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RDK X5 MagicBox📖
1.RDK MagicBox
  • 1. RDK MagicBox Official Materials
  • 2. Troubleshooting boot failure
  • 3. Linux memory query
2.RDK MagicBox Introduction
  • 1. Introduction to RDK MagicBox
  • 2. Write System File
  • 3. Hardware Interface Description
3.RDK MagicBox User Guide
1. Quick Start
  • Quick Start
2. Basic Peripheral Usage
  • Basic Peripheral Usage
3. Algorithm Development
  • 1. Stereo Depth Estimation
  • 2. Gesture Interaction
  • 3. Voice Interaction
4.RDK MagicBox Basic Settings
  • 1.Network configuration
  • 2.Remote login
  • 3.Update system
  • 4.srpi-config user guide
  • 5.config. txt configuration file
  • 6.Self-startup setting
  • 7.RDK exclusive command usage
  • 8.Linux command usage
  • 9.GPIO readwrite operation
  • 10.Image classification algorithm
  • 11.Use USB camera
  • 12.MIPI Camera Usage
5.RDKX5 Magicbox Basic Development Course
For C language
  • 1. Camera Image Acquisition and Display
  • 2. Camera Image Local Saving
  • 3. Camera Image Acquisition and Encoding
  • 4. Video File Decoding and Display
  • 5. RTSP Stream Decoding
  • 6. VPS Scaling Example
  • 7. Target Detection Algorithm — focs
  • 8. Target Detection Algorithm — YOLOv5s
  • 9. Using CAN
For Python language
  • 1. Prerequisites Before Using Pin Functions
  • 2. Using GPIO
  • 3. Using PWM
  • 4. Use serial port
  • 5. Using I2C
  • 6. Using SPI
For Linux Development
  • Linux Development Guide
6.Online AI Model Course
Online AI Model Course(Text Interaction)
  • 0. Preparation before use
  • 1. OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal Visual Understanding Application
  • 3. Multimodal Visual Positioning Application
  • 4. Multimodal Table Scanning Application
  • 5. Multimodal Autonomous Agent Application
Online AI Model Course(Voice Interaction)
  • 1. Online Speech‑to‑Text (ASR)
  • 2. Online Text‑to‑Speech (TTS)
  • 3. AI Large Model Voice Interaction
  • 4. Multimodal Visual Voice Interaction
  • 5. Multimodal Visual Positioning Application
  • 6. Multimodal Table Scanning Application
  • 7. Multimodal Autonomous Agent Application
  • 8. AI Large Model Online Voice Assistant
7.OpenClaw Embodied AI Development
  • 1. Introduction to OpenClaw
  • 2. OpenClaw Deployment
  • 3. OpenClaw Whatsapp Plugin Application
  • 4. OpenClaw WebChat Interaction
  • 5. OpenClaw TUI Interaction
  • 6. OpenClaw Tool Introduction
  • 7. OpenClawGate Gateway User Manual
  • 8. OpenClaw Plugin Feature Introduction
  • 9. OpenClaw ClawHub Introduction (skill installation)
  • 10. OpenClaw Application - File Management
  • 11. OpenClaw Application - Camera
  • 12. OpenClaw Application - Browser Control
  • 13. OpenClaw Application - Script Execution
  • 14. OpenClaw Application - AI‑programmed Status Light Control
  • 15. OpenClaw Application - AI‑programmed Servo Control
  • 16. OpenClaw Application - Dedicated AI Assistant
8.ROS2 Basic Tutorial
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 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
  • Code
  • Software_tools
  • SystemFile
Download ZIP

Welcome to RDK X5 MagicBox repository

2. Camera Image Local Saving

Local save camera images

Local save camera images1. Experimental preparation2. How to run3. Expected results

1. Experimental preparation

This example vio_capture implements the function of capturing images from MIPI cameras and saving images in two formats, RAW and YUV, locally.

The example flow chart is as follows.

 

  • When the development board is powered off, connect the MIPI camera to the development board (with the black side facing the HDMI interface).
  • Connect the development board and the monitor via an HDMI cable
  • Power on the development board and log in to the system

2. How to run

The sample code is provided in source code form. You need to use the make command to compile and run it.

The steps are as follows.

xxxxxxxxxx
sunrise@ubuntu:~$ cd /app/cdev_demo/vio_capture/
sunrise@ubuntu:/app/cdev_demo/vio_capture$ sudo make
sunrise@ubuntu:/app/cdev_demo/vio_capture$ sudo ./capture -b 12 -c 10 -h 1080 -w 1920

参数说明:

Parameter description:

  • -b: RAW image bit number, IMX219 / IMX477 / OV5647 are all set to 16, only a few camera sensors need to be set to 8
  • -c: Number of saved images
  • -w: Width of saved images
  • -h: Height of saved images

 

3. Expected results

After the program runs correctly, the current directory will save the specified number of image files.

The RAW format is named in the raw_*.raw format, and the YUV format is named in the yuv_*.yuv format.

The running log is as follows.

sunrise@ubuntu:/app/cdev_demo/vio_capture$ sudo ./capture -b 12 -c 10 -h 1080 -w 1920
Setting VPS channel-2: src_w:1920, src_h:1080; dst_w:1920, dst_h:1080;
Setting VPS channel-1: src_w:1920, src_h:1080; dst_w:1920, dst_h:1080;
jiale:start streaming...
capture time :0
capture time :1
capture time :2
capture time :3
capture time :4
capture time :5
capture time :6
capture time :7
capture time :8
capture time :9
sensor_name imx477, setting_size = 1
[  701.213210]hb_isp_algo_stop@main_user.c:389 GENERIC(ERR) :g_mutex destroy.
Camera Image Acquisition and Display
Camera Image Acquisition and Encoding

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