Image recognition and object detection has been around for some years. However, usage and adoption was limited due to quality and ease of development.
With the release of Microsoft’s Project Oxford, and Google’s Vision API, the accessibility and applicability has massively improved.
Both APIs use REST API access and provide an excellent opportunity for the average developer...
Getting users feedback is always a pleasant moment. In most cases in World of Open Source we are creating tools and applications for people and we love to hear that someone thinks our (generally pet) project is useful. Mostly this moment is nicer than any paycheck.
But how author can enable easy contact with him as the...
Continuing in the series of shiny module design patterns, this post covers how to pass all the inputs from one module to another. TL;DR Return input from within the server call. Store the callModule() result in a variable. Pass the variable into arguments for other modules. Access the variable like you would input. Steal the
My current Shiny project contains at least five tables and I constantly forget how they are called. So I whipped up a little bookmarklet that uses jQuery to show the id of each div and input. Some of those can be ignored as they are internal names set ...
Introduction In just a few weeks the Eurovision 2016 song contest will be held again. There are 43 participants, two semi-finals on the 10th and 12th of May and a final on the 14th of May. It’s going to be a … Continue reading →
Following on from looking at the shiny modules design pattern of passing an input value to many modules, I’m now going to look at a more complex shiny module design pattern: passing an input from one module to another. TL;DR Return the input in a reactive expression from within the server call. Store the callModule()
I have an unnatural obsession with 4-dimensional networks. It might have started with a dream, but VR might make it a reality one day. For now I will settle for 3D networks in Plotly. Presentation: R users group (more) More: networkly
This post is the third in a series that make up my entry in Ari Lamstein’s R Election Analysis Contest.
First I introduced the nzelect R package from a user perspective. Second was a piece on how the build of that package works. Today, the third in the series introduces an interactive map of...
For the awesome Shiny Developers Conference back in January, I endeavoured to learn about shiny modules and overhaul an application using them in the space of two days. I succeeded and almost immediately switched onto other projects, thereby losing most of the hard-won knowledge! As I rediscover shiny modules and start putting them into more