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jetson-examples

jetson

Discord

This repository provides examples for running AI models and applications on NVIDIA Jetson devices with a single command.

This repo builds upon the work of the jetson-containers, ultralytics and other excellent projects.

Features

  • 🚀 Easy Deployment: Deploy state-of-the-art AI models on Jetson devices in one line.
  • 🔄 Versatile Examples: Supports text generation, image generation, computer vision and so on.
  • ⚡ Optimized for Jetson: Leverages Nvidia Jetson hardware for efficient performance.

Install

To install the package, run:

pip3 install jetson-examples

Notes:

  • Check here for more installation methods
  • To upgrade to the latest version, use: pip3 install jetson-examples --upgrade.

Quickstart

To run and chat with LLaVA, execute:

reComputer run llava
jetson

Example list

Here are some examples that can be run:

Example Type Model/Data Size Docker Image Size Command
🆕 Ultralytics-yolo Computer Vision 15.4GB reComputer run ultralytics-yolo
🆕 Deep-Live-Cam Face-swapping 0.5GB 20GB reComputer run deep-live-cam
🆕 llama-factory Finetune LLM 13.5GB reComputer run llama-factory
🆕 ComfyUI Computer Vision 20GB reComputer run comfyui
Depth-Anything-V2 Computer Vision 15GB reComputer run depth-anything-v2
Depth-Anything Computer Vision 12.9GB reComputer run depth-anything
Yolov10 Computer Vision 7.2M 5.74 GB reComputer run yolov10
Llama3 Text (LLM) 4.9GB 10.5GB reComputer run llama3
Ollama Inference Server * 10.5GB reComputer run ollama
LLaVA Text + Vision (VLM) 13GB 14.4GB reComputer run llava
Live LLaVA Text + Vision (VLM) 13GB 20.3GB reComputer run live-llava
Stable-diffusion-webui Image Generation 3.97G 7.3GB reComputer run stable-diffusion-webui
Nanoowl Vision Transformers(ViT) 613MB 15.1GB reComputer run nanoowl
Nanodb Vector Database 76GB 7.0GB reComputer run nanodb
Whisper Audio 1.5GB 6.0GB reComputer run whisper
Yolov8-rail-inspection Computer Vision 6M 13.8GB reComputer run yolov8-rail-inspection
TensorFlow MoveNet Thunder Computer Vision 7.7GB reComputer run MoveNet-Thunder
Parler-TTS mini: expresso Audio 6.9GB reComputer run parler-tts

Note: You should have enough space to run example, like LLaVA, at least 27.4GB totally

More Examples can be found examples.md

Calling Contributors Join Us!

How to work with us?

Want to add your own example? Check out the development guide.

We welcome contributions to improve jetson-examples! If you have an example you'd like to share, please submit a pull request. Thank you to all of our contributors! 🙏

This open call is listed in our Contributor Project. If this is your first time joining us, click here to learn how the project works. We follow the steps with:

  • Assignments: We offer a variety of assignments to enhance wiki content, each with a detailed description.
  • Submission: Contributors can submit their content via a Pull Request after completing the assignments.
  • Review: Maintainers will merge the submission and record the contributions.

Contributors receive a $250 cash bonus as a token of appreciation.

For any questions or further information, feel free to reach out via the GitHub issues page or contact edgeai@seeed.cc

TODO List

  • detect host environment and install what we need
  • all type jetson support checking list
  • try jetpack 6.0
  • check disk space enough or not before run
  • allow to setting some configs, such as BASE_PATH
  • support jetson-containers update
  • better table to show example's difference

License

This project is licensed under the MIT License.

Resources