Explore and learn from Jetson projects created by us and our community. These projects have been built for Jetson Nano, Jetson AGX Xavier, and Jetson TX2

Have a Jetson project to share? Post it on our forum for a chance to be featured here too. Every month, we’ll award one project with a Jetson AGX Xavier Developer Kit that’s a cut above the rest for its application, inventiveness and creativity.


JetBot

Open-source project for learning AI by building fun applications. It’s easy to set up and use, is compatible with many accessories and includes interactive tutorials showing you how to harness the power of AI to follow objects, avoid collisions and more. The kit includes the complete robot chassis, wheels, and controllers along with a battery and 8MP camera. Supports AI frameworks such as TensorFlow and PyTorch.

Hello AI World

Jetson Nano Jetson TX2 Jetson AGX Xavier

Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection (using pretrained models) on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You also get to code your own easy-to-follow recognition program in C++.

Donkey Car 3.0 with Jetson Nano

By Rahul Ravikumar
Jetson Nano

Having read some amazing books on machine learning, I had been looking for opportunities to apply ML from first principles in the real world. That was what got me curious about the wonderful Donkey® Car project. The project is essentially a how-to guide to building your own RC car which can drive itself around a track using classical control theory, computer vision or in my case machine learning. I wanted to experiment with more sophisticated models. As I was constrained by the CPU on the Asus Tinkerboard S, I decided to level-up using the NVIDIA Jetson Nano.

Image: Rahul Ravikumar

Smart Doorbell Camera

By Adam Geitgey
Jetson Nano

We’ll create a simple version of a doorbell camera that tracks everyone that walks up to the front door of your house. With face recognition, it will instantly know whether the person at your door has ever visited you before—even if they were dressed differently. And if they have visited, it can tell you exactly when and how often.

Image: Adam Geitgey

Open Source Autocar (1/10th scale) with Jetson Nano

By Joseph Bastulli
Jetson Nano

With this open-source autocar powered by Jetson Nano, you can seamlessly toggle between your remote-controlled manual input and your AI-powered autopilot mode!

Image: Joseph Bastulli

OpenPose

By karaage
Jetson Nano

Run real-time, multi-person pose estimation on Jetson Nano using a Raspberry Pi camera to detect human skeletons, just like Kinect does. With this setup environment, obtain about 7–8fps performance.

Image: karaage

Donkey Car with Jetson Nano

By Fei Cheung
Jetson Nano

Open source hardware and software platform to build a small scale self driving car. Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.

Image: Fei Cheung

Jetson Nano Detection and Tracking

By Steve Macenski
Jetson Nano

This repository is my set of install tools to get [Jetson] Nano up and running with a convincing and scalable demo for robot-centric uses. In particular, using detection and semantic segmentation models capable at running in real-time on a robot for $100. By convincing, I mean not using NVIDIA's 2-day startup model you just compile and have magically working without having control. This gives you full control of which model to run and when.

Image: Steve Macenski

Fast Object Detector for the Jetson Nano

By Carroll Vance
Jetson Nano

MobileDetectNet is an object detector which uses MobileNet feature extractor to predict bounding boxes. It was designed to be computationally efficient for deployment on embedded systems and easy to train with limited data. It was inspired by the simple yet effective design of DetectNet and enhanced with the anchor system from Faster R-CNN.

Using an FP16 TF-TRT graph the model runs at ~55 FPS on the Jetson Nano in mode 1 (5W).

Image: Carroll Vance

OpenCV with CUDA for Jetson Nano

By Michael de Gans
Jetson Nano

A small script to build OpenCV 4.1.0 on a barebones system. The script installs build dependencies, clones a requested version of OpenCV, builds it from source, tests it, and installs it.

Jetson Nano Insulator Detection: Compare TensorFlow & TensorRT

By ICC TOBOROBOT
Jetson Nano

Detection insulator with ssd_mobilenet_v1 custom trained network. Testing with tensorflow frozen graph gives about 0.07sec per one image (~15FPS). I have recieved better result (about 20fps) with TensorRT library.

Image: ICC TOBOROBOT

Interface Touch Sensor, Accelerometer, IV Sensor, OLED

By Elaine Wu, Seeed Studio
Jetson Nano

Grove is an open source, modulated, and ready-to-use toolset. It takes a building block approach to assembling electronics, […] [simplifying] the learning process. If you want to use Grove sensors with Jetson Nano, the best way is to grab the grove.py Python library and get your sensors up in running in minutes! Currently there are more than 20 Grove modules supported on Jetson Nano […].

Image: Seeed Studio

Have a Jetson project to share? Post it on our forum for a chance to be featured here too. Every month, we’ll award one project with a Jetson AGX Xavier Developer Kit that’s a cut above the rest for its application, inventiveness and creativity.