If I want to draw a text on a control, I can get "a bounding rectangle" first and place it at an appropriate place (using GetTextExtentPoint32 function).
But I also need to know where some baselines are, e.g the two red lines in the picture.
(Their positions are calculated respect to the top of the bounding rectangle.)
I didn't figure a way to get these information. Please help.
The function GetTextMetrics will get you this. Select your font into the DC first, then call GetTextMetrics. The fields tmAscent and tmDescent of the TEXTMETRIC structure are probably the ones you need.
Related
I'm aware my question is maybe somewhat lazy. But I hope someone could maybe give me head start with my idea, or can provide me with an existing code example that points me in the right direction.
I want to create an organic shape/blob that more or less fills up existing space, but wraps around typographical elements. Whenever these elements move around, the shape should adjust itself accordingly. I was looking at Paper.js where examples like http://paperjs.org/examples/candy-crash/ and http://paperjs.org/examples/voronoi/ make it seem like this should be possible.
You can use the path.subtract() boolean operation, along with the path.smooth() function to smooth your shape with the type of smoothing of your choice.
Here is a demo sketch. You can also try to smooth the rectangles ; and maybe randomly add points on your curves or randomly displace all segment handles.
I have data from some experiment that should resemble a known grid-structure. However, the data
is off by some unknown angle
is distorted in an unknown way
may contain some displaced points
For an example, please have a look at this picture:
As you can see, the (nice looking) grid is distorted (the angle between the red indicators I drew is not 90deg) and is also rotated a little bit (the horizontal red line is not really horizontal). In addition, on rhe right top and bottom you can see some defects of the structure.
Are there tools I could use to match the data to some grid that I define and thereby find out the corrected data point positions? If not, could you give me some hints to appropriate algorithms to accomplish this? I have googled and thought for a while, but did not come up with a nice (and simple) solution.
in one of my projects, I would like to create heatmap of user clicks. I was searching a while and found this library - http://www.patrick-wied.at/static/heatmapjs/examples.html . That is basically exactly what I would like to make. I would like to create heatmap in SVG, if possible, that is only difference.
I would like to create my own heatmap and I'm just wondering how to do that. I have XY clicks position. Each click has mostly different XY position, but there can be exceptions time to time, a few clicks can have the came XY position.
I found a few solutions based on grid on website, where you have to check which clicks belong into the same column in this grid and according to these informations you are able to fill the most clicked columns with red or orange and so on. But it seems a little bit complicated to me and maybe slower for bigger grids.
So I'm wondering if there is another solution how to "calculate" heatmap colors or I would like to know the main idea used in library above.
Many thanks
To make this kind of heat map, you need some kind of writable array (or, as you put it, a "grid"). User clicks are added onto this array in a cumulative fashion, by adding a small "filter" sub-array (aligned around each click) to the writable array.
Unfortunately, this "grid" method seems to be the easiest, simplest way to get that kind of smooth, blobby appearance. Fortunately, this kind of operation is well-supported by software and hardware, under the name "computer graphics".
When considered as a computer graphics operation, the writable array is called an "accumulation buffer". The filter is what gives you the nice blobby appearance, even with a relatively small number of clicks -- you can tweak the size of the filter according to the needs of your application.
After accumulating the user clicks, you will need to convert from the raw accumulated values to some kind of visible color scale. This may involve looking through the entire accumulation buffer to find the largest value, and mapping your chosen color scale accordingly. Alternately, you could adjust your scale according to the number of mouse clicks, or (as in the demo you linked to) just choose a fixed scale regardless of the content of the buffer.
Finally, I should mention that SVG is not well-adapted to representing this kind of graphic. It should probably be saved as some kind of image file (.jpg or .png) instead.
I'm trying to create a matrix plot with mathematica. Using ArrayPlot[] I get a very nice figure, apart from the fact that it's surrounded by a white margin. I've got to the root of the problem, in the sense of the following example.
http://img689.imageshack.us/img689/8427/badmargin.png
If I try to export the resulting graphic, it exports the margin also. I want my array content to fill a rectangle of a certain size so that it can be superimposed on another image, but the ArrayPlot function produces margins that interfere.
What do?
QuickEdit: ImageCrop will not work in my case, because a) I want my resulting image to be of a certain size, and b) without specifying how wide margins I want to remove the automatic version may mess with my graph (first row may well be white, for example).
Try PlotRangePadding->0
Apparently my reply was too short, so I'm typing more.
If you set the option Background->None the edges should be transparent. This would work if you were embedding it in another graphic.
I'm searching for an certain object in my photograph:
Object: Outline of a rectangle with an X in the middle. It looks like a rectangular checkbox. That's all. So, no fill, just lines. The rectangle will have the same ratios of length to width but it could be any size or any rotation in the photograph.
I've looked a whole bunch of image recognition approaches. But I'm trying to determine the best for this specific task. Most importantly, the object is made of lines and is not a filled shape. Also, there is no perspective distortion, so the rectangular object will always have right angles in the photograph.
Any ideas? I'm hoping for something that I can implement fairly easily.
Thanks all.
You could try using a corner detector (e.g. Harris) to find the corners of the box, the ends and the intersection of the X. That simplifies the problem to finding points in the right configuration.
Edit (response to comment):
I'm assuming you can find the corner points in your image, the 4 corners of the rectangle, the 4 line endings of the X and the center of the X, plus a few other corners in the image due to noise or objects in the background. That simplifies the problem to finding a set of 9 points in the right configuration, out of a given set of points.
My first try would be to look at each corner point A. Then I'd iterate over the points B close to A. Now if I assume that (e.g.) A is the upper left corner of the rectangle and B is the lower right corner, I can easily calculate, where I would expect the other corner points to be in the image. I'd use some nearest-neighbor search (or a library like FLANN) to see if there are corners where I'd expect them. If I can find a set of points that matches these expected positions, I know where the symbol would be, if it is present in the image.
You have to try if that is good enough for your application. If you have too many false positives (sets of corners of other objects that accidentially form a rectangle + X), you could check if there are lines (i.e. high contrast in the right direction) where you would expect them. And you could check if there is low contrast where there are no lines in the pattern. This should be relatively straightforward once you know the points in the image that correspond to the corners/line endings in the object you're looking for.
I'd suggest the Generalized Hough Transform. It seems you have a fairly simple, fixed shape. The generalized Hough transform should be able to detect that shape at any rotation or scale in the image. You many need to threshold the original image, or pre-process it in some way for this method to be useful though.
You can use local features to identify the object in image. Feature detection wiki
For example, you can calculate features on some referent image which contains only the object you're looking for and save the results, let's say, to a plain text file. After that you can search for the object just by comparing newly calculated features (on images with some complex scenes containing the object) with the referent ones.
Here's some good resource on local features:
Local Invariant Feature Detectors: A Survey