Real-time portrait segmentation for mobile devices

Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot

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.

The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.

Dockerfile and docker-compose file to enable google coral USB accelerators in containers on Synology DSM 7

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

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

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

Use the Google Coral USB Accelerator for deep learning.

Benchmarking machine learning inferencing on embedded hardware.

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

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

Google Coral TPU DKMS Driver package for Fedora, RHEL, OpenSUSE, and OpenMandriva

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.

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

Coral Edge TPU compilable version of DeepLab V3

m.2 B+M Coral TPU card for Raspberry Pi CM4

use edgetpu_compiler from anywhere with docker