Neuralet is an open-source platform for edge deep learning models on edge TPU, Jetson Nano, and more.

Social Distancing Detector using deep learning and capable to run on edge AI devices such as NVIDIA Jetson, Google Coral, and more.

This example will help you deploy a streaming camera feed with realtime people detection using the Coral Edge TPU for on-device ML inferencing.

Streamlining the process for seamless execution of PyCoral in running TensorFlow Lite models on an Edge TPU USB.

Object detection at the edge, with Google's Coral dev board

Benchmarking machine learning inferencing on embedded hardware.

Machine Learning Based Real-Time Traffic Light Alert on Your Car with Raspberrypi

Performance testing of 24 Machine Learning models on Raspberry Pi using TensorFlow Lite and Google Coral USB Accelerator

Testing Google Coral USB Accelerator's performance with 04 models of Raspberry Pi. Results have shown 10 times faster inferencing speeds with the Coral hardware attached.

Coral Edge TPU compilable version of DeepLab V3

Pigeon Repellent with Artificial Intelligence

Use the TensorFlow Object Detection API to train models for the Google Coral Edge TPU.

High FPS live stream Raspberry Pi cam with object detection by Google Coral EdgeTPU

A simple and real-time traffic monitoring solution using TensorFlow and OpenCV.

An AI powered rear facing radar for your bike. Instead of using mmWave radar tech, this project uses an inexpensive raspberry pi zero 2, a camera and Coral.ai TPU accelerator to detect objects behind you.

Face Recognition using Coral USB Accelerator, Flask and SocketIO.

Contains a service that allows you to run ultralytics yolo on your cpu(not recommended) or coral tpu the api has the same request and response as deepstack, this enables the usage with frigate.

A very basic example of using a Coral TPU from within a docker container

Bachelor Thesis. This work consists of designing a miniature autonomous car that can follow a road, detect signalisations and obstacles.