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- USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
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Numéro d'article:
62198572
USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
Numéro d'article:
62198572
XOF 95896
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Coral USB Accelerator provides high performance ML inferencing with a low power cost over a USB 3.0 interface.
Livraison
rapide
Retour
gratuit*
Emballage sécurisé
Produits 100 % originaux
Conformité PCI DSS
Certifié ISO 27001
Ce qui se démarque
Fast Inference
Achieves high-speed machine learning inferencing with low power consumption, making it ideal for edge computing applications without sacrificing performance.
Easy Integration
Designed for seamless integration with Raspberry Pi and other single-board computers, simplifying setup for developers and hobbyists alike.
Versatile Applications
Supports a wide range of machine learning models, empowering users to create solutions in various fields like IoT, robotics, and smart devices.
Détails du produit
- Featuring the Edge TPU, designed and built by Google
- Provides high performance ML inferencing with low power cost over a USB 3.0 interface
- Executes state-of-the-art mobile vision models at over 100 fps in a power-efficient manner
- Allows fast ML inferencing to embedded AI devices in a power-efficient and privacy-preserving way
- Models developed in TensorFlow Lite and then compiled to run on the USB Accelerator
- Key benefits: High speed TensorFlow Lite inferencing, low power, small footprint
| 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 |
À qui est-ce destiné ?
-
AI Developers
Ideal for developers creating machine learning applications requiring fast inference on edge devices and single board computers.
-
Embedded System Hobbyists
Perfect for hobbyists wanting to add AI capabilities to their Raspberry Pi and other embedded systems projects.
-
Robotics Engineers
Useful for robotics engineers needing real-time object detection and classification with minimal latency in applications.
-
General Users
Not suitable for casual users lacking programming skills or AI knowledge to leverage advanced machine learning capabilities.
DESCRIPTION DU PRODUIT
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!.
Vous avez une question ? Chattez avec nous
Questions et réponses des clients
-
question:
What is the Edge TPU?
répondre: 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. -
question:
Which models does the Coral USB Accelerator support?
répondre: It fully supports MobileNet and Inception architectures though custom architectures are possible. -
question:
What is included in the package?
répondre: 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.
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Avantages
- 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
Les inconvénients
- Initial setup challenges with recognition and compatibility on certain systems
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XOF 95896
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Conforme PCI DSS et certifié ISO 27001:2022, avec des paiements chiffrés et une protection complète de l'acheteur pour chaque commande.
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Livraison transfrontalière la plus rapide
Caractéristiques et avantages
- 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
Assurance Ubuy
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