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USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
MZN 9170
Price Details
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*All items will import from Reino Unido
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Coral USB Accelerator provides high performance ML inferencing with a low power cost over a USB 3.0 interface.
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O que se Destaca
Detalhes do produto
- Powerful ML inferencing capabilities with low power cost over USB 3.0
- Executes state-of-the-art mobile vision models at 100+ fps
- Developed in TensorFlow Lite and supports MobileNet and Inception architectures
- High speed inferencing with low power consumption and small footprint
- Built using Arm Cortex-M0+ Microprocessor with 16 KB Flash memory
- Compatible with Google Cloud and supports Debian Linux on host CPU
| Memory Storage Capacity | 16 KB |
| Network Connectivity Technology | USB |
| Operating System | Linux |
| Processor Brand | ARM |
| Processor Count | 1 |
| Total USB Ports | 1 |
| Item Dimensions L x W x H | 7.6L x 5.1W x 2.5H centimetres |
| Brand Name | Google Coral |
| Model Name | Coral-USB-Accelerator |
| UPC | 608614201389 |
| Model Number | Coral-USB-Accelerator |
| Manufacturer Part Number | Coral-USB-Accelerator |
| Manufacturer | Google Coral |
| Brand | Google-Coral |
| Connectivity technology | USB |
Quem Deverá Comprar?
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AI Developers
Ideal for developers creating machine learning applications requiring fast inference on edge devices and single board computers.
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Embedded System Hobbyists
Perfect for hobbyists wanting to add AI capabilities to their Raspberry Pi and other embedded systems projects.
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Robotics Engineers
Useful for robotics engineers needing real-time object detection and classification with minimal latency in applications.
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General Users
Not suitable for casual users lacking programming skills or AI knowledge to leverage advanced machine learning capabilities.
DESCRIÇÃO DO PRODUTO
USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
About This Item
Introducing the Google Coral USB Edge TPU ML Accelerator - the ultimate coprocessor for Raspberry Pi and other embedded single board computers. This powerful device brings advanced machine learning (ML) inferencing capabilities to your existing Linux systems. Featuring the highly efficient Edge TPU, a small ASIC designed and developed by Google, the Coral USB Accelerator provides you with high-performance ML inferencing while consuming minimal power through a USB 3.0 interface. With its cutting-edge technology, this accelerator can execute state-of-the-art mobile vision models, such as MobileNet v2, at over 100 frames per second in a power-efficient manner. The Coral USB Accelerator allows you to enable fast ML inferencing on your embedded AI devices, all while maintaining a power-efficient and privacy-preserving approach.
Models are developed using TensorFlow Lite and then compiled to run seamlessly on this accelerator, providing you with high-speed inferencing capabilities. One of the key benefits of the Edge TPU is its ability to deliver low-power ML inferencing without compromising on performance. This coprocessor is equipped with an Arm 32-bit Cortex-M0+ Microprocessor (MCU) with up to 32 MHz clock speed, ensuring outstanding speed and efficiency. In addition to its impressive performance, the Coral USB Accelerator also boasts a small footprint, making it a flexible and versatile solution for your embedded systems. It comes with a USB 3.1 (gen 1) port and cable, ensuring a SuperSpeed data transfer rate of up to 5Gb/s. The Coral USB Accelerator is fully compatible with Google Cloud and supports Debian Linux on host CPUs.
You can develop models using TensorFlow and take advantage of its compatibility with popular architectures like MobileNet and Inception. Furthermore, the device supports custom architectures, opening up endless possibilities for your ML projects. At Ubuy, we offer a range of e-commerce options for Raspberry Pi and other embedded single board computers, allowing you to conveniently shop for high-quality embedded computing products and components. Whether you are an AI enthusiast, a hobbyist, or a professional developer, our online store provides you with a seamless shopping experience for all your embedded system needs. Discover the future of embedded AI with the Google Coral USB Edge TPU ML Accelerator.
Shop now and unlock the potential of your embedded systems!.
Perguntas e Respostas dos Clientes
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pergunta:
What is the Edge TPU?
Resposta: The Edge TPU is a small ASIC designed and built by Google that provides high performance ML inferencing with a low power cost over a USB 3.0 interface. -
pergunta:
Which models does the Coral USB Accelerator support?
Resposta: It fully supports MobileNet and Inception architectures though custom architectures are possible. -
pergunta:
What is included in the package?
Resposta: The package includes the Coral USB Accelerator and a USB Type-C to Type-A cable.
Google Coral Single-Board Computers & Accessories Coral-USB-Accelerator Editorial Review
The Google Coral USB Edge TPU ML Accelerator coprocessor has received mixed feedback from users. While some have found it extremely easy to use and have seen significant improvements in performance, others have faced issues with the device failing or not being recognized initially. One user expressed frustration at the need to update drivers for compatibility. Nevertheless, those who got it up and running seamlessly praised its performance and the relief it brought to their CPU workload. Overall, when functioning correctly, the product has proven to be effective in accelerating machine learning inference tasks, such as object detection for CCTV systems on platforms like Raspberry Pi and Home Assistant. However, there are concerns about quality control and initial setup challenges for certain setups, which have impacted the user experience.
Avaliações e Classificações dos Clientes
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5 Estrela
100%
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4 Estrela
0%
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3 Estrela
0%
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2 Estrela
0%
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1 Estrela
0%
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Prós
- Significant performance improvement in machine learning inference tasks
- Effective in offloading AI detection burden from the CPU
- Compatible with platforms like Raspberry Pi, Home Assistant, and Frigate
Contras
- Initial setup challenges with recognition and compatibility on certain systems
Platform Trust & Buyer Confidence
“The product received very good packaging & safe…Thank You”
“Accurate delivery timing given”
“Not madly expensive like I thought, and much quicker than promised.”
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“The process was smooth, with clear communication and timelines. This was my 1st purchase and I am really impressed. I will definitely be coming back.”
Histórico de preços do produto
Informação importante
- Limitações: para produtos expedidos internacionalmente, tenha em atenção que qualquer garantia do fabricante pode não ser válida; opções de serviço do fabricante podem não estar disponíveis; manuais de produtos, instruções e avisos de segurança podem não estar nas línguas do país de destino; os produtos (e materiais que o acompanham) pode não ter sido concebido em conformidade com as normas, especificações e requisitos de rotulagem do país de destino; e os produtos podem não estar em conformidade com a voltagem e outras normas elétricas do país de destino (requerendo assim o uso de um adaptador ou conversor caso seja apropriado). O destinatário é responsável por garantir que o produto pode ser legalmente importado para o país de destino. Quando encomenda à Ubuy ou aos seus afiliados, o destinatário é o importador de registo e deve estar em conformidade com todas as leis e regulamentos do país de destino.
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MZN 9170
Encomende já e receba por volta de Quarta-feira, Julho 29
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QTY:
PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.
Recursos e benefícios
- Brings powerful ML inferencing capabilities to existing Linux systems
- Execute state-of-the-art mobile vision models in a power-efficient manner
- Great for fast ML inferencing to embedded AI devices in a privacy-preserving way
- Fully supports MobileNet and Inception architectures though custom architectures are possible
- Compatible with Google Cloud
- Features Google Edge TPU ML accelerator coprocessor, USB 3.0 Type-C socket, Debian Linux on host CPU and models built with TensorFlow
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