Given a sprite sheet with a plain background like this:
I want to take each individual image off this background and create a file for it. I've looked around and had trouble finding information on how to do this - I cant help but feel there is some simple method. Does anyone have any pointers?
Caveat: Not all sprite sheets are the same format/layout, e.g. this one:
It's laid out slightly differently, and this one is even weirder.
So some challenges:
The background of the sprite sheet varies in colour.
Sprites in the sprite sheet vary in size, and that size cannot be specified ahead of time.
Method must generalize (reasonably well) to thousands of sprite sheets.
Appreciate any help.
Taken from: https://www.reddit.com/r/computervision/comments/ej3wgr/extracting_images_from_a_simpleplain_background/
by /u/tzatza
1) detect background color (sample appropriately, say from image edges), one option is with votes in a hashtable (key = r+"-"+g+"-"+b)
2) setup a mask, set all the background pixels to zero in mask within certain color distance of background, set all other mask pixels to 1.
3) optionally: erode the mask once (or twice), then dilate back to remove useless lines.
4) you now have a mask of 0 vs 1, do flood fill on each grouping of 1s to determine the extent of each sprite. Set mask pixels to "2" as you do the flood fill to indicate visited.
5) as you flood fill, track each sprite's min/max x/y and at the end of the flood fill, you have the extents (and a mask) which can be used to crop/store.
I know this goes against Stackoverlow principles of putting in the entire answer, but may I suggest you search for the "Blue Screen Matting" paper by Alvy Ray Smith & Jim Blinn. There's a copy available here.
They have been in the graphics industry for decades and so "know their stuff".
Related
I have a 2d grid where pixel centers are at the intersection of two half-grid lines, as shown below.
I also have a shape that is drawn on this grid. In my case the shape is a glyph, and is described by segments. Each segment has a start point, end point and a number of off-curve points. These segments can be quadratic curves or lines. What's important is that I can know the points and functions that make up the outline of the shape.
The rule for deciding which pixels should be turned on is simple: if the center of the pixel falls within the shape outline, turn that pixel on. The following image shows an example of applying this rule.
Now the problem I'm facing has to do with anti aliasing. What I'd like to do is to calculate what percentage of the area of a given pixel falls within the outline. As an example, in the image above, I've drawn a red square around a pixel that would be about 15% inside the shape.
The purpose of this would be so that I can then turn that pixel on only by 15% and thus get some cleaner edges for the final raster image.
While I was able to find algorithms for determining if a given point falls within a polygon (ray casting), I wasn't able to find anything about this type of problem.
Can someone can point me toward some algorithms to achieve this? Also let me know if I'm going about this problem in the wrong way!
This sounds like an X, Y problem.
You are asking for a way to calculate the perecentage of pixel coverage, but based on your question, it sounds that what you want to do is anti alias a polygon.
If you are working only with single color 2D shapes (i.e red, blue, magenta... squares, lines, curves...) A very simple solution is to create your image and blur the result afterwards.
This will automatically give you a smooth outline and is simple to implement in many languages.
In MS Excel, I applied conditional formatting to a cell A1 so that it's color changes from blue at value 0 and red at value 100. I copied that cell and pasted it as linked picture(I) specially.(Paste Special). The color of the rectangle picture now changes if value in original cell is changed. The problem is, the shape is only rectangular, it can be converted into square and diamond shape at best.If same rectangle can be transformed into different shapes(maybe by adding extra anchor on rectangle shape), a heat map can be created easily. Please share your insights about this thing if there is a way.
Following pictures may help understand the problem:
[Example][1]
If you want a heat map, please consider using a CHART not gazillions of picture objects, colored/placed/rotated/etc to ... mimic a chart.
First, google anything about "surface chart" in Excel, see how it looks in Excel, whatever. Just see it and think about it so you can compare it to your current approach.
You will observe some things, like:
it's 3D
it has just a few layers/colors
etc.
But really, all of them can be solved. Probably easier than your current approach.
you can easily turn off both axes and you can rotate it so the camera is totally straight top-down - then it looks flat as paper and noone can see it as 3D anymore
you can add more layers, you can set each of them to specific colors
etc.
Some resources:
multiple colors in surface chart
how to change rotation of 3d chart
geesh, I just found even a whole article/tutorial dedicated to creating heat map charts.
Please, read that last link and I'm pretty sure you will want to use that approach instead of doing picture puzzles.
I have an image and I am picking colors by RGB (data sampling). I select N points from a specific region in the image which has the "same" color. By "same" I mean, that part of the image belongs to an object, (let's say a yellow object). Each picked point in the RGB case has three values [R,G,B]. For example: [120,150,225]. And the maximum and minimum for each field are 255 and 0 respectively.
Let's assume that I picked N points from the region of the object in the image. The points obviously have different RGB values but from the same family (a gradient of the specific color).
Question:
I want to find a range for each RGB field that when I apply a color filter on the image the pixels related to that specific object remain (to be considered as inliers). Is it correct to find the maximum and minimum from the sampled points and consider them as the filter range? For example if the max and min of the field R are 120 ,170 respectively, can it be used as a the range that should be kept.
In my opinion, the idea is not true. Because when choosing the max and min of a set of sampled data some points will be out of that range and also there will be some point on the object that doesn't fit in this range.
What is a better solution to include more points as inliers?
If anybody needs to see collected data samples, please let me know.
I am not sure I fully grasp what you are asking for, but in my opinion filtering in RGB is not the way to go. You should use a different color space than RGB if you want to compare pixels of similar color. RGB is good for representing colors on a screen, but you actually want to look at the hue, saturation and intensity (lightness, or luminance) for analysing visible similarities in colors.
For example, you should convert your pixels to HSI or HSL color space first, then compare the different parameters you get. At that point, it is more natural to compare the resulting hue in a hue range, saturation in a saturation range, and so on.
Go here for further information on how to convert to and from RGB.
What happens here is that you implicitly try to reinvent either color indexing or histogram back-projection. You call it color filter but it is better to focus on probabilities than on colors and color spaces. Colors of course not super reliable and change with lighting (though hue tends to stay the same given non-colored illumination) that's why some color spaces are better than others. You can handle this separately but it seems that you are more interested in the principles of calculating "filtering operation" that will do segmentation of the foreground object from background. Hopefully.
In short, a histogram back-projection works by first creating a histogram for R, G, B within object area and then back-projecting them into the image in the following way. For each pixel in the image find its bin in the histogram, calculate its relative weight (probability) given overall sum of the bins and put this probability into the image. In such a way each pixel would have probability that it belongs to the object. You can improve it by dividing with probability of background if you want to model background too.
The result will be messy but somewhat resemble an object segment plus some background noise. It has to be cleaned and then reconnected into object using separate methods such as connected components, grab cut, morphological operation, blur, etc.
I have more then 1 week reading about selective color change of an image. It meand selcting a color from a color picker and then select a part of image in which I want to change the color and apply the changing of color form original color to color of color picker.
E.g. if I select a blue color in color picker and I also select a red part in the image I should be able to change red color to blue color in all the image.
Another example. If I have an image with red apples and oranges and if I select an apple on the image and a blue color in the color picket, then all apples should be changing the color from red to blue.
I have some ideas but of course I need something more concrete on how to do this
Thank you for reading
As a starting point, consider clustering the colors of your image. If you don't know how many clusters you want, then you will need methods to determine whether to merge or not two given clusters. For the moment, let us suppose that we know that number. For example, given the following image at left, I mapped its colors to 3 clusters, which have the mean colors as shown in the middle, and representing each cluster by its mean color gives the figure at right.
With the output at right, now what you need is a method to replace colors. Suppose the user clicks (a single point) somewhere in your image, then you know the positions in the original image that you will need to modify. For the next image, the user (me) clicked on a point that is contained by the "orange" cluster. Then he clicked on some blue hue. From that, you make a mask representing the points in the "orange" cluster and play with that. I considered a simple gaussian filter followed by a flat dilation 3x5. Then you replace the hues in the original image according to the produced mask (after the low pass filtering, the values on it are also considered as a alpha value for compositing the images).
Not perfect at all, but you could have a better clustering than me and also a much-less-primitive color replacement method. I intentionally skipped the details about clustering method, color space, and others, because I used only basic k-means on RGB without any pre-processing of the input. So you can consider the results above as a baseline for anything else you can do.
Given the image, a selected color, and a target new color - you can't do much that isn't ugly. You also need a range, some amount of variation in color, so you can say one pixel's color is "close enough" while another is clearly "different".
First step of processing: You create a mask image, which is grayscale and varying from 0.0 to 1.0 (or from zero to some maximum value we'll treat as 1.0), and the same size as the input image. For each input pixel, test if its color is sufficiently near the selected color. If it's "the same" or "close enough" put 1.0 in the mask. If it's different, put 0.0. If is sorta borderline, put an in-between value. Exactly how to do this depends on the details of the image.
This might work best in LAB space, and testing for sameness according to the angle of the A,B coordinates relative to their origin.
Once you have the mask, put it aside. Now color-transform the whole image. This might be best done in HSV space. Don't touch the V channel. Add a constant to S, modulo 360deg (or mod 256, if S is stored as bytes) and multiply S by a constant chosen so that the coordinates in HSV corresponding to the selected color is moved to the HSV coordinates for the target color. Convert the transformed S and H, with the unchanged L, back to RGB.
Finally, use the mask to blend the original image with the color-transformed one. Apply this to each channel - red, green, blue:
output = (1-mask)*original + mask*transformed
If you're doing it all in byte arrays, 0 is 0.0 and 255 is 1.0, and be careful of overflow and signed/unsigned problems.
I want to fill some part of the shapes in actionscript, lets say "half of a circle", but unfortunately i could not find any suitable way to do it ?. Any suggestions will be appreciated thanks :)
one solution, in your case you have to draw some Close-region# square and rectangle triangle etc. in your Main region and then you can fill it whole part of the region which you draw. so if you want to fill a part of the region then you must draw a region on your main region then you can fill it so user have a feeling that he has filling a half region.
May This link'll be helpfull the ActionScript Drawing API & Drawing and Filling Partial Circles