Project tutorials and code examples to build intelligent devices with Coral

Project tutorials

Detailed instructions to help you bring local AI into the real world.

Teachable Sorter

A physical machine that you can teach to rapidly recognize and sort objects using your own custom machine learning models.

Smart Bird Feeder

A smart bird feeder that uses an image classification model to identify birds, record animal visits, and deter squirrels from stealing bird seed.

Embedded Teachable Machine

A machine that can quickly learn to recognize new objects by re-training a vision classification model directly on your device.


An implementation of AlphaGo Zero called Minigo, which uses machine learning to play the strategy board game "go" at expert levels.

Code examples

Simple examples showing how to run pre-trained models on your Coral device.


Pose estimation with video

Multiple examples showing how to use the PoseNet model to detect human poses from images and video, such as locating the position of someone’s elbow, shoulder or foot.


Image recognition with video

Multiple examples showing how to stream images from a camera and run classification or detection models with the TensorFlow Lite API. Each example uses a different camera library, such as GStreamer, OpenCV, PyGame, and PiCamera.

Keyphrase detector

A few examples using a keyphrase detection model that can detect over 140 short phrases such as "start game" and "next song." Includes a snake game and a YouTube player that respond to voice commands.

Semantic segmentation

An example that performs semantic segmentation with BasicEngine from the Edge TPU Python API. It takes an image as input and creates an image showing which pixels correspond to each recognized object.

Partner examples

More examples that use ML tools from our partners.

Fleet management with balenaCloud

This example uses balenaCloud to deploy an object detection model to a Dev Board and view live inferencing from a web page.