Examples

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

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

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.

An example that performs image classification with a photo.

An example that performs object detection with a photo and draws a square around each object. Also works with face detection models.

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.

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.

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.

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.

This uses MediaPipe to perform real-time object detection with your camera.

This uses MediaPipe to perform real-time face detection with your camera.