jetson-examples

[](https://discord.gg/5BQCkty7vN) This repository provides examples for running AI models and applications on [NVIDIA Jetson devices](https://www.seeedstudio.com/reComputer-J4012-p-5586.html) with a single command. This repo builds upon the work of the [jetson-containers](https://github.com/dusty-nv/jetson-containers), [ultralytics](https://github.com/ultralytics/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: ```sh pip3 install jetson-examples ``` > Notes: > - Check [here](./docs/install.md) for more installation methods > - To upgrade to the latest version, use: `pip3 install jetson-examples --upgrade`. ## Quickstart To run and chat with [LLaVA](https://www.jetson-ai-lab.com/tutorial_llava.html), execute: ```sh reComputer run llava ``` ## Example list Here are some examples that can be run: | Example | Type | Model/Data Size | Docker Image Size | Command | | ------------------------------------------------ | ------------------------ | --------------- | ---------- | --------------------------------------- | | 🆕 llama-factory | Finetune LLM | | 13.5GB | `reComputer run llama-factory` | | 🆕 [ComfyUI](/reComputer/scripts/comfyui/README.md) |Computer Vision | | 20GB | `reComputer run comfyui` | | [Depth-Anything-V2](/reComputer/scripts/depth-anything-v2/README.md) |Computer Vision | | 15GB | `reComputer run depth-anything-v2` | | [Depth-Anything](/reComputer/scripts/depth-anything/README.md) |Computer Vision | | 12.9GB | `reComputer run depth-anything` | | [Yolov10](/reComputer/scripts/yolov10/README.md) | Computer Vision | 7.2M | 5.74 GB | `reComputer run yolov10` | | Llama3 | Text (LLM) | 4.9GB | 10.5GB | `reComputer run llama3` | | [Ollama](https://github.com/ollama/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](../reComputer/scripts/nanodb/readme.md) | Vector Database | 76GB | 7.0GB | `reComputer run nanodb` | | Whisper | Audio | 1.5GB | 6.0GB | `reComputer run whisper` | | [Yolov8-rail-inspection](/reComputer/scripts/yolov8-rail-inspection/readme.md) | Computer Vision | 6M | 13.8GB | `reComputer run yolov8-rail-inspection` | | [Ultralytics-yolo](/reComputer/scripts/ultralytics-yolo/README.md) | Computer Vision | | 15.4GB | `reComputer run ultralytics-yolo` | | [TensorFlow MoveNet Thunder](/reComputer/scripts/MoveNet-Thunder/readme.md) |Computer Vision | | 7.7GB | `reComputer run MoveNet-Thunder` | | [Parler-TTS mini: expresso](/reComputer/scripts/parler-tts/readme.md) | 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](./docs/examples.md) ## Calling Contributors Join Us! ### How to work with us? Want to add your own example? Check out the [development guide](./docs/develop.md). 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](https://github.com/orgs/Seeed-Studio/projects/6/views/1?filterQuery=jetson&pane=issue&itemId=64891723). If this is your first time joining us, [click here](https://github.com/orgs/Seeed-Studio/projects/6/views/1?pane=issue&itemId=30957479) 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 - https://github.com/dusty-nv/jetson-containers - https://www.jetson-ai-lab.com/ - https://www.ultralytics.com/