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RDK S600 Developer Kit📖
1.RDK S600 board introduction
  • 1.1 RDK S600 board introduction
  • 1.2 System Flashing
  • 1.3 Hardware Interface Description
  • 1.4 Accessory Installation
  • 1.5 Camera Expansion Board
  • 1.6 MCU Interface Expansion Board
  • 1.7 Precautions for Using the 15.6-inch Screen
  • 1.8 System Boot Modes
2.RDK S600 basic course
  • 2.1 Network Configuration
  • 2.2 Remote Login
  • 2.3 System Update
  • 2.4 Boot Auto-Start Configuration
  • 2.5 RDK Exclusive Command Usage
  • 2.6 Linux Command Usage
  • 2.7 Examples of GPIO Read and Write Operations
  • 2.8 Using the USB Camera
  • 2.9 Solid-state mounting
  • 2.10 SSD expansionnew
3.TogetheROS.Bot Vision Applications
  • 1. About TogetheROS. Bot
  • 2. System Installation
  • 3. Object Detection(YOLO)
  • 4. Image Classification(mobilenetv2)
  • 5. Image Segmentation(mobilenet_unet)
  • 6. Perception Algorithm(BEV)
  • 7. Human Detection and Tracking (Ultralytics YOLO Pose)
4. Offline AI Large Model Development
Offline large model (Text Interaction)
  • 1. AI large model environment deployment
  • 2. Install large model dialogue platform
  • 3. Meta AI Llama 3.2 model
  • 4. Alibaba Cloud Qwen3 model
  • 5. Microsoft Phi-4 mini model
  • 6. DeepSeek - DeepSeek-R1 model
  • 7. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 8. Google Gemma3 Visual Multimodal Large Model
  • 9. Lava Visual Multimodal Large Model
  • 10. MiniCPM-V Visual Multimodal Large Model
  • 11. Multimodal visual understand application
  • 12. Multimodal text image application
  • 13. Multimodal visual localization application
  • 14. Multimodal table scanning application
  • 15. Multimodal Autonomous Agent Applications
Offline large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Offline speech-to-text (ASR)
  • 2. Offline Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual understanding voice interaction
  • 5. Multimodal Text-to-Image application
  • 6. Multimodal video analytics application
  • 7. Multimodal visual localization application
  • 8. Multimodal table scanning application
  • 9. Multimodal autonomous agent application
  • 10. AI Large Model Offline Voice Assistant
5. Online AI Large Model Development
Online large model (Text Interaction)
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal visual understand application
  • 3.Multimodal visual localization application
  • 4.Multimodal table scanning application
  • 5.Multimodal autonomous proxy application
Online large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Online speech to text (ASR)
  • 2.Online text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multimodal visual localization application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model online voice assistant
6.YOLO26 tutorials
  • 01.YOLO26 environment
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training - conversion
  • 11.Model prediction
7.OpenClaw Advanced Development
  • 1. OpenClaw Deployment
  • 2. OpenClaw and WhatsApp Plugin Application
  • 3. OpenClaw TUI Interaction
  • 4. OpenClaw WebChat Interaction
  • 5. OpenClaw Gate Gateway Operation Manual
  • 6. OpenClaw Plugin Function Introduction
  • 7. OpenClaw Tools Introduction
  • 8. OpenClaw ClawHub Introduction (skill Installation)
  • 9.OpenClaw Application - File Management
  • 10.OpenClaw Application - Browser Control
  • 11.OpenClaw Application - Camera
  • 12.OpenClaw Application - Script Execution
  • 13.OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 14. OpenClaw Application - Dedicated AI Assistant
  • 15. OpenClaw Configure Web Search Capability
8.ROS2 basic course
  • 1.Introduction to ROS2
  • 2.ROS2 install Jazzy
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
Download
  • System_File
  • Code
  • 3D_Model_File
  • Tools_Software
Download ZIP

Welcome to RDK S600 Developer Kit repository

01.YOLO26 environment

YOLO Environment Setup

YOLO Environment Setup1. One-Click Installation2. Installation Directory3. Example Source Code Porting

This chapter applies to those who set up using the RDK official image. If you are using the YAHBOOM version image, you can ignore this tutorial.

1. One-Click Installation

The following command automatically installs the environment required for yolov26. Please wait patiently.

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pip install -U ultralytics --break-system-packages

After installation is complete, restart the RDK development board.

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sudo reboot

2. Installation Directory

Use the following command to view the installation directory

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pip show ultralytics

image-20260613141634619

The source code is in the /home/sunrise/.local/lib/python3.12/site-packages/ultralytics directory.

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cd /home/sunrise/.local/lib/python3.12/site-packages/ultralytics

3. Example Source Code Porting

Port the source code provided in the materials to the /home/sunrise/ directory.

image-20260615141564872

Add environment and permissions

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pip install ncnn --break-system-packages
pip install --break-system-packages "onnx>=1.12.0,<2.0.0" onnxruntime "onnxslim>=0.1.82"
pip install --break-system-packages pnnx
chmod +x /home/sunrise/ultralytics26/yahboom_demo/*
AI large model online voice assistant
CLI use

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