I have an image:
How do I find areas of different intensity in an image? How do I find all the bright areas that differ to the original brightness, and contrary-wise, how to find the dark areas, originating from shadows in this case?
Human eye realises the change in brightness, but how would a program do that?
Find bright and dark spots in one picture:
There are multiple approaches to this. I am gonna suggest just a couple of them here.
You can find the mean of the RGB values of the image and use the lower 10% of the pixels which vary the most from the mean as darker pixels and the highest 10% of the pixels which vary the most from the mean as brighter pixels.
You can set a predefined threshold for a bright pixel, lets say RGB=[220,220,220] and dark pixel as RGB=[30,30,30] and iterate through the image and classify the pixels accordingly.
You can also look into dynamic thresholding for the second method and your approach to the problem can be optimised accordingly.
Find changes in bright and dark spots:
There are multiple ways to handle this as well. One approach can be the mean-value subtraction technique. The human eye responds to change with respect to the previous image which was perceived. The program needs to do the same where it needs to compare the changes to the previously captured frame(s). Look into temporal filtering to get a further idea about this..
Hope this helped
Related
I'm coming from a Direct3D 9 background, and recently switched my custom game engine over to Direct3D12. After some research, it looked like using one of the *_SRGB formats was the way to go, because it corrected the gamma level.
Immediately, I noticed that everything nearly doubled in brightness, which was unexpected. When correcting a curve, I would expect some values to be brighter and some to be darker, but everything just appears brighter. However, I just accepted it and moved on. But now I'm noticing some other strange issues, and I'm not sure what's going on. Maybe someone could help me understand what I'm missing?
When I draw a primitive with a color value in either HLSL or C++, such as color(128,128,128,255) or float4(0.5,0.5,0.5,1.0), the resulting color I see on the screen is actually RGB 188,188,188. Is this to be expected? I'm reading the values of these colors in Adobe Photoshop 2022, which is in SRGB mode. Should the values not match up if both applications are using SRGB?
128 to 188 is really strange, but 0.5 to 0.73 is even stranger. How do I manually construct a color that comes out the way I constructed it? For example, one might use 0.5 to scale by "half brightness", but 0.73 is definitely not half brightness. It's almost white.
If our textures are painted on a PC, such as in Substance Painter or Photoshop, what is the point of converting all of these colors? If the artist can see the same color space that will be used to render, why tell the display to show us something else?
Before I switched to sRGB, I modeled in Blender, and my textures always looked the same between Blender and my game engine. If I start using sRGB, I'm worried that will not be the case. How are artists making that work?
Images that I've seen that were gamma corrected are often brighter and washed out. And images that were not gamma correct are usually dark and rich. Does gamma correction cause some type of saturation loss in darker color?
I appreciate any guidance. I've done research on this topic, but most of the information goes on endlessly about linear color space. Linear is nice, because it makes math easier, but half of the stuff we deal with in a 3D app is non-linear. At this point, I'm not sure its worth it.
1&2: Gamma correction is designed to convert between light intensity as it exists in the real world, i.e. the amount of photons that hit a camera sensor, and how human beings perceive light. So if a light source is emitting 50% less photons, we see it as as around 74% of the light (individual curves may vary) so 128 should become 188.
3&4: The point of linear color is to allow us to process images in a space where an increase in the number of photons is linearly related to the increase in the intensity values. Then the linear colors are gamma corrected before presenting them to the user. When you work in those programs, you are looking at gamma corrected images.
Basically, people don't look at linear color spaces. They look wrong to us. They only exist to allow the computer to do some processing. If you have shaders that do work in linear color space, saving your images in a linear format so that they don't have to remove the gamma, do the processing, and then reapply the gamma can have performance benefits.
The problem may be that you are gamma correcting images that are already gamma corrected. If the images look right to you, they may be gamma corrected, if they look dark, with the lighter areas seemingly emphasized, they may be linear. If you are adding colors/images that look right to you, before gamma is applied, you will have to put the colors/images through inverse gamma correction.
How Applications Display/Convert Color Spaces: (Edit)
Photoshop interprets what the numbers in an image mean through the currently applied color space. It is possible to both "assign" a color space, which changes how photoshop interprets the numbers, and "convert" a color space, which changes the numbers so that they look the same (or as close as possible) when interpreted through the new color space.
This first image is in the sRGB color space. I've painted a gray dot with the values of (127,127,127).
In this second image I have converted the image to a linear color space. It looks almost the same, because photoshop always applies gamma correction so that it looks right to you, but the first dot now has the value (54,54,54). I've added a second dot with the values (127,127,127) in this color space.
In this third image, I have assigned the sRGB color space. Now photoshop thinks the numbers are in the sRGB color space, so it thinks the image already has gamma correction, and is showing us something like the way linear color space looks.
For the final image, I did everything the opposite direction, drawing a dot with a value of (127,127,127), then converting back. The last dot now has a value of (187,187,187)
I want to detect that the sprite has encountered a color in pygame, which function should I use to achieve this function.
Though it is possible to get the color at any point in the surface that you want to check against using get_at() (docs here). You would need to find the new area that your sprite covered that it did not cover last time and check every pixel in that, and if other things were moving around you would have to check if your sprite now overlapped with any of those area and check that. Or you could decide that was too complicated and just run through every pixel under your sprites location (without you sprite drawn yet) and check for that color.
It is possible, but would likely not be very fast.
An alternative is if you know where those colors are you can mark those areas using rects, circles, sprites or masks (see here and here) that you can check against. That is usually much faster. These do not have to be drawn and so would be invisible. They would just be used to mark areas for the collision check.
If you do not know exactly where the colors are in the background or the other images, you can create masks based on the colors in them using pygame.mask.from_surface() or pygame.mask.from_threshold() (docs here and here).
Anyone who frequently does UI likely knows that for a given color hsl(H, 100%, 50%) (syntax is CSS) not all values of H will produce a color suitable to be placed under arbitrarily black or white text. The specific fact I'm noting is that certain colors (green) appear especially bright and other (blue) appear especially dark.
Well suppose I would like a user to be able to enter a color hue and have the color always appear with a consistent brightness so that one of either white or black text is guaranteed to always be readable on top of it. I would like all colors to also maintain the most vivid level of saturation they can given the constraint on brightness.
Here is a quick example of what I've tried so far. I start with a grid of squared like this rendered using a bunch of html div elements. Essentially these are hue values roughly from 0 to 360 along the horizontal axis and lightness values from roughly 0% to 100% along the vertical axis. All saturation value are set to 100%.
Using a JS library library called chroma.js, I now process all colors using the color.luminance function, whose definition seems to be to do what I'm looking for. I just passed the lightness of the hsl value in as the parameter to the function. I don't know for sure that this is the best way to accomplish my goal though since I'm not familiar with all the terminology at play here. Please note that my choice to use this library is by no means a constraint on how I want to go about this. It just represents my attempt at solving the problem.
The colors certainly now have a more consistent lightness, but the spectrum now seems particularly vivid around the orange to cyan area and particularly dull everywhere else. Also the colors seems to drop very quickly away from black at the top.
Hopefully this example helps a bit to express what I'm trying to accomplish here. Does any know what they best way to go about this is?
I found the solution! Check out HSLuv. It balances out all the hues in the spectrum so that at any given saturation and lightness, all hues will have the exact same perceived brightness to the human eye.
This solved my problem because now I can just set my text color to white (for example) and then as long as the text is readable against a certain HSLuv lightness it is guaranteed that it will be readable against any hue and saturation used in combination with that lightness. Magic.
I need to write some code (for a web.py webapp with a straight-HTML/JS client) that will generate a visual representation of a set of point-values. Each point has an X and Y coordinate, and the value is an integer. If I can use SVG to do this, then I can scale the image client-side with no extra code. Can I actually do this? I am concerned about a couple of things:
The points don't necessarily have any relation to each other. They aren't necessarily in a grid, nor can we say how many points are nearby, etc.
Gradients are primarily one-direction, and multiple gradients on the same shape seems to be a foreign concept.
Fills require an existing image, at which point, I'd be better off generating the entire image server-side anyway.
Objects always have a layering, even if it isn't specified, which can change how the image is rendered.
If it helps, consider a situation where we have a point surrounded by 5 others, where one of them is a bit closer than the others (exact distances and sizes can be adjusted). All six of the points have different colors (Red, Green, Blue, Cyan, Magenta, Yellow, with red in the center and Yellow being slightly closer), and the outer five points are arranged roughly in a pentagon. Note that this situation is not the only option, just a theoretically possible situation.
Can I do this with SVG, or should I render an image server-side?
EDIT: The main difficulty isn't in drawing the points, it is in filling the space between the points so that there is no whitespace, and color transitions aren't harsh/unpredictable if you know the data.
I don't entirely understand the different issues you are having with wanting to use svg. I am currently using the set up you are describing to render X-Y scatter plots and gaussian curves and found that it works great.
Regarding the last point about object layering, you have to be particularly careful when layering objects with less than 100% opacity which are different colors. The way the colors "add" depends on the order in which you add the objects to your svg drawing.
Thankfully you can use different filters to overlay the colors without blending them. Specifically I am using the FeComposite filter element. There is a good example of its usage here:
http://www.w3.org/TR/SVG/filters.html#feCompositeElement
I'm trying to create a spectral image with a constant grey-scale value for every row. I've written some fantastically slow code that basically tries 1000 different variation between black and white for a given hue and it finds the one whose grey-scale value most closely approximates the target value, resulting in the following image:
On my laptop screen (HP) there is a very noticeable 'dip' near the blue peak, where blue pixels near the bottom of the image appear much brighter than the neighbouring purple and cyan pixels. On my second screen (Acer, which has far superior colour display) the dip is smaller, but still there.
I use the following function to compute the grey-scale approximation of a colour:
Math.Abs(targetGrey - (0.2989 * R + 0.5870 * G + 0.1140 * B))
when I convert the image to grey-scale using Paint.NET, I get a perfect black to white gradient, so that part of the code at least works.
So, question: Is this purely an artefact of the display qualities of my screens? Or can the above mentioned grey-scale algorithm be improved upon to give a visually more consistent result?
EDIT: The problem seems to be mostly monitor calibration. Not, I repeat not, a problem with the code.
I'm wondering if its more to do with the way our eyes interpret the colors, rather than screen artifacts.
That said... I am using a very-high quality screen (Dell Ultrasharp, IPS) that has incredible color reproduction and I'm not sure what you mean by "dip" in the blue peak. So either I'm just not noticing it, or my screen doesn't show the same picture and it more color-accurate.
The output looks correct given the greyscale conversion you have used (which I believe is the standard one for sRGB colour spaces).
However - there are lots of tradeoffs in colour models and one of these is that you can get results which aren't visually quite what you want. In your case, the fact that there is a very low blue weight means that a greater amount of blue is needed to get any given greyscale value, hence the blue seems to start lower, at least in terms of how the human eye perceives it.
If your objective is to get a visually appealing spectral image, then I'd suggest altering your function to make the R,G,B weights more equal, and see if you like what you get.