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introducing Google Coral to everyone

Helping you bring local AI to applications from prototype to production——Google Coral


About Coral technology

 Coral provides a complete platform for accelerating neural networks on embedded devices. At the heart of our accelerators is the Edge TPU coprocessor. It's a small-yet-mighty, low-power ASIC that provides high-performance neutral net inferencing.


Coral helps you bring on-device AI application ideas from prototype to production. We offer a platform of hardware components, software tools, and pre-compiled models for building devices with local AI.

 For prototyping
Google prototyping products make it easy to take your idea from sketch into proof-of-concept.

 For production
Google production products integrate seamlessly into processes at any scale, helping create tailored solutions for your industry.

 For sensing
Coral sensing products help deliver the real-world data you need to your machine learning system.


Dev Board: A single-board computer with a removable system-on-module (SoM) featuring the Edge TPU.

 USB Accelerator: A USB accessory featuring the Edge TPU that brings ML inferencing to existing systems.

 Mini PCIe Accelerator: A PCIe device that enables easy integration of the Edge TPU into existing systems.

 M.2 Accelerator A+E key/B+M key: A PCIe device that enables easy integration of the Edge TPU into existing systems.

 System-on-Module (SoM): A fully-integrated system for accelerated ML applications in a 40mm x 48mm pluggable module.

 Camera: 5-megapixel camera module that's compatible with the Coral Dev Board.

 Environmental Sensor Board: An accessory board that provides temperature, light and humidity sensors for IoT applications.
Google AIY & Coral Authorized Distributor & Partner : Gravitylink

 https://store.gravitylink.com/global

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How to Retrain an object detection model

This tutorial shows you how to retrain an object detection model to recognize a new set of classes. You'll use a technique called transfer learning to retrain an existing model and then compile it to run on an Edge TPU device—you can use the retrained model with either the Coral Dev Board or the Coral USB Accelerator. Specifically, this tutorial shows you how to retrain a MobileNet V1 SSD model (originally trained to detect 90 objects from the COCO dataset) so that it detects two pets: Abyssinian cats and American Bulldogs (from the Oxford-IIIT Pets Dataset). But you can reuse these procedures with your own image dataset, and with a different pre-trained model. The steps below show you how to perform transfer-learning using either last-layers-only or full-model retraining. Most of the steps are the same; just keep an eye out for the different commands depending on the technique you desire. Note: These instructions do not require deep experience with TensorFlow o...
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How to retrain an image classification model?

Got a tutorial from Google Coral Team: This tutorial shows you how to retrain an image classification model to recognize a new set of classes. You'll use a technique called transfer learning to retrain an existing model and then compile it to run on an Edge TPU device—you can use the retrained model with either the Coral Dev Board or the Coral USB Accelerator. Specifically, this tutorial shows you how to retrain a  quantized  MobileNet V1 model to recognize different types of flowers (adopted from TensorFlow's docs). But you can reuse these procedures with your own image dataset, and with a different pre-trained model. Tip:  If you want a shortcut to train an image classification model, try Cloud AutoML Vision. It's a web-based tool that allows you to train a model with your own images, optimize it, and then export it for the Edge TPU. Set up the Docker container Prepare your dataset Retrain your classification model Compile the model for the Edge TPU Run...
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Introducing Google Coral Edge TPU Device--Mini PCIe Accelerator

Mini PCIe Accelerator A PCIe device that enables easy integration of the Edge TPU into existing systems. Supported host OS: Debian Linux Half-size Mini PCIe form factor Supported Framework: TensorFlow Lite Works with AutoML Vision Edge https://store.gravitylink.com/global/product/miniPcIe The Coral Mini PCIe Accelerator is a PCIe module that brings the Edge TPU coprocessor to existing systems and products. The Mini PCIe Accelerator is a half-size Mini PCIe card designed to fit in any standard Mini PCIe slot. This form-factor enables easy integration into ARM and x86 platforms so you can add local ML acceleration to products such as embedded platforms, mini-PCs, and industrial gateways. https://store.gravitylink.com/global/product/miniPcIe Features Google Edge TPU ML accelerator Standard Half-Mini PCIe card Supports Debian Linux and other variants on host CPU About Edge TPU  The Edge TPU is a small ASIC designed by Google that provi...
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