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seeed studio USB Accelerator Features
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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.
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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.
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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.
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Supports TensorFlow lite：No need to build models from the ground up. Tensorflow Lite models can be compiled to run on USB Accelerator.
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Features: Fully supports MobileNet and Inception architectures though custom architectures are possible; Compatible with Google Cloud;
About Seeed Studio USB Accelerator
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
