I didn't see any documentation for shading patterns, only solid fill color for Graphviz. Does anybody know how to do it, or is it not possible?
Like the pattern fill here. https://www.ablebits.com/office-addins-blog/2012/03/28/excel-charts-tips/
The closest thing to what you want is probably gradients.
In Graphviz's Node, Edge and Graph Attributes page, it supports gradients when specifying color lists.
You can use them referring to these examples.
Another alternative which would be a bigger hassle is use the shapefile attribute and build a shapefile per pattern although this feature is deprecated.
A third option would be if you are outputting in SVG format, is to do some post processing on the generated SVG to apply texture patterns on the nodes.
Related
I'm trying to create a geochoropleth that maps subregions, but also includes outlines of larger regions. (You can think of it like mapping counties, but then wanting to include thicker outlines of states). Not all subregions are part of larger regions that need to be outlined. (Most aren't.) You can see an example of what I'm trying to replicate here:
What's the best way to add this regional outline to my map? I've tried keeping the regions and subregions as two separate files, with two overlaygeojsons calls in my geochoropleth call (with added d3 styling to change the fill and stroke to just be an outline). But when I do - the projection of the regional outline layer is strangely offset from the lower one.
I've also considered having both sets of boundaries in just the one geojson. However, I wasn't sure how to work with this.
While it would be nice to be able to mouseover the boundaries of the larger regions and get a tooltip before crossing over into the individual subregions and getting their tooltips, this isn't a must. I could live with just outlines around the regions. Please advise on the best way to do this. Happy to provide more detail, and thanks so much!
EDIT: I discovered that I had a misplaced transform tag which is what offset the second layer. Fixed now!
My graphs currently indicate "no data" by calculating the holes in my datasets, then generating a new fake dataset that ranges from nil to max(all-y-values), thus making it look like a full-height background. I make it an "area" dataset and apply an SVG pattern to make it look like this:
The problem arises when the y-axis scale is greater than the data, in other words when max(all-y-values) doesn't coincide with the top of the graph.
I need to make these shaded background intervals always the full height of the graph, and I'm willing to rethink the whole process of adding them.
My recent attempts have been trying to follow the "filling an area above the line" example described in D3 Tips and Tricks as well as the NVD3 documentation and various other resources, but I haven't seen anything working.
This is the "filling an area above the line" example from that link:
Any solution must either use ClojureScript and Om or at least be directly compatible with them, since I already have a proof of concept in the above links and I am looking for more.
I have a target image to be searched for a curve along its edges and a template image that contains the curve. What I need to achieve is to find the best match of the curve in the template image within the target image, and based on the score, to find out whether there is a match or not. That also includes rotation and resizing of the curve. The target image can be the output of a Canny Edge detector if that makes things easier.
I am considering to use OpenCV (by using Python or Processing/Java or if those have limited access to the required functions then by using C) to make things practical and efficient, however could not find out if I can use any functions (or a combination of them) in OpenCV that are useable for doing this job. I have been reading through the OpenCV documentation and thought at first that Contours could do this job, however all the examples show closed shapes as opposed to my case where I need to match a open curve to a part of an edge.
So is there a way to do this either by using OpenCV or with any known code or algorithm that you would suggest?
Here are some images to illustrate the problem:
My first thought was Generalized Hough Transform. However I don't know any good implementation for that.
I would try SIFT or SURF first on the canny edge image. It usually is used to find 2d areas, not 1d contours, but if you take the minimum bounding box around your contour and use that as the search pattern, it should work.
OpenCV has an implementation for that:
Features2D + Homography to find a known object
A problem may be getting a good edge image, those black shapes in the back could be distracting.
Also see this Stackoverflow answer:
Image Processing: Algorithm Improvement for 'Coca-Cola Can' Recognition
i'm just curious if someone knows how to analyse an image. for example:
i have a heatmap picture, know i want to extract the color value and the x,y coordiantes and redraw the image with javascript & canvas.
Another example would be to recognize pattern in the image (lines, arrows) and extract the direction and length.
A popular image/video analysis library I would recommend is OpenCV. I have used this github fork of the ruby-opencv gem with success. If you scroll down on the readme file, you'll see an example on face detection. The unit tests demonstrate how to do other things like drawing shapes and such. At a glance, I don't see any tests on extracting pixel data, but it most definitely is possible.
If you need something more simple, you can try out devil. It's more user-friendly and is focused on image manipulation, but you can probably extract pixel data with it.
It sounds like you'll be leaning towards OpenCV. It might be useful to look at this previous question, specifically the mention of the Hough transform
With my new assignment I am looking for a method to detect the presence of text on image. The image is a map - can be for example google map. The task is to detect where the street/city label is placed.
I know that opencv library has algorithm that can detect features (for example human faces) - haar classifier or hog (histogram of oriented gradients), but I heard that learning process of such algorithms is quite difficult.
Do you know of any algorithm, method or a library that could do that (detect presence of text on image)?
Thanks,
John
There is a standard problem in vision called text detection in images. it is quite different to OCR. OCR concerms itself with what it says, while text detection is about determining if there is text in the image. Adi Shavit's third link is a method to address this problem. You can look on google scholar well cited articles on text detection.
There are several possible approaches you can take.
Use OCR. A search for OCR on Stackoverflow will show many options. These include Tesseract and Ocropus.
If your text uses very specific fixed font, you may get away with simple template matching.
In the more general case you might want to take a look at "Detecting Text in Natural Scenes with Stroke Width Transform"
UPDATE Jan. 2017
The OpenCV 3.2 contrib module now has a text detection module.
It also includes a sample (C++, Python) of how to use it.
You need to tune this to a specific type of map images, or the problem is going to be very difficult (see the previous post about links to articles).
OCR is the way to go, and you should use an existing library. However, OCR is mainly done on text on white backgrounds. To reduce your problem to a regular OCR problem, you should attempt to work on the color space of the map. Likely the map text has a very specific color and this may be enough to find these pixels. You can then filter the detected pixels based on the size of connected regions.
If you literally only want to find the locations of text labels, you can do the above, and pretty much just skip the OCR step. If the labels are not too close, simple clustering algorithms can be used to find their respective positions.