Difference between revisions of "Template:Google Coral/Main contents"
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<div style="padding:2rem 1rem; margin:0; background-color:#004a9f;color:#ffffff;"> | <div style="padding:2rem 1rem; margin:0; background-color:#004a9f;color:#ffffff;"> | ||
<div> | <div> | ||
| − | <p style="font-size: 4em; margin-bottom:0">Welcome to RidgeRun's guide to Google | + | <p style="font-size: 4em; margin-bottom:0">Welcome to RidgeRun's guide to Coral from Google</p> |
| − | <p style="font-size: 1em; margin-top:0; margin-bottom:4rem"> | + | <p style="font-size: 1em; margin-top:0; margin-bottom:4rem">Coral is a complete toolkit from Google to build products with local AI.</p> |
</div> | </div> | ||
</div> | </div> | ||
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<td> | <td> | ||
| valign="center" style="text-align:center;" | | | valign="center" style="text-align:center;" | | ||
| − | [[File: | + | |
| − | | | + | <br> |
| − | [[File: | + | [[File:Coral logo med.png|500px|frameless|center|Coral Logo|link=]] |
| + | [[File:Google coral.jpg|500px|center|Coral from Google|link=]] | ||
| + | Image taken from: https://coral.ai/products/ | ||
| + | |||
</td> | </td> | ||
</tr> | </tr> | ||
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|- | |- | ||
| width="100%" valign="top" colspan="3" style="background-color: #004a9f; font-weight: bold; text-align: center; color:#ffffff"| | | width="100%" valign="top" colspan="3" style="background-color: #004a9f; font-weight: bold; text-align: center; color:#ffffff"| | ||
| − | Google | + | Coral from Google |
|- | |- | ||
| width="100%" valign="top" colspan="6"| | | width="100%" valign="top" colspan="6"| | ||
| − | + | ||
| − | + | The [https://coral.ai/ '''Coral Dev Board'''] is a board developed by Google, which is ideal for the development of applications that involves the use of machine learning techniques and needs an optimized inference process in some tiny hardware. The Coral board has the benefit of providing a high speed and low power machine learning inference, facilitates the prototyping of ML solutions on embedded devices and the operating system that runs on the board is a Linux-based known as [https://coral.googlesource.com/docs/+/refs/heads/master/GettingStarted.md Mendel] (Debian derivate). | |
| − | + | ||
| − | + | The Coral Dev Board has a cost of [https://coral.ai/products/dev-board $149.99], but for production purposes, there is also a '''System-on-Module (SoM)''' ready to be integrated into a custom PCB hardware at a cost of [https://coral.ai/products/som $114.99]. | |
| − | + | ||
| − | |||
RidgeRun knows how important documentation is for your project and | RidgeRun knows how important documentation is for your project and | ||
how a single source of information may decrease the time-to-market of your product. | how a single source of information may decrease the time-to-market of your product. | ||
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|- | |- | ||
| width="100%" valign="top" colspan="3" style="background-color: #004a9f; font-weight: bold; text-align: center; color:#ffffff"| | | width="100%" valign="top" colspan="3" style="background-color: #004a9f; font-weight: bold; text-align: center; color:#ffffff"| | ||
| − | RidgeRun | + | RidgeRun Support |
|- | |- | ||
| width="100%" valign="top" colspan="3"| | | width="100%" valign="top" colspan="3"| | ||
| − | RidgeRun provides support for embedded Linux development for | + | RidgeRun provides support for embedded Linux development for the Coral platform, specializing in the use of hardware accelerators in multimedia applications. RidgeRun's products take full advantage of the hardware that Coral exposes to perform transformations on the video streams achieving great performance on complex processes. |
| + | |||
| + | This page contains detailed guides and information on how to get started with the Coral from Google using its full capabilities. | ||
| + | |||
| + | * '''[[R2Inference]]:''' is an open-source project from RidgeRun that serves as an abstraction layer in C/C++ for a variety of machine learning frameworks. | ||
| + | * '''[[GstInference]]:''' is an open-source project from RidgeRun that provides a framework for integrating deep learning inference into GStreamer. | ||
| + | |||
| + | <html> | ||
| + | <style> | ||
| + | .column { | ||
| + | float: left; | ||
| + | width: 33%; | ||
| + | padding: 1px; | ||
| + | } | ||
| + | |||
| + | /* Clear floats after image containers */ | ||
| + | .row::after { | ||
| + | content: ""; | ||
| + | clear: both; | ||
| + | display: table; | ||
| + | } | ||
| + | </style> | ||
| + | <div class="row"> | ||
| + | <div class="column"> | ||
| + | <a href="https://developer.ridgerun.com/wiki/index.php?title=Coral_from_Google"> | ||
| + | <img src="https://developer.ridgerun.com/wiki/images/6/62/Works_with_coral_svg.svg" alt="Coral from Google" style="width:500px"> | ||
| + | </a> | ||
| + | </div> | ||
| + | <div class="column"> | ||
| + | <div class="row"> | ||
| + | <b>R2Inference</b> | ||
| + | </div> | ||
| + | <a href="https://developer.ridgerun.com/wiki/index.php?title=R2Inference"> | ||
| + | <img src="https://developer.ridgerun.com/wiki/images/4/43/R2Inference_Logo.svg" alt="R2Inference" style="width:300px"> | ||
| + | </a> | ||
| + | </div> | ||
| + | <div class="column"> | ||
| + | <div class="row"> | ||
| + | <b>GstInference</b> | ||
| + | </div> | ||
| + | <a href="https://developer.ridgerun.com/wiki/index.php?title=GstInference"> | ||
| + | <img src="https://developer.ridgerun.com/wiki/images/1/10/GstInference_Logo.svg" alt="GstInference" style="width:300px"> | ||
| + | </a> | ||
| + | </div> | ||
| + | </div> | ||
| + | </html> | ||
| − | |||
| − | To get up-to-speed with your | + | To get up-to-speed with your Coral, start by clicking below: |
| − | [[File:xavier_get_started_here.png|400px|frameless|center|link=Google | + | [[File:xavier_get_started_here.png|400px|frameless|center|link=Coral from Google/Introduction/Getting_Started]] |
<br> | <br> | ||
|- | |- | ||
| width="100%" valign="top" colspan="3" style="background-color: #004a9f; font-weight: bold; text-align: center; color:#ffffff"| | | width="100%" valign="top" colspan="3" style="background-color: #004a9f; font-weight: bold; text-align: center; color:#ffffff"| | ||
| − | <span style="font-size:120%"> | + | <span style="font-size:120%"></span> |
|- | |- | ||
| width="100%" valign="top" colspan="3"| | | width="100%" valign="top" colspan="3"| | ||
| − | <span style="color:DarkViolet;font-size:110%"> '''RidgeRun is an official | + | <span style="color:DarkViolet;font-size:110%"> '''RidgeRun is an official <u>Coral from Google</u> partner and we have created this set of documentation to support our joint customers. If you have any questions on the content, please contact us through our [https://www.ridgerun.com/contact <u>Contact Us</u>] page.''' </span> |
{{ContactUs}} | {{ContactUs}} | ||
|} | |} | ||
Latest revision as of 14:19, 28 August 2023
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Welcome to RidgeRun's guide to Coral from Google Coral is a complete toolkit from Google to build products with local AI. |
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Coral from Google | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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The Coral Dev Board is a board developed by Google, which is ideal for the development of applications that involves the use of machine learning techniques and needs an optimized inference process in some tiny hardware. The Coral board has the benefit of providing a high speed and low power machine learning inference, facilitates the prototyping of ML solutions on embedded devices and the operating system that runs on the board is a Linux-based known as Mendel (Debian derivate). The Coral Dev Board has a cost of $149.99, but for production purposes, there is also a System-on-Module (SoM) ready to be integrated into a custom PCB hardware at a cost of $114.99. RidgeRun knows how important documentation is for your project and
how a single source of information may decrease the time-to-market of your product.
That's why we've decided to share our expertise with the developer community,
creating a centralized wiki with technical documentation, tutorials, examples and much more!
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RidgeRun Support | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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RidgeRun provides support for embedded Linux development for the Coral platform, specializing in the use of hardware accelerators in multimedia applications. RidgeRun's products take full advantage of the hardware that Coral exposes to perform transformations on the video streams achieving great performance on complex processes. This page contains detailed guides and information on how to get started with the Coral from Google using its full capabilities.
R2Inference
GstInference
Error creating thumbnail: Unable to save thumbnail to destination
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RidgeRun is an official Coral from Google partner and we have created this set of documentation to support our joint customers. If you have any questions on the content, please contact us through our Contact Us page.
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