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- USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
JPY 33804
Price Details
Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )
*All items will import from 英国
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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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100%本物
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この商品の利点
製品詳細
- 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
| RAM Memory Installed | 2 KB |
| Memory Storage Capacity | 16 KB |
| Processor Speed | 32 MHz |
| Network Connectivity Technology | USB |
| Operating System | Linux |
| Processor Brand | ARM |
| Compatible Devices | Raspberry Pi |
| Processor Count | 1 |
| Total USB Ports | 1 |
| Smart Home Compatibility | Not Smart Home Compatible |
| 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 |
| RAM memory installed size | 2 KB |
| CPU speed | 32 MHz |
どんな人にお勧めですか?
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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.
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Complex ML Tasks
Ineffective for heavy-duty machine learning tasks that require powerful processing capabilities beyond its edge TPU limitations.
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Budget-Conscious Buyers
May not appeal to users looking for cost-effective solutions, as the product could be considered relatively expensive.
製品説明書
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!.
顧客の質問と回答
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質問:
What is the Edge TPU?
答え: 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. -
質問:
Which models does the Coral USB Accelerator support?
答え: It fully supports MobileNet and Inception architectures though custom architectures are possible. -
質問:
What is included in the package?
答え: 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.
お客様のレビュー&評価
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5 星
59%
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4 星
16%
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3 星
8%
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2 星
6%
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1 星
11%
この商品のレビュー
お考えをお聞かせください
長所
- 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
短所
- 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.”
Product Price History
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JPY 33804
今すぐ注文すると 頃に届きます 土曜日, 7月 25
This item is not restrict in my country.(Please click on above link if this item is not restrict in your country, So our team will review and allow.)
QTY:
PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.
特徴と利点
- 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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