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

Examples showing how to use the PoseNet model to detect human poses from images and video, such as where someone’s elbow, shoulder or foot appear in the image.

Image recognition with a camera

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

TensorFlow Lite API and Raspberry Pi Camera

This example performs real-time classification using the TensorFlow Lite Python API and Raspberry Pi Camera.

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.

Partner examples

More examples that use ML tools from our partners.