跳至主要内容

New Google Coral Hardware are released at Gravitylink Store!

Google New Coral Hardware has released for months, and now they've already available at Gravitylink online store!




  •  Google Coral Edge TPU Mini PCIe Accelerator


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


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.


  • Google Coral Edge TPU M.2 Accelerator (A+E / B+M key)


Integrate the Edge TPU into legacy and new systems using an M.2 A+E/B+M key interface.

The Coral M.2 Accelerator is an M.2 module that brings the Edge TPU coprocessor to existing systems and products.



The M.2 Accelerator is a dual-key M.2 card (either A+E or B+M keys), designed to fit any compatible M.2 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.


  • Environmental Sensor Board

An accessory board that provides temperature, light and humidity sensors for IoT applications.

The Environmental Sensor Board is an add-on board (also known as a pHAT or bonnet) that adds sensing capabilities to your Coral Dev Board or Raspberry Pi projects. (It includes an EEPROM for compatibility with Raspberry Pi boards.)

The board provides atmospheric data such as light level, barometric pressure, temperature, and humidity. You can also attach additional sensors with the Grove connectors.

The board also includes a secure cryptoprocessor with Google keys to enable connectivity with Google Cloud IoT Core services, allowing you to securely connect to the device and then collect, process, and analyze the sensor data.

Compatible with Coral and Raspberry Pi boards.


  • System-on-Module (SoM)


A fully-integrated system for accelerated ML applications (includes CPU, GPU, Edge TPU, Wi-Fi, Bluetooth, and Secure Element), in a 40mm x 48mm pluggable module.

The Coral System-on-Module (SoM) is a fully-integrated system that helps you build embedded systems that demand fast machine learning (ML) inferencing. It contains NXP's iMX8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, but its unique power comes from Google's Edge TPU coprocessor.

The Edge TPU is a small ASIC designed by Google that provides high performance ML inferencing with a low power cost. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 400 FPS, in a power efficient manner. This on-device processing reduces latency, increases data privacy, and removes the need for a high-bandwidth connection used to perform ML inferencing in the cloud.

If you are interested in Google Coral products, and more details about large volume or bulk sales (Volume Discounts) at #Gravitylink online store  (https://store.gravitylink.com/global), welcome to contact our sales team via email: sales@gravitylink.com or market@gravitylink.com, and we'll get back to you with our best quotation ASAP.


评论

此博客中的热门博文

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...

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...

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...