Google Coral USB Accelerator

Product Information

Easily build and deploy fast, high-accuracy custom image classification models to your device with AutoML Vision Edge. The Coral Edge TPU is a revolutionary product for machine learning applications. This enables embedded solutions that can, for example, recognize problems with workpieces, recognize traffic situations and much more. Resources https://buyzero.de/collections/google-aiy-coral/products/aiy-maker-kit-includes-raspberry-pi-coral-usb-accelerator Note: this is NOT the TensorFlow Lite API, but an alternative API intended for users who have not used TensorFlow before and simply want to start with image classification and object detection Notably, these products are excluded from selling into France and the Czech Republic, and several embargo countries including China.

No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU.Simply connect via USB to any system running Debian Linux (including Raspberry Pi), macOS, or Windows 10 and you’re good to go! It’s a versatile little gadget that can be integrated into various setups. Connects via USB to any system running Debian Linux (including Raspberry Pi), macOS, or Windows 10. Supports TensorFlow Lite

With that said, the table below compares the time spent to perform a single inference with several popular models on the Edge TPU. For the sake of comparison, all models running on both CPU and Edge TPU are the TensorFlow Lite versions. No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU. Tech specs An individual Edge TPU is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt). How that translates to performance for your application depends on a variety of factors. Every neural network model has different demands, and if you're using the USB Accelerator device, total performance also varies based on the host CPU, USB speed, and other system resources. you can instead flash your SD card with the AIY Maker Kit system image, which includes everything you need to use

Specification

The on-board Edge TPU coprocessor is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt). For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 FPS, in a power efficient manner. See more performance benchmarks. Supports all major platforms QTS is the operating system for entry- and mid-level QNAP NAS. WIth Linux and ext4, QTS enables reliable storage for everyone with versatile value-added features and apps, such as snapshots, Plex media servers, and easy access of your personal cloud. System