{"id":7914,"date":"2026-07-08T18:15:07","date_gmt":"2026-07-08T18:15:07","guid":{"rendered":"https:\/\/www.diyipcb.com\/?post_type=product&#038;p=7914"},"modified":"2026-09-27T15:12:43","modified_gmt":"2026-09-27T15:12:43","slug":"coral-usb-accelerator-with-google-edge-tpu-ml-accelerator-coprocessor-macos-windows-10-google-cloud","status":"publish","type":"product","link":"https:\/\/www.diyipcb.com\/ja\/product\/coral-usb-accelerator-with-google-edge-tpu-ml-accelerator-coprocessor-macos-windows-10-google-cloud\/","title":{"rendered":"Coral USB\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\uff08Google Edge TPU ML\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30b3\u30d7\u30ed\u30bb\u30c3\u30b5\u642d\u8f09\uff09macOS\u3001Windows 10\u3001Google Cloud"},"content":{"rendered":"<p>The Coral USB Accelerator adds an Edge TPU coprocessor to your system, enabling high-speed machine learning simply by connecting to a USB port.<\/p>\n<p>A USB accessory that brings machine learning capabilities to existing systems. Works with Raspberry Pi and other Linux systems.<\/p>\n<p>Performs high-speed ML inference: The integrated Edge TPU coprocessor is capable of performing 4 trillion operations per second (TOPS) and consumes 0.5 watts per TOPS (2 TOPS per watt). For example, it can run state-of-the-art mobile vision models like MobileNet V2 at 400 FPS in an energy-efficient manner.<\/p>\n<p>Works with Debian Linux: Connects to any Debian-based Linux system via the included USB 3.0 Type-C cable.<\/p>\n<p>Supports TensorFlow Lite: No need to build models from scratch. TensorFlow Lite models can be compiled to run on the Edge TPU.<\/p>\n<p>Supports AutoML Vision Edge: Easily build and deploy fast, high-precision custom image classification models for your device using AutoML Vision Edge.<\/p>\n<section class=\"module-customization\">\n<h3>\u88fd\u54c1\u306e\u30ab\u30b9\u30bf\u30de\u30a4\u30ba<\/h3>\n<p>\u5f53\u793e\u306f\u88fd\u54c1\u306e\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u30b5\u30fc\u30d3\u30b9\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002. <a href=\"https:\/\/www.diyipcb.com\/ja\/contact-us\/\">\u304a\u554f\u3044\u5408\u308f\u305b<\/a> \u304a\u5ba2\u69d8\u306e\u3054\u8981\u671b\u306b\u3064\u3044\u3066\u8a71\u3057\u5408\u3046\u305f\u3081\u3002.<\/p>\n<\/section>","protected":false},"excerpt":{"rendered":"<p>The Coral USB Accelerator adds an Edge TPU coprocessor to your system, enabling high-speed machine learning simply by connecting to a USB port. A USB accessory that brings machine learning capabilities to existing systems. Works with Raspberry Pi and other Linux systems. Performs high-speed ML inference: The integrated Edge TPU coprocessor is capable of performing 4 trillion operations per second (TOPS) and consumes 0.5 watts per TOPS (2 TOPS per watt). For example, it can run state-of-the-art mobile vision models like MobileNet V2 at 400 FPS in an energy-efficient manner. Works with Debian Linux: Connects to any Debian-based Linux system via the included USB 3.0 Type-C cable. Supports TensorFlow Lite:&#8230;<\/p>","protected":false},"featured_media":2240,"comment_status":"open","ping_status":"closed","template":"","meta":{"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":""},"product_brand":[],"product_cat":[2094,94,101],"product_tag":[],"class_list":["post-7914","product","type-product","status-publish","has-post-thumbnail","product_cat-equipments","product_cat-electronic-modules","product_cat-prototyping-expansion","first","instock","shipping-taxable","purchasable","product-type-simple","entry","content-bg","loop-entry"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/product\/7914","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/comments?post=7914"}],"version-history":[{"count":0,"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/product\/7914\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/media\/2240"}],"wp:attachment":[{"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/media?parent=7914"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/product_brand?post=7914"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/product_cat?post=7914"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/www.diyipcb.com\/ja\/wp-json\/wp\/v2\/product_tag?post=7914"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}