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flagProduct From India  
new | seeed studio Google Coral USB Accelerator
Brand : seeed studio
new | seeed studio Google Coral USB Accelerator
Brand : seeed studio
Product Specifications
Conditionnew
AsinB07XYZ69GK
CategoryComputers & Accessories
SubcategoryBarebones
LeafcategoryELECTRONIC_CABLE
MPN114991790
OriginIndia
Brandnameseeed studio
Weight1
Product Details
Coral USB accessory that brings machine learning inferencing to existing systems. Works with Raspberry Pi (Pi2/3/4 Model B / B+) and other Linux systems.
Featuring the Edge TPU — a small ASIC designed and built by Google— the USB Accelerator provides high performance ML inferencing with a low power cost over a USB 3.0 interface.
Edge TPU key benefits:High-speed TensorFlow Lite inferencing;Low power;Small footprint. Coral is a division of Google, that helps you build intelligent ideas with our platform for local AI.
Supports TensorFlow lite:No need to build models from the ground up. Tensorflow Lite models can be compiled to run on USB Accelerator.
Features: Fully supports MobileNet and Inception architectures though custom architectures are possible; Compatible with Google Cloud;
Product Description
FEATURES
Google Edge TPU ML accelerator coprocessor
USB 3.0 Type-C socket
Supports Debian Linux on host CPU
Models are built using TensorFlow
Fully supports MobileNet and Inception architectures though custom architectures are possible
Compatible with Google Cloud

SPECS
Edge TPU ML accelerator
ASIC designed by Google that provides high performance ML inferencing for TensorFlow Lite models

Arm 32-bit Cortex-M0+ Microprocessor (MCU)
Up to 32 MHz max
16 KB Flash memory with ECC
2 KB RAM

Connections
USB 3.1 (gen 1) port and cable (SuperSpeed, 5Gb/s transfer speed)
Included cable is USB Type-C to Type-AU

Local inferencing
Run on-device ML inferencing on the Edge TPU designed by Google.

Works with Debian Linux
Connect to any Linux-based system with an included USB Type-C cable.

Supports TensorFlow lite
No need to build models from the ground up. Tensorflow Lite models can be compiled to run on USB Accelerator.

Requirements
The Coral USB Accelerator must be connected to the hostcomputer which is consistent with the following specifications:
All kinds of Linux computer with a USB port
Debian6.0 or higher,or any derivative thereof(such as Ubuntu10.0+)

System architecture of either x86_64 or ARM64 with ARMv8 instruction set

Raspberry Pi
Raspberry Pi2/3 Model B / B+ only
Also note that to reach the best inference speed, you should use a USB 3.0 port.(unfortunately, Raspberry Pi has only USB 2.0 port)

Tech Specs
ML accelerator:Google Edge TPU coprocessor
Connector:USB Type-C* (data/power)
Dimensions:65 mm x 30 mm

Part List
1 x Coral USB Accelerator

Product Description
FEATURES
Google Edge TPU ML accelerator coprocessor
USB 3.0 Type-C socket
Supports Debian Linux on host CPU
Models are built using TensorFlow
Fully supports MobileNet and Inception architectures though custom architectures are possible
Compatible with Google Cloud

SPECS
Edge TPU ML accelerator
ASIC designed by Google that provides high performance ML inferencing for TensorFlow Lite models

Arm 32-bit Cortex-M0+ Microprocessor (MCU)
Up to 32 MHz max
16 KB Flash memory with ECC
2 KB RAM

Connections
USB 3.1 (gen 1) port and cable (SuperSpeed, 5Gb/s transfer speed)
Included cable is USB Type-C to Type-AU

Local inferencing
Run on-device ML inferencing on the Edge TPU designed by Google.

Works with Debian Linux
Connect to any Linux-based system with an included USB Type-C cable.

Supports TensorFlow lite
No need to build models from the ground up. Tensorflow Lite models can be compiled to run on USB Accelerator.

Requirements
The Coral USB Accelerator must be connected to the hostcomputer which is consistent with the following specifications:
All kinds of Linux computer with a USB port
Debian6.0 or higher,or any derivative thereof(such as Ubuntu10.0+)

System architecture of either x86_64 or ARM64 with ARMv8 instruction set

Raspberry Pi
Raspberry Pi2/3 Model B / B+ only
Also note that to reach the best inference speed, you should use a USB 3.0 port.(unfortunately, Raspberry Pi has only USB 2.0 port)

Tech Specs
ML accelerator:Google Edge TPU coprocessor
Connector:USB Type-C* (data/power)
Dimensions:65 mm x 30 mm

Part List
1 x Coral USB Accelerator