Does anyone have a line on an algorithm to place boxes in an organizational chart?
Any language is fine.
yFiles might be of interest. I've not used it, though I have some experience of yEd.
You can use Excel. I did that for a family tree once, which is similar to an org chart.
Related
I am searching a way to do the following charts with D3.js and as I'm new to this, I have no idea at the moment how to sort the squares.
Tried some research for charts like this:
Square chart
Proportional Aera Chart
but I did not find anything regarding D3.js.
Does anyone have an idea how to start or proceed?
I think I could manage to create an area with all squares in the right dimensions, but I do not know how to sort them dynamically, so they would group together automatically as shown especially in the first image, when their sizes do not match perfectly but differ a lot.
Thanx for any help, hirschferkel
This example from Mike Bostock is, I think, the sort of thing you're after:
https://bl.ocks.org/mbostock/8fe6fa6ed1fa976e5dd76cfa4d816fec
I suddenly came accross maybe a similar chart: It's called demers cartogram. There is a way to create it in d3.js but it does not look as good as Arc Gis creates it, where the alignment of squares looks much cleaner.
Demers Cartogram with d3.js
Demers Cartogram with ArcGis
First of all, thanks for reading my question. I'm beginner in computer vision.
I read a lot but I didn't find any solution.
I have an image and I want to detect logo/logos on it.
Also, I have a whole of images with different logos, all image containing a logo on it and nothing more.
Can you help me with any idea of how to detect logo/logos on an image when I have a whole (thousands) of training sets (known logos set)?
It can be done by using the SURF or SIFT feature detection algorithm for few known logos, by matching the given image with all of the others but I have a huge dataset, and I can't match with all other images.
To try all images in the dataset takes toooooo much time :)
Can be useful any SDK? (it can be even for mobile phones or for desktop also).
Or can I use some multiple algorithms for it?
I found an interesting paper about this question with a SIGMA algorithm, but I can't find any description for these algorithms (http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5495345).
I think to detect the features on the images is OK (SIFT, maybe SURF).
But I think the problem is with the big number of known images/logos.
I think it should be stored in a special way.
Ex. made a tree somehow from the thousand of known logos, or to separate them in groups.
Is it possible to do this task?
I appreciate any help.
The thousands of training sets is useful only to test your algorithm, it will not help to analyze a new image.
I made a bit of pattern recognition in the past, I would start this way: look for sharp edges (sharp color transitions too). So an edge filter and statistical analysis about features all located in the same corner. The result of the algorithm will be a number that you will use with your training set.
Since you are doing original reserch be prepared for a long work. If a SDK with a function "ImageHasLogo()" exists yet, you will find it on Google.
To simplify the problem, I have a graph that contains nodes and edges which are on a 2D plane.
What I want to be able to do is click a button and it make the automatically layout the graph to look clean. By that I mean minimal crossing of edges, nice space between nodes, maybe even represent the graph scale (weighted edges).
I know this is completely subjective of what is a clean looking graph, but does anyone know of an algorithm to start with, rather than reinventing the wheel?
Thanks.
You will find http://graphdrawing.org/ and this tutorial, by Roberto Tamassia, professor at Brown University, quite helpful.
I like a lot Force-Directed Techniques (pp. 66-72 in the tutorial) like the Spring Embedder.
You assume there is a spring or other force between any two adjacent nodes and let nature (simulation) do the work :)
I would suggest that you take a look at at graphviz. The dot program can take a specification of a graph and generate an image of the network for you somewhat "cleanly". I've linked to the "theory" page that gives you some links that might be relevant if you're interested in the theoretical background. The library and tools themselves are mature enough if you simply want a solution to a problem with layout that you're facing.
I would say as Noufal Ibrahim, but you could also look more precisely at the C API of the graphviz project. It includes a lib to build your graph (libgraph.pdf) with all the nodes and edges, and a lib to layout the graph (libgvc.pdf) (just compute each nodes position), so you can then display it in your own UI for example.
Also JGraph if you want the layouts in Java (I work on the project).
A good visual guide how the most popular layouts actually look: follow the link
I'm thinking of writing few blogs on arrays and linked list and for that I need some good drawing tool for drawing images to explain the concept and the logic. I don't want to copy/paste images from other source so if anyone among you knows about any such tool in which I can create images fast and similar to ones given in books and on other site, please let me know.
Graphviz can draw linked data structures by using special "record" node shapes. Here's one example which was automatically generated during a debug session.
I believe that Google Docs Draw, could satisfy your needs.
http://googlesystem.blogspot.com/2009/03/drawing-in-google-docs.html
I use Omni Graffle for the sort of task you are describing.
http://www.omnigroup.com/products/omnigraffle/
In the upcoming version of Photoshop there is a feature called Content-Aware fill.
This feature will fill a selection of an image based on the surrounding image - to the point it can generate bushes and clouds while being seamless with the surrounding image.
See http://www.youtube.com/watch?v=NH0aEp1oDOI for a preview of the Photoshop feature I'm talking about.
My question is:
How does this feature work algorithmically?
I am a co-author of the PatchMatch paper previously mentioned here, and I led the development of the original Content-Aware Fill feature in Photoshop, along with Ivan Cavero Belaunde and Eli Shechtman in the Creative Technologies Lab, and Jeff Chien on the Photoshop team.
Photoshop's Content-Aware Fill uses a highly optimized, multithreaded variation of the algorithm described in the PatchMatch paper, and an older method called "SpaceTime Video Completion." Both papers are cited on the following technology page for this feature:
http://www.adobe.com/technology/projects/content-aware-fill.html
You can find out more about us on the Adobe Research web pages.
I'm guessing that for the smaller holes they are grabbing similarly textured patches surrounding the area to fill it in. This is described in a paper entitled "PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing" by Connelly Barnes and others in SIGGRAPH 2009. For larger holes they can exploit a large database of pictures with similar global statistics or texture, as describe in "Scene Completion Using Millions of Photographs". If they somehow could fused the two together I think it should work like in the video.
There is very similar algorithm for GIMP for a quite long time. It is called resynthesizer and probably you should be able to find a source for it (maybe at the project site)
EDIT
There is also source available at the ubuntu repository
And here you can see processing the same images with GIMP: http://www.youtube.com/watch?v=0AoobQQBeVc&feature=related
Well, they are not going to tell for the obvious reasons. The general name for the technique is "inpainting", you can look this up.
Specifically, if you look at what Criminisi did while in Microsoft http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.67.9407 and what Todor Georgiev does now at Adobe http://www.tgeorgiev.net/Inpainting.html, you'll be able to make a very good guess. A 90% guess, I'd say, which should be good enough.
I work on a similar problem. From what i read they use "PatchMatch" or "non-parametric patch sampling" in general.
PatchMatch: A Randomized Correspondence Algorithm
for Structural Image Editing
As a guess (and that's all that it would be) I'd expect that it does some frequency analysis (some like a Fourier transform) of the image. By looking only at the image at the edge of the selection and ignoring the middle, it could then extrapolate back into the middle. If the designers choose the correct color plains and what not, they should be able to generate a texture that seamlessly blends into the image at the edges.
edit: looking at the last example in the video; if you look at the top of the original image on either edge you see that the selection line runs right down a "gap" in the clouds and that right in the middle there is a "bump". These are the kind of artifacts I'd expect to see if my guess is correct. (OTOH, I'd also expect to see them is it was using some kind of sudo-mirroring across the selection boundary.)
The general approach is either content-aware fill or seam-carving. Ariel Shamir's group is responsible for the seminal work here, which was presented in SIGGRAPH 2007. See:
http://www.faculty.idc.ac.il/arik/site/subject-seam-carve.asp
Edit: Please see answer from the co-author of Content-Aware fill. I will be deleting this soon.