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Raspberry Pi 5📖
00.Quick Start (Must See)
  • 1.Quick Start (Must See)
  • 2.TF card expand capacity
  • 3.Raspberry Pi 5 - 1GB Version Must - See Before Use
01.Introduction to Raspberry PI 5
  • 1. Introduction to Raspberry PI 5
  • 2. Raspberry PI system installation and backup
  • 3. Powering the Raspberry PI 5
  • 4. Startup of Raspberry PI 5
  • 5. Installation and introduction of shell and active radiator
  • 6. GPIO and 40-pin pins
  • 7. Tips for using Raspberry PI 5
  • 8. Raspberry PI PCIe connector
  • 9. MIPI CSI DSI connector
  • 10. UART connector
  • 11. Real-time clock
  • 12. Power over Ethernet (PoE) connector
02.Introduction to common mirror systems
  • 1. Official Raspberry PI system
  • 2. Ubuntu
03.Basic settings of Raspberry Pi
  • 1. Update and upgrade operating system
  • 2.Introduction to raspi-config tool
  • 3.config.txt file description
  • 4.Network Configuration
  • 5.remote access
  • 6.Transfer files remotely
  • 7.Set display resolution and rotation
  • 8.Set screen to sleep
  • 9.Get real-time temperature of Raspberry Pi
  • 10.Play audio and video
  • 11.Using USB camera
  • 12.Using MIPI camera
04.Basic programming course
1. C language programming
  • 1. C language environment construction
  • 2. Print Hello World
2. Python programming
  • 1.Python usage
  • 2.Use APT to install Python packages
  • 3.Python virtual environment
  • 4.GPIO Zero
  • 5.Pin output high and low levels
  • 6.Pin reads high and low levels
  • 7.Pin output PWM
3.Jupyter lab programming
  • 1.Jupyter Lab environment construction
  • 2.Basic use of Jupyter Lab
  • 3.Jupyter Lab plug-in installation
  • 4.Basic use of Jupyter Widgets
05.Advanced AI course
5.Advanced AI gameplay
  • 1. Human pose estimation
  • 2. target detection
  • 3.yolov5
  • 4. Camera display
  • 5. QR code
  • 6. face detection
  • 7. Color recognition
2.Getting started with Open Source CV
  • 1. Introduction to Open Source CV
  • 2. Read and display Open Source CV images
  • 3. Open Source CV image writing
  • 4. Open Source CV image quality
  • 5.Open Source CV pixel operation
3.Open Source CV Geometric Transformations
  • 1. Image resizing
  • 2. Cut the image
  • 3. Image translation
  • 4. Image mirroring
  • 5. Affine transformation
  • 6. Rotate the image
  • 7. Perspective transformation
4.Text Picture Drawing Open Source CV image processing and drawing text line segments
  • 1、Grey Processing
  • 2、image binaryzation
  • 3、edge detection
  • 4、Line segment drawing
  • 5、Rectangle and circle drawing
  • 6、Text image drawing
1.Open Source CV environment setup
  • Open Source CV environment setup
6.YOLOv11 development
  • 1. YOLOv11 environment construction
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model conversion
  • 9. Dataset Annotation
  • 10. Model training_conversion
  • 11. Model prediction
7.YOLO26 development
  • 01.YOLO26 environment
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented bounding box object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training - conversion
  • 11.Model prediction
06.Mediapipe course
  • 1. Face special effects
  • 2. Face detection
  • 3. Three-dimensional object recognition
  • 4. Paintbrush
  • 5. Finger control
  • 6. Gesture recognition
07.Docker Tutorial
  • 1.Overview and installation
  • 2.Common commands
  • 3.Understand and publish images
  • 4.Hardware interaction data processing
  • 5.Enter docker container
  • 6.Update docker images
  • 7. docker container to install ROS using accessories
08.ROS1 advanced tutorial
1.ROS1 basic course
  • 1.ROS introduction
  • 2.ROS installation
  • 3.ROS common command tools
  • 4.ROS workspace
  • 5.ROS function package
  • 6.ROS node
  • 7.ROS topic publisher
  • 8.ROS topic subscribers
  • 9.ROS service client
  • 10.ROS service server
  • 11.ROS action client
  • 12.ROS action server
  • 13.ROS custom message reception
  • 14.ROS-launch file
  • 15.ROS-TF transformation
  • 16.ROS parameter service
  • 17.ROS-rviz use
  • 18.ROS-rqt tool usage
  • 19.Topic message recording and playback
  • 20.urdf model introduction
  • 21.gazebo introduction
  • 22.ROS distributed communication
2.ROS1 vision application
  • 0.Precautions
  • 1.AR vision
  • 2.AR QR code
  • 3.ROS+Opencv basics
  • 4.Face recognition
  • 5.harris corner detection
  • 6.Target tracking algorithm
  • 7.Contour moment
  • 8.Polygon outline
  • 9.Discrete fourier transform algorithm
  • 10.Edge detection algorithm
  • 11.Face detection algorithm
  • 12.Optical flow detection algorithm
  • 13.Contour detection
  • 14.General contour detection
  • 15.Feature point tracking
  • 16.HLS color filtering
  • 17.Hough circle detection
  • 18.Hough linear detection
  • 19.HSV color filtering
  • 20.LK optical flow algorithm
  • 21.detection algorithm
  • 22.Phase dependent displacement detection
  • 23.Image pyramid sampling algorithm
  • 24.RGB color filtering
  • 25.Clear background detection algorithm
  • 26.Simplified optical flow algorithm
  • 27.Simple filter
  • 28.Threshold image processing
  • 29.Watershed segmentation algorithm
09.ROS2 advanced tutorial
1.ROS2 basic course
  • 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
2.ROS2 vision application
  • 0.Precautions
  • 1.Opencv basic course
  • 2.ROS+opencv application
  • 3.QR code creation and recognition
  • 4.AR vision
  • 5.Interesting gameplay of mediapipe
10.Offline AI model coursenew
Offline large model (Text Interaction)
  • 0. AI large model image description
  • 1. Deployment of large AI model environments
  • 2. Switch Chinese input method
  • 3. Installation of large model dialogue platform
  • 4. Meta AI Llama 3.2 model
  • 5. Alibaba Cloud Qwen3 Model
  • 6. Microsoft Phi-4-mini model
  • 7. DeepSeek DeepSeek-R1 model
  • 8. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 9. Google Gemma3 Visual Multimodal Large Model
  • 10. Llava Visual Multimodal Large Model
  • 11.MiniCPM-V Visual Multimodal Large Model
  • 12. Multimodal Visual Understanding Applications
  • 13. Multimodal Text-Based Image Application
  • 14. Multimodal Video Analysis Application
  • 15. Multimodal visual positioning applications
  • 16. Multimodal table scanning application
  • 17. Multimodal Autonomous Agent Application
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 and voice interaction
  • 5. Multimodal Text-Based Image Application
  • 6. Multimodal Video Analysis Application
  • 7. Multimodal visual positioning applications
  • 8. Multimodal table scanning application
  • 9. Multimodal Autonomous Agent Applications
  • 10. AI large model offline voice assistant
11.Online AI model coursenew
Online large model (text interaction)
  • 1.OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal Visual Understanding Applications
  • 3. Multimodal visual positioning applications
  • 4. Multimodal table scanning application
  • 5. Multimodal Autonomous Agent Applications
Online large model (voice interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Online speech-to-text (ASR)
  • 2. Online Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual and voice interaction
  • 5. Multimodal visual positioning applications
  • 6. Multimodal table scanning application
  • 7. Multimodal Autonomous Agent Applications
  • 8. AI large model online voice assistant
12.OpenClaw Deployment and Basic Usagenew
  • 01. OpenClaw Deployment
  • 02. OpenClaw WhatsApp Plugin Application
  • 03. OpenClaw WebChat Interaction
  • 04. OpenClaw TUI Interaction
  • 05. OpenClaw Tools Introduction
  • 06. OpenClawGate Gateway User Manual
  • 07. OpenClaw Features Overview
  • 08. OpenClawHub Introduction (Skill Installation)
  • 09. OpenClaw Application - File Management
  • 10. OpenClaw Application - Camera
  • 11. OpenClaw Application - Browser Control
  • 12. OpenClaw Application - Script Execution
  • 13. OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 14. OpenClaw Application - Dedicated AI Assistant
13.OpenClaw Advanced Developmentnew
1.Preparation Before Use
  • 01. Peripheral Hardware Configuration
  • 02. OpenClaw API-KEY Configuration
  • 03. OpenClaw Model Switching
  • 04. OpenClaw Prompts
  • 05. AI Voice Interaction Configuration
  • 06. 3D Configuration Tests
2.OpenClaw AI Programming Peripheral Control
  • 1. Servo Control
  • 2. RGB Strip
  • 3. OLED Display
  • 4. Temperature and Humidity Sensor
  • 5. Camera Application
  • 6. AI Script Peripheral Control
3.OpenClaw Peripheral Integration Applications
  • 1. Plant Care Assistant
  • 2. AI Calorie Estimation
  • 3. AI Rock Paper Scissors Game
  • 4. AI Pet
  • 5. AI Weather Station
  • 6. Temperature and Humidity Dashboard
  • 7. Scheduled Tasks
Download
  • SystemFile
  • Code
  • SoftWare
  • 3D_Model_File
  • GuideManual
Download ZIP

Welcome to Raspberry Pi 5 repository

1.Overview and installation

1.Overview and installation

 

1.Overview and installation1.1、Docker overview1.1.1、why docker appears1.1.2、Docker's core idea1.1.3、Compare virtual machines to Docker1.1.4、docker architecture1.1.5、Docker core objects1.1.6、images, containers, repositories1.1.7、Docker operation mechanism1.2、docker installation

Docker Chinese website: https://www.docker-cn.com

Docker Hub (repository) official website: https://hub.docker.com

 

1.1、Docker overview

Docker is an application container engine project, developed based on the Go language and open source.

At present, ROS2's courses are all placed in Docker containers, and customers can experience learning to use containerized development methods.

1.1.1、why docker appears

Let's start with a few scenarios:

  1. O&M deploys the project you developed to the server, telling you that there is a problem and cannot be started. You ran around locally and found that there was no problem...
  2. The project to be launched is unavailable due to the update of some software versions...
  3. There are a lot of environmental content involved in the project, various middleware, various configurations, and the deployment of multiple servers...

These problems can actually be summed up in relation to the environment. To avoid various problems caused by different environments, it is best to deploy the project together with the various environments required by the project. For example, the project involves environments such as REDIS, MYSQL, JDK, ES, etc., and the entire environment is brought with you when deploying the JAR package. So the question is, how can you bring the project with the environment?

Docker is here to solve this problem!

1.1.2、Docker's core idea

 

image-20230424111123951

This is the logo of Docker, a whale full of containers, on the back of the whale, the containers are isolated from each other, which is the core idea of Docker. For example, if there were multiple applications running on the same server before, there may be port occupation conflicts of software, but now they can run alone after isolation. In addition, Docker can maximize the power of the server.

1.1.3、Compare virtual machines to Docker

 

  • The docker daemon can communicate directly with the main operating system to allocate resources to individual docker containers; It can also isolate containers from the main operating system and isolate individual containers from each other. Virtual machines take minutes to start, while docker containers can start in milliseconds. Since there is no bloated from the operating system, Docker can save a lot of disk space as well as other system resources.
  • Virtual machines are better at completely isolating the entire operating environment. For example, cloud service providers often use virtual machine technology to isolate different users. Docker is often used to isolate different applications, such as front-end, back-end, and database.
  • Docker containers are more resource-efficient and faster (start, shut down, create, delete) than virtual machines

1.1.4、docker architecture

Docker uses a client-server architecture. The Docker client communicates with the Docker daemon, which is responsible for building, running, and distributing the Docker container. The Docker client and daemon can run on the same system, or you can connect a Docker client to a remote Docker daemon. The docker client and daemon communicate using REST APIs over UNIX sockets or network interfaces. Another Docker client is Docker Compose, which lets you work with applications that consist of a set of containers.

30f24e4195234f58afbe43525dd57504

 

  • docker client is a docker command that is used directly after installing docker.
  • Docker host is our docker host (i.e. the operating system on which docker is installed)
  • Docker Daemon is Docker's background daemon that listens for and processes Docker client commands and manages Docker objects such as images, containers, networks, and volumes.
  • registry is a remote repository where docker pulls images, providing a large number of images for download, and saving them in images (local image repository) after downloading.
  • Images is a local image repository of docker, and image files can be viewed through docker images.

1.1.5、Docker core objects

 

1.1.6、images, containers, repositories

Image:

A docker image is a read-only template. Images can be used to create docker containers, and one image can create many containers. Just like classes and objects in Java, classes are images and containers are objects.

Container:

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Docker uses containers to run independently of an application or set of applications. A container is a running instance created from an image. It can be started, started, stopped, removed. Each container is an isolated platform for security. Think of a container as a simple version of the Linux environment (including root privileges, process space, user space, network space, etc.) and the applications running in it. The definition of a container is almost identical to an image, and it is also a unified view of a bunch of layers, the only difference is that the top layer of the container is readable and writable.

Repository:

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A repository is a place where image files are stored centrally. Repositories are divided into two forms: public repositories and private repositories.
The largest public repository is Docker Hub (https://hub.docker.com/), which houses a huge number of images for users to download. Domestic public warehouses include Alibaba Cloud, NetEase Cloud, etc.

You need to correctly understand the concepts of warehousing/image/container:

  • Docker itself is a container runtime carrier, or management engine. We package the application and configuration dependencies to form a shippable runtime environment, and this packaged runtime environment is like an image image file. Only this image file can generate a docker container. An image file can be thought of as a template for a container. Docker generates an instance of the container from the image file. The same image file allows you to generate multiple container instances running at the same time.
  • The container instance generated by the image file is itself a file, called an image file.
  • A container runs a service, and when we need it, we can create a corresponding running instance through the docker client, which is our container.
  • As for the repository, it is a place where a bunch of images are placed, we can publish the images to the repository, and pull them from the repository when needed.

1.1.7、Docker operation mechanism

Docker pull execution process:

  1. The client sends instructions to Docker Daemon
  2. Docker Daemon first check whether there are relevant images in the local images
  3. If there is no relevant image locally, request the mirror server to download the remote mirror to the local computer

docker run execution process:

  1. Check whether the specified image exists locally and download it from the public repository
  2. Create and start a container from the image
  3. Assign a file system (lite Linux system) and mount a read-write layer outside the read-only image layer
  4. Bridge a virtual interface from the bridge interface configured by the host to the container
  5. Configure an IP address from the address pool to the container
  6. Execute the application specified by the user

1.2、docker installation

  1. Official website installation reference manual: https://docs.docker.com/engine/install/ubuntu/
  2. You can use the following commands to install with one click:
xxxxxxxxxx
curl -fsSL https://get.docker.com | bash -s docker --mirror Aliyun
  1. Check the docker version
xxxxxxxxxx
sudo docker version

image-20230424113920974

  1. Test the command
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sudo docker run hello-world

The following output indicates that the Docker installation was successful

image-20230424113848585

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