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Item #:
181267336
USB Edge TPU ML Accelerator processor for Raspberry Pi and Other Embedded Single Board Computers
Item #:
181267336
ZAR 2997
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*All items will import from JP
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Imported from Japan store
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Only 2 items left in stock.
Order now and get it around Thursday, July 16
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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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What Stands Out
High performance
Accelerates machine learning tasks with exceptional speed, enabling real-time inference on edge devices, significantly enhancing the capabilities of Raspberry Pi and other embedded systems.
Compact design
Designed for space-constrained applications, this small coprocessor integrates seamlessly with embedded single-board computers, maintaining a clean and efficient architecture.
Versatile compatibility
Compatible with various embedded platforms beyond Raspberry Pi, offering users the flexibility to implement machine learning across diverse projects and environments, maximizing investment potential.
Product Details
- 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 |
| Processor Speed | 32 MHz |
| Connectivity Technology | USB |
| Operating system | Linux |
| Processor Brand | ARM |
| RAM Memory Technology | LPDDR3 |
| Processor Count | 1 |
| Total Usb Ports | 1 |
| Brand | Google-Coral |
| UPC | 608614201389 |
| Model Number | Coral-USB-Accelerator |
| Mfr Part Number | Coral-USB-Accelerator |
| Manufacturer | Google Coral |
| CPU Speed | 32 MHz |
| Item Weight | 0.2 lbs (90 grams) |
Who Should Buy?
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AI Developers
Ideal for developers creating machine learning models and applications on Raspberry Pi and embedded systems.
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Hobbyist Projects
Perfect for hobbyists interested in integrating machine learning capabilities into their DIY electronics projects.
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Educational Use
Great for educators teaching AI concepts and hands-on machine learning in a classroom or workshop setting.
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Casual Users
Not suited for general users looking for simple plug-and-play solutions without a technical background.
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Non-embedded Applications
Inappropriate for users needing machine learning on standard PCs or laptops, where performance varies greatly.
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Limited resources
Unsuitable for users without technical expertise or resources to manage and develop ML applications effectively.
Product Description
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!.
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Is USB Edge TPU ML Accelerator processor for Raspberry Available to Shop Online in South Africa?
Answer: Yes, at Ubuy South Africa this product is available for you to shop at a reasonable price. The USB Edge TPU ML Accelerator processor for Raspberry is not available locally but you can trust us with our express shipping services. -
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Answer: The delivery time of your ordered product varies as per what you've ordered and the shipping method that you've chosen. The estimated delivery time is mentioned during the checkout process, so be carefree while shopping.
Google Coral Single Board Computers Coral-USB-Accelerator Editorial Review
The Google Coral USB Edge TPU ML Accelerator is garnering positive attention for its performance, particularly in applications such as CCTV processing and machine learning inference. Users have found it to be a valuable addition to their Raspberry Pi and other embedded systems, particularly when paired with software like the Frigate CCTV system. The device seamlessly integrates, enabling efficient offloading of image processing tasks; this prevents overwhelming the host computer and enhances reliability in person and car detection. Users have reported significant improvements in inference times, with one individual noting a reduction from 1-1.5 seconds down to under 20 milliseconds when using TensorFlow Lite with the Coral. This leap in performance is highlighted as "amazing," and suggests that the device's capabilities notably exceed those of even relatively powerful processors like the 8th gen i5 NUC. Despite its higher price point, many Consumers feel justified in their purchase because of the efficiency gains it provides in machine learning applications. However, there are some technical hiccups to Consider; several users have experienced issues with the device being intermittently detected on Linux systems, primarily due to cheap USB cables. Those who invested in a better quality cable found that their problems were resolved, indicating that users should ensure they have robust connections for optimal performance. Overall, the Google Coral USB Edge TPU ML Accelerator is praised for its unparalleled performance in specialized applications, making it a strong choice for those looking to enhance their machine learning capabilities on low-power devices. **
Customer Reviews & Ratings
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Pros
- Significant reduction in inference time for machine learning tasks
- Seamless integration with popular software like Frigate
- Efficient offloading of image processing from host devices
Cons
- Higher price point may deter some customers
Product Price History
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ZAR 2997
Order now and get it around Thursday, July 16
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:
Only 2 items left in stock.
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Features & Benefits
- 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 architects though custom architects 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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