Here’s an open-source ready to use bootstrap project written in Node.js that lets you to quickly build a REST service to host your image processing and computer vision code in a cloud environment. Please welcome: cloudcv-bootstrap. I made this project aside of CloudCV to keep it simple but functionaly. It is self-contained Node.js project that helps you to get quick results on building and deploying your first server-based image processing service.
While working on CloudCV I encountered problems in node.js addon written in native code. For CloudCV I use node.js with C++ Addon to separate high-performance algorithms (C++) from high-level networking API which node provides. In this tutorial I’m going to reveal best practices on debugging C++ Addons for Node.js (0.12) using Visual Studio 2013. Continue reading if you want to read in details why this works. This article is valid for Node.
![NanCheck](logo.jpg) During development of CloudCV I came to the problem on converting v8::Arguments to native C++ data types in my Node.js native module. If you are new to C++ and Node.js, I suggest you to read how to write C++ modules for Node.js and connecting OpenCV and Node.js first. Mapping V8 data types to native C++ equivalents is trivial, but somewhat wordy. One should take the argument at given index, check whether it is defined, then check it’s type and finally cast to C++ type.
img.img-thumbnail.pull-left(src=“travis-logo.png”) p | In this post i will show you how i implemented continuous integration and testing in my a(href=“http://cloudcv.io") CloudCV | project. Healthy unit tests and easy and continuous integration workflow is a must in any project goes beyound “Hello, world” application. | Today software is a mixture of technologies of all kind. Therefore it can break literally everywhere. Each integration point is a place of risk. | The CloudCV has a C++ backend that is using OpenCV library, it’s front-end is written in Node.
| Hey everyone! I continue to play with clouds and today it’s time to reveal the CloudCV - a cloud-based image processing project. | Based on my previous posts i host a server in the Digital Ocean’s cloud. | I have to say, everything is working like a charm. | The cheapest 5$/month plan gives me whatever i may need for this project. | All the source-code is already sits on Github and you are more than welcome to study it.
Vacation time is over, and now i’m on my way from Tartu, Estonia where i participated in 48 km. inline speedskating marathon to Odessa. My bus have Wi-Fi onboard, so i decided to write a short success-story how i managed to build a C++ addon module for Node.js and run it on the real server inside the Cloud9 IDE. You may also want to check the first tutorial since this guid relies on it.
A long time ago i was playing with cloud-based image processing. The first reason why i didn’t shared a reciple how to compile OpenCV as native app for windows azure cloud was trycky build process. It was too complicated and this tutorial will become outdated very quickly. The second one - Azure hosting wants a lot of money. So i put my research in this area on hold for better times.