github.com/ryan4yin/nixos-rk3588)** - 适用于香橙派/ROCK 5A的NixOS

## 项目
1. **[YOLOv8 C++ ↗](https://github.com/cqu20160901/yolov8_rknn_Cplusplus)** - 生产级YOLOv8推理
2. **[rknn-multi-threaded ↗](https://github.com/leafqycc/rknn-multi-threaded)** - 多线程NPU（性能+40%）
3. **[YOLOv5+DeepSORT ↗](https://github.com/Zhou-sx/yolov5_Deepsort_rknn)** - 实时目标跟踪
4. **[GStreamer MPP ↗](https://github.com/rockchip-linux/gstreamer-rockchip)** - 硬件加速视频管线
5. **[FFmpeg RKMPP ↗](https://github.com/rockchip-linux/ffmpeg-rockchip)** - 8K视频编解码

## 开发板
### 消费级/创客
1. **[香橙派5系列 ↗](http://www.orangepi.org/)** - 性价比最高（4-16GB，PCIe 3.0）
2. **[Radxa ROCK 5 ↗](https://radxa.com/products/rock5)** - 工业级，双网口
3. **[野火LubanCat RK3588 ↗](https://doc.embedfire.com/products/link/zh/latest/linux/ebf_lubancat.html)** - 接口丰富，中文文档完善

### 工业级
1. **ITOP-3588 ↗** - 北京迅为，完整技术支持
2. **FireFly ITX-3588J ↗** - Mini-ITX嵌入式版型

## 文档
### 技术文档
1. **[RK3588数据手册 ↗](https://www.rock-chips.com/uploads/pdf/2022.8.26/191/RK3588%20Brief%20Datasheet.pdf)** - 官方规格（6 TOPS，8K@60fps）
2. **[RKNN用户指南 ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/doc)** - 转换与部署指南
3. **[RKNPU2 API参考 ↗](https://github.com/rockchip-linux/rknpu2/blob/master/doc/Rockchip_RKNPU_User_Guide_RKNN_API_V2.0.0.pdf)** - C/C++ API文档

### 开发板专用
1. **[Radxa ROCK 5文档 ↗](https://docs.radxa.com/rock5)** - 优质英文文档
2. **[野火LubanCat手册 ↗](https://doc.embedfire.com/linux/rk3588/quick_start/zh/latest/)** - 最佳中文文档

## 开发工具
1. **[RKDevTool ↗](https://github.com/rockchip-linux/rkdeveloptool)** - 固件烧录工具
2. **[RKNN-Toolkit2 Docker ↗](https://github.com/airockchip/rknn-toolkit2/tree/master/docker)** - 预配置环境
3. **NPU监控**: `cat /sys/kernel/debug/rknpu/load`

## 示例代码
1. **[RKNN Model Zoo ↗](https://github.com/airockchip/rknn_model_zoo)** - 30+官方模型示例
2. **[rknn_api_demo ↗](https://github.com/rockchip-linux/rknpu2/tree/master/rknn_api_demo)** - 极简C API示例
3. **[RKLLM Examples ↗](https://github.com/airockchip/rknn-llm/tree/main/examples)** - LLM聊天机器人示例

## 社区
### 国际社区
1. **[Radxa论坛 ↗](https://forum.radxa.com/)** - ROCK系列社区
2. **[Armbian论坛 ↗](https://forum.armbian.com/forum/29-rockchip-3588-3566-3568-3399/)** - 操作系统级支持
3. **[香橙派论坛 ↗](http://www.orangepi.org/orangepibbsen/)** - 官方香橙派论坛

### 中文社区
1. **[iTOP-RK3588论坛 ↗](http://bbs.topeetboard.com/forum.php?mod=forumdisplay&fid=55)** - 北京迅为技术支持
2. **[野火LubanCat社区 ↗](https://forums.embedfire.com/c/lubancat/21)** - 野火电子

---

## 贡献 🤝

有提交请求吗？打开它，我们将尽快审查。如果您有任何建议或发现任何错误，请随时提出您的新想法！[贡献指南](contributing.md)

- [Open Issues](https://github.com/choushunn/awesome-RK3588/issues)
- [Open Pull Requests](https://github.com/choushunn/awesome-RK3588/pulls)
- [Open Discussions](https://github.com/choushunn/awesome-RK3588/discussions)

感谢所有代码贡献者。 [[Contribute](contributing.md)].

<a href="https://github.com/choushunn/awesome-RK3588/graphs/contributors"><img src="https://contrib.rocks/image?repo=choushunn/awesome-RK3588&max=200&columns=24" width=850px /></a>

================================================
FILE: contributing.md
================================================
# Contribution Guidelines

When contributing to the RK3588 project, please ensure that you adhere to the following guidelines:

- The pull request should have a useful title and include a link to the thing you're submitting and why it should be included.
- Don't open a Draft / WIP pull request while you work on the guidelines. A pull request should be 100% ready and should adhere to all the guidelines when you open it.
- If you just created something, wait at least 30 days before submitting.
- The project repo should have at least 20 stars.
- Search previous suggestions before making a new one, as yours may be a duplicate.
- Boilerplates are not accepted as most boilerplates are too opinionated and low-quality and I don't have time to comment on everything they need to improve.
- If you're submitting a closed source app, include evidence of it being built with RK3588.
- The "Closed Source" section has a very high bar for acceptance. You're a lot more likely to get accepted if you link to a blog post on how you built the app. Don't worry if your submission is declined, you can still submit your app to the official RK3588 apps list.
- Make an individual pull request for each suggestion.
- Use the following format: `[title](link) - Description.`
- Descriptions should be short and simple, but descriptive.
- Start the description with a capital and end with a full stop/period.
- Don't mention RK3588 in the description as it's implied.
- Don't start the description with A or An.
- Check your spelling and grammar.
- Make sure your text editor is set to remove trailing whitespace.
- New categories or improvements to the existing categorization are welcome, but should be done in a separate pull request.
- Thank you for your suggestion!

**Updating your PR**
A lot of times, making a PR adhere to the standards above can be difficult. If the maintainers notice anything that we'd like changed, we'll ask you to edit your PR before we merge it. If you're not sure how to do that, [here ↗](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests) is a guide on the different ways you can update your PR so that we can merge it.