I have a rather large graph in DOT, which I render using neato
and I'm more or less able to distinguish its main clusters using a lot of len=... attributes.
I wanted to experiment with twopi, because I like a lot the way it renders, but I see that it doesnt support len.
There are alternatives? My need is to manually keep some portions of the graph rather isolated from others, to enhance readability. I tried with clusters but apparently the results are not so good.
With twopi, you specify a root then the number of edges away from root will dictate which ring of the circle it belongs on. Another alternative you might also consider is circo which is yet another graphing tool from graphviz.
Related
I have a dot graphviz file that geneates the following output:
http://www.qlands.com/other_files/test.png
However the output is organized vertically. If I setup the size to be for example 8.27 inches; How can I distribute the elements around a box of 8.27 x 8.27 inches?
Your graph is a directed graph layed out with dot from left to right, and the first rank contains many nodes which results in a very high image.
The main tool to break up graphs with this problem is unflatten:
unflatten is a preprocessor to dot that is used to improve the aspect
ratio of graphs having many leaves or disconnected nodes. The usual
layout for such a graph is generally very wide or tall. unflatten
inserts invisible edges or adjusts the minlen on edges to improve
layout compaction.
You may combine this with other tools and techniques to get the result you want:
Use the unflatten utility - please see this answer for a detailed example using unflatten.
Use invisible edges to introduce new ranks (basically what unflatten does automatically, but with human inspiration... example also here)
If you need the output to be of this exact size, be sure to understand graphviz's various attributes which have an impact on it, such as size, margin, ratio... (see also this and yet another answer providing details)
Finally, you could simply use a different layout (neato for example)
I'm looking for a way to render dependency graphs (puppet resource graphs to be exact) in a human readable way. And by 'readable' I mean easily readable without the need of having to setup a cinema screen just to be able to completely display the relevant part.
Here is such a graph I'm talking about.
If you render it via graphviz' dot -Tpng, it generates a about 16k x 3k pixel image which I absolutely cannot entirely display in any way that I could still read anything that's written there.
I'd like it to be more compact (less white space) and maybe different colors to help keeping track of the relationships more easily. Any hints on how to do that?
PS: The example graph actually is a quite simple one.
Perhaps you could use Gephi to filter the graph...
This post could help.
I have a lot of polygons. Ideally, all the polygons must not overlap one other, but they can be located adjacent to one another.
But practically, I would have to allow for slight polygon overlap ( defined by a certain tolerance) because all these polygons are obtained from user hand drawing input, which is not as machine-precised as I want them to be.
My question is, is there any software library components that:
Allows one to input a range of polygons
Check if the polygons are overlapped more than a prespecified tolerance
If yes, then stop, or else, continue
Create mesh in terms of coordinates and elements for the polygons by grouping common vertex and edges together?
More importantly, link back the mesh edges to the original polygon(s)'s edge?
Or is there anyone tackle this issue before?
This issue is a daily "bread" of GIS applications - this is what is exactly done there. We also learned that at a GIS course. Look into GIS systems how they address this issue. E.g. ArcGIS define so called topology rules and has some functions to check if the edited features are topologically correct. See http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=Topology_rules
This is pretty long, only because the question is so big. I've tried to group my comments based on your bullet points.
Components to draw polygons
My guess is that you'll have limited success without providing more information - a component to draw polygons will be very much coupled to the language and UI paradigm you are using for the rest of your project, ie. code for a web component will look very different to a native component.
Perhaps an alternative is to separate this element of the process out from the rest of what you're trying to do. There are some absolutely fantastic pre-existing editors that you can use to create 2d and 3d polygons.
Inkscape is an example of a vector graphics editor that makes it easy to enter 2d polygons, and has the advantage of producing output SVG, which is reasonably easy to parse.
In three dimensions Blender is an open source editor that can be used to produce arbitrary geometries that can be exported to a number of formats.
If you can use a google-maps API (possibly in an native HTML rendering control), and you are interested in adding spatial points on a map overlay, you may be interested in related click-to-draw polygon question on stackoverflow. From past experience, other map APIs like OpenLayers support similar approaches.
Check whether polygons are overlapped
Thomas T made the point in his answer, that there are families of related predicates that can be used to address this and related queries. If you are literally just looking for overlaps and other set theoretic operations (union, intersection, set difference) in two dimensions you can use the General Polygon Clipper
You may also need to consider the slightly more generic problem when two polygons that don't overlap or share a vertex when they should. You can use a Minkowski sum to dilate (enlarge) two and three dimensional polygons to avoid such problems. The Computational Geometry Algorithms Library has robust implementations of these algorithms.
I think that it's more likely that you are really looking for a piece of software that can perform vertex welding, Christer Ericson's book Real-time Collision Detection includes extensive and very readable description of the basics in this field, and also on related issues of edge snapping, crack detection, T-junctions and more. However, even though code snippets are included for that book, I know of no ready made library that addresses these problems, in particular, no complete implementation is given for anything beyond basic vertex welding.
Obviously all 3D packages (blender, maya, max, rhino) all include built in software and tools to solve this problem.
Group polygons based on vertices
From past experience, this turned out to be one of the most time consuming parts of developing software to solve problems in this area. It requires reasonable understanding of graph theory and algorithms to traverse boundaries. It is worth relying upon a solid geometry or graph library to do the heavy lifting for you. In the past I've had success with igraph.
Link the updated polygons back to the originals.
Again, from past experience, this is just a case of careful bookkeeping, and some very careful design of your mesh classes up-front. I'd like to give more advice, but even after spending a big chunk of the last six months on this, I'm still struggling to find a "nice" way to do this.
Other Comments
If you're interacting with users, I would strongly recommend avoiding this issue where possible by using an editor that "snaps", rounding all user entered points onto a grid. This will hopefully significantly reduce the amount of work that you have to do.
Yes, you can use OGR. It has python bindings. Specifically, the Geometry class has an Intersects method. I don't fully understand what you want in points 4 and 5.
I 'm trying to find an efficient way of acceptable complexity to
detect an object in an image so I can isolate it from its surroundings
segment that object to its sub-parts and label them so I can then fetch them at will
It's been 3 weeks since I entered the image processing world and I've read about so many algorithms (sift, snakes, more snakes, fourier-related, etc.), and heuristics that I don't know where to start and which one is "best" for what I'm trying to achieve. Having in mind that the image dataset in interest is a pretty large one, I don't even know if I should use some algorithm implemented in OpenCV or if I should implement one my own.
Summarize:
Which methodology should I focus on? Why?
Should I use OpenCV for that kind of stuff or is there some other 'better' alternative?
Thank you in advance.
EDIT -- More info regarding the datasets
Each dataset consists of 80K images of products sharing the same
concept e.g. t-shirts, watches, shoes
size
orientation (90% of them)
background (95% of them)
All pictures in each datasets look almost identical apart from the product itself, apparently. To make things a little more clear, let's consider only the 'watch dataset':
All the pictures in the set look almost exactly like this:
(again, apart form the watch itself). I want to extract the strap and the dial. The thing is that there are lots of different watch styles and therefore shapes. From what I've read so far, I think I need a template algorithm that allows bending and stretching so as to be able to match straps and dials of different styles.
Instead of creating three distinct templates (upper part of strap, lower part of strap, dial), it would be reasonable to create only one and segment it into 3 parts. That way, I would be confident enough that each part was detected with respect to each other as intended to e.g. the dial would not be detected below the lower part of the strap.
From all the algorithms/methodologies I've encountered, active shape|appearance model seem to be the most promising ones. Unfortunately, I haven't managed to find a descent implementation and I'm not confident enough that that's the best approach so as to go ahead and write one myself.
If anyone could point out what I should be really looking for (algorithm/heuristic/library/etc.), I would be more than grateful. If again you think my description was a bit vague, feel free to ask for a more detailed one.
From what you've said, here are a few things that pop up at first glance:
Simplest thing to do it binarize the image and do Connected Components using OpenCV or CvBlob library. For simple images with non-complex background this usually yeilds objects
HOwever, looking at your sample image, texture-based segmentation techniques may work better - the watch dial, the straps and the background are wisely variant in texture/roughness, and this could be an ideal way to separate them.
The roughness of a portion can be easily found by the Eigen transform (explained a bit on SO, check the link to the research paper provided there), then the Mean Shift filter can be applied on the output of the Eigen transform. This will give regions clearly separated according to texture. Both the pyramidal Mean Shift and finding eigenvalues by SVD are implemented in OpenCV, so unless you can optimize your own code its better (and easier) to use inbuilt functions (if present) as far as speed and efficiency is concerned.
I think I would turn the problem around. Instead of hunting for the dial, I would use a set of robust features from the watch to 'stitch' the target image onto a template. The first watch has a set of squares in the dial that are white, the second watch has a number of white circles. I would per type of watch:
Segment out the squares or circles in the dial. Segmentation steps can be tricky as they are usually both scale and light dependent
Estimate the centers or corners of the above found feature areas. These are the new feature points.
Use the Hungarian algorithm to match features between the template watch and the target watch. Alternatively, one can take the surroundings of each feature point in the original image and match these using cross correlation
Use matching features between the template and the target to estimate scaling, rotation and translation
Stitch the image
As the image is now in a known form, one can extract the regions simply via pre set coordinates
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