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Jetson AGX Thor📖
1.Get started
  • 01.Learning Route
  • 02.Getting Started Quickly
2.Jetson basic course
  • 01.Jetson board introduction
  • 02.Flashing a Pure Jetson System via SDK
  • 03.Flashing a Pure Jetson System via USB Drive
  • 04.Flashing the Jetson Bootloader using L4T
  • 05.Replacing the SSD
  • 06.Install Jetpack environment
  • 07.Backup SSD system
  • 08.Restore factory image system
  • 09.SSD expansion
  • 10.SSD Speed Test
3.Basic setting course
  • 01.Basic knowledge
  • 02.Network configuration
  • 03.SSH remote login
  • 04.VNC remote control
  • 05.Remote file transfer
  • 06.Jtop tool
  • 07.Exchange space expansion
  • 08.Use VSCode
  • 09.Use VMware
  • 10.Change screen resolution
  • 11.Virtual Desktop
  • 12.Set root user password
  • 13.Configure sudo passwordless operation
  • 14.Managing custom services
  • 15.View system version information
4.OpenCV basic course
  • 01.Image reading
  • 02.Image saving
  • 03.Image modification
  • 04.Image scaling
  • 05.Image cropping
  • 06.Image translation
  • 07.Image mirroring
  • 08.Image grayscale conversion
  • 09.Image binarization
  • 10.Image edge detection
  • 11.Add line segments
  • 12.Add rectangles
  • 13.Add circular shape
  • 14.Add ellipses
  • 15.Add polygons
  • 16.Add Text
5.Vision basic course
  • 01.USB camera preview
  • 02.Use Jupyter Lab
  • 03.Use JetCam
6.Vision advanced course
01.Environment construction
  • 01.TensorFlow
  • 02.PyTorch
  • 03.Torchvision
  • 04.Torchaudio
02.DeepStream development
  • 01.DeepStream environment
  • 02.Four types of detection(traffic)
03.YOLO26 development
  • 01.YOLO Environment Setup
  • 02.CLI Usage
  • 03.Object Detection
  • 04.Instance Segmentation
  • 05.Pose Estimation
  • 06.Image Classification
  • 07.Oriented Bounding Boxes Object Detection
  • 08.Model Conversion
  • 09.Dataset Annotation
  • 10.Model Training_Conversion
  • 11.Model Prediction
04.Mediapipe development
  • 01.Mediapipe environment
  • 02.Hand detection
  • 03.Face detection
  • 04.Face effects
  • 05.3D object recognition
  • 06.Virtual brush
  • 07.Gesture recognition
  • 08.Finger control
  • 09.Posture estimation
  • 10.Face mask
  • 11.Overall detection
  • 12.Green scene removal(Human)
05.QR code recognition
  • 01.Barcode Recognition
  • 02.QR Code Recognition
  • 03.Machine Code Recognition
  • 04.Handwritten Digit Recognition
7.Docker basic course
  • 01.Docker introduction
  • 02.Docker installation
  • 03.Docker command
  • 04.Docker usage
  • 05.Docker interaction
8.ROS2-jazzy
1.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
2.ROS2 vision course
  • 01.Camera preview (USB)
  • 02.Camera calibration (USB)
  • 03.AR vision (USB)
9.Offline AI model course
Offline large model (Text Interaction)
  • 1.Al large model environment deployment
  • 2.Install large model dialogue platform
  • 3.Meta Al Llama3.2 model
  • 4.Alibaba Cloud Qwen3 model
  • 5.Microsoft Phi-4-mini model
  • 6.DeepSeek DeepSeek-R1 model
  • 7.Alibaba Cloud Qwen2.5v 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 video analysis application
  • 14.Multi module visual position application
  • 15.Multimodal table scanning application
  • 16.Multimodal autonomous agent application
Offline large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Offline speech to text (ASR)
  • 2.Offline text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multimodal text and graphics application
  • 6.Multimodal video analysis application
  • 7.Multi module visual position application
  • 8.Multimodal table scanning application
  • 9.Multimodal autonomous proxy application
  • 10.AI large model offline voice assistant
10.Online AI model course
Online large model (Text Interaction)
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal Video Analysis Applications
  • 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.Multi module visual position application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model offline voice assistant
11.Generative AI Applications
  • 0.Development Environment Setup
  • 01.Children's Storytelling Session
  • 02.Cooking Assistant
  • 03.Homework tutor
  • 04.Image to animation
12.OpenClaw Advanced Development
  • 00.OpenClaw Quick Start on Jetson Platform
  • 01.OpenClaw Installation
  • 02.OpenClaw Online Platform Deployment
  • 03.OpenClaw Local Model Deployment
  • 04.OpenClaw TUI Interaction
  • 05.OpenClaw WebChat Interaction
  • 06.OpenClaw Tools Introduction
  • 07.OpenClawGate Gateway User Manual
  • 08.OpenClaw Features Overview
  • 09.OpenClawClawHub Introduction (Skill Installation)
  • 10. OpenClaw Switching Models
  • 11.OpenClaw Application - File Management
  • 12.OpenClaw Application - Camera
  • 13.OpenClaw Application - Browser Control
  • 14.OpenClaw Application - Script Execution
  • 15.OpenClaw Application - AI Programming
  • 16.OpenClaw Application - Dedicated AI Assistant
  • 17.OpenClaw WhatsApp Plugin Application
  • 18.OpenClaw Voice Assistant
Download
  • Code
  • SystemFile
  • VM_File
  • Tools
  • Jetson boot files
Download ZIP

Welcome to Jetson AGX Thor repository

01.Children's Storytelling Session

Children's Storytelling

Children's Storytelling1. Function Introduction2. Hardware Connection and Setup3. Code Analysis4. Running the Code5. Demonstration Results

1. Function Introduction

This example program can be used to tell stories to children aged 4-7. Based on the child's speech, it generates a related short story and accompanying illustrations.

2. Hardware Connection and Setup

This example program requires not only a power adapter but also a large language model module for language input and output, a DP monitor, and a mouse and keyboard for displaying the interface and operation, or logging into a remote desktop.

image-20260408202523869

Open system settings, click Sound, select Speakers-USB Audio Device for Output Device, and Microphone-USB Audio Device for Input Device.

image-20260211115144308

3. Code Analysis

Source Code Path:

/home/jetson/showing/gpt-oss-storyteller/storyteller.py

The default is to use Chinese voice. If you need English voice, change the language variable to "en". The program will automatically switch to the English voice model and prompts.

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language = "en"

If you need to adjust the image window size, modify the values of self.win_width and self.win_height.

image-20260211143617952

If you need to modify the control buttons, control the start and stop buttons accordingly.

image-20260211143737275

The background will start a task to detect language activation. When you say "Hello, Xiaoya" to the language module, the module will be activated and start recording.

image-20260401161052839

If you need to adjust the recording duration, modify the value of the -d parameter; this value specifies the number of seconds after which the recording will automatically stop. The default setting is 10 seconds.

image-20260211143917038

If you need to manually input specific text, uncomment the text variable and enter your custom text.

image-20260211144131835

If you wish to change the opening prompt, search for OPENING_TEXT and modify the associated parameters. If you wish to modify the content used to generate the story and images, search for STORY_PROMPT and modify the associated parameters.

Note: For Chinese text, modify the variables located under the "zh" section; for English text, modify the variables located under the "else" section.

image-20260401160228672

If you wish to change the background image, modify the file path specified in initial_image. Please ensure that the image file is placed in the same directory as the program files.

image-20260211145727633

If you need to modify the serial port for the Large Language Model (LLM) module, the ComfyUI port, the Ollama server port, or the Piper model file, please modify the parameters listed below.

image-20260211150514779

4. Running the Code

Open a new system terminal and launch the ComfyUI service:

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cd ~/ComfyUI
source venv/bin/activate
python main.py

image-20260210162629624

image-20260210162433208

Open another new system terminal, activate the virtual environment, and launch the main storytelling program:

xxxxxxxxxx
cd ~/showing/
source venvs/bin/activate
cd gpt-oss-storyteller
python storyteller.py

image-20260211114844087

5. Demonstration Results

Once the program launches, a background image will appear.

At this point, you can wake up the Large Language Model (LLM) module by saying, "Hi, yahboom" or press the 's' key on your keyboard to begin recording. Then, simply voice your ideas. Wait for the recording to finish—or press the Spacebar to stop recording manually—and the speakers will play an audio prompt announcing that the story is about to begin. The system will then generate the story and convert it into speech for playback. As the narrative shifts between scenes, the background image will automatically update to display visuals relevant to the current setting.

image-20260211152238617

If you wish to end the story, you can press the ESC key. Alternatively, you can interrupt the current story—and restart the recording and story generation process—by saying, "Hello, Xiaoya," to the LLM module.

Development Environment Setup
Cooking Assistant

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