I am writing an application in Perl, but I don't necessarily need code, just an algorithm I can Implement.
I want to represent space allocation of a database system as a number of rectangles packed into one large rectangle (size to fill the monitor). So I know the total area I have to work with, how many pieces I want to divide it into and how big each of those pieces should be.
What I need is a way to lay the individual rectangles out on the big window, correctly sized so they cover the correct area, and packed to cover the entire big window.
This is somewhat reminiscent of bin packing, but differs because I know the area I want each piece to be but I can choose the dimensions (as long as they give the correct area) to fit into the big window.
I hope this is clear enough and I hope someone has run into this before.
Thanks.
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If you have a file which include objects for example for EE like transistors, resistors etc and if you group them into one and then from the corner drag it to zoom in a bigger figure.
How can I make sure that these components are not zoom in only wiring changes?
The problem is that I have like 30 images with different sizes and I'm placing them in a table with many images side by side. However, if I keep the same scale then some images looks small compared to other. So I tried to scale them to get the same size. However, this make the components's sizes are also scaled up with different scale factors.
Here is an example of circuit using the bult-in shapes in Visio. As you can see the components'sizes got bigger when I scaled up the object. This is usually desired. However, in my specific case I want to keep the component's size same.
Here is the Visio file or I think you can also use any available components in Visio.
https://file.io/VRUCR8yVgYxs
I have a set of roughly 2000 images to process, and have stumbled on a problem regarding my edges. The original images are CT Scans of a heart, which are then thresholded and sobel filtered to produce a binary image of parts of the tissue. Unfortunately the thresholding and filtering has resulted in certain images missing the 'edges' of the heart --> R&LHS you can see the gaps & further down Just a small one at the top hopefully this shows how annoying this is to do automatically
I've tried various inbuilt methods of edge detection, but the difference in size of the gaps makes it nearly impossible to do, without filling out the bits that are supposed to remain as gaps due to the sizes of the filters I use.
Is there a way of manually "connecting the dots" so to speak? It would take forever on the whole image set but seems to be my only option, or if you could suggest any other way of doing it would be cool!
I have scanned copies of currency notes from which I need to extract only the rectangular notes.
Although the scanned copies have a very blank background, the note itself can be rotated or aligned correctly. I'm using matlab.
Example input:
Example output:
I have tried using thresholding and canny/sobel edge detection to no avail.
I also tried the solution given here but it detects the entire image for cropping and it would not work for rotated images.
PS: My primary objective is to determine the denomination of the currency. There are a couple of methods I thought I could use:
Color based, since all currency notes have varying primary colors.
The advantage of this method is that it's independent of the
rotation or scale of the input image.
Detect the small black triangle on the lower left corner of the note. This shape is unique
for each denomination.
Calculating the difference between 2 images. Since this is a small project, all input images will be of the same dpi and resolution and hence, once aligned, the difference between the input and the true images can give a rough estimate.
Which method do you think is the most viable?
It seems you are further advanced than you looked (seeing you comments) which is good! Im going to show you more or less the way you can go to solve you problem, however im not posting the whole code, just the important parts.
You have an image quite cropped and segmented. First you need to ensure that your image is without holes. So fill them!
Iinv=I==0; % you want 1 in money, 0 in not-money;
Ifill=imfill(Iinv,8,'holes'); % Fill holes
After that, you want to get only the boundary of the image:
Iedge=edge(Ifill);
And in the end you want to get the corners of that square:
C=corner(Iedge);
Now that you have 4 corners, you should be able to know the angle of this rotated "square". Once you get it do:
Irotate=imrotate(Icroped,angle);
Once here you may want to crop it again to end up just with the money! (aaah money always as an objective!)
Hope this helps!
I saw many Q&A here about squeezing space out of Matlab figures. However I want to squeeze space resulted from a possibly fixed aspect, i.e. to choose proper paper size for figure printing when aspect is fixed.
Quite often I work with DEM/map/image thus I use axis image. Now if I want to produce a high resolution image I do something like
set(gcf,'PaperUnits','inches','PaperPosition',[0 0 4 3])
print('-dpng','-r300','somefile.png')
as described in Matlab KB.
The problem here is to determine a proper aspect such that I can specify proper paper size that would leave no white/background stripes on either sides.
Apparently if I have a map (let's say 1000x2000 cells) with aspect ratio of 0.5, and I'm printing it on 4"x3" paper, I'll get background stripes on the sides. This is quite annoying as I'd prefer 1.5"x3" paper + axes & labels or so. Right now I have to manually adjust paper size.
This is inconvenient as I'd like a universal solution. For instance I may print a plot into file that I expect to occupy 4"x3" as well that has no fixed aspect. Or I may want to print a 3D figure. I'm aware of daspect and pbaspect, but how can I know how it is currently drawn?
Perhaps I can derive current 2D aspect from get(gca,'Position') and then scale it to my maximum allowed desired size (e.g., 4"x3") while respecting whether DataAspectRatioMode (?) property is set to manual. Is it the way to proceed or is there a better way?
I am not exactly sure if I understand your problem exactly, but I have used the following commands to create pdf images that are sized exactly to the size of the figure. I have used this for both 2D and 3D figures. The "handle" variable is simply your figure handle.
set(handle,'Units','inches');
set(handle,'PaperUnits','Inches','PaperPositionMode','auto');
P = get(handle,'Position');
set(handle,'PaperSize', [P(3),P(4)]);
I'm trying to lay out images in a grid, with a few featured ones being 4x as big.
I'm sure it's a well known layout algorithm, but i don't know what it is called.
The effect I'm looking for is similar to the screenshot shown below. Can anyone point me in the right direction?
UPDATED
To be more specific, lets limit it to the case of there being only the two sizes shown in the example. There can be an infinite number of items, with a set margin between them. Hope that clarifies things.
There is a well-known layout algorithm called treemapping, which is perhaps a bit too generic for your specific problem with some images being 4x as big, but could still be applicable particularly if you decide you want to have arbitrary sizes.
There are several different rectangular treemap algorithms, any of which could be used to visualise photos. Here is a nice example, which uses the strip algorithm to lay out photos with each size proportional to the rating of the photo.
This problem can be solved with a heatmap or a treemap. Heatmaps often use space-filling-curves. A heatmap reduces the 2d complexity to a 1d complexity. A heatmap looks like a quadtree. You want to look for Nick's hilbert curve quadtree spatial index blog.