I have a grayscale image, which has a certain wanted pattern of colours + some unwanted colors.
The colors I want to leave are (rgb):
000
666
121212
181818
242424
303030
363636
424242
As you can see, there's a pattern. Umfortunately there are some really "hard to select" colors also. The colors are actually contours (curves for height changes of the terrain), so they would be really tiresome to edit manually. The image is 2048 x 2048 pixels.
How could I somehow limit the image just to have those certain colors and maybe even automagically convert the wrong ones to those wanted ones?
You could try converting the image mode to indexed color:
Then choose a custom pallet:
Then add your custom colors to the pallet. Set dither to none. It should convert all colors to the index color they are closest to.
To remove the white lines... convert mode back to rgb, use magic wand to select all white lines (uncheck contiguous and set tolerance to around 10). Then choose select>modify>expand and expand selection by 1 pixel. Now choose edit>fill and choose content-aware.
This should fill in the lines with the colors around them.
Set color to index again to clean up the blured shape edges.
Hope this helps.
Related
I have a table like this one: https://docs.google.com/spreadsheets/d/1Kn4vfbHwpif7u-6ZTznFpBJFNHhnStETPIQVyQq8xgY/edit#gid=0 with bottom / top color and the Red, Green, Blue (RGB) of the result (where it states 'Preparation' for the bottom color means the canvas so essentially its the RGB of the top color - those rows are the 'single colors').
I am looking for a relation between the double colors and the single colors. E.g. could I somehow subtract one color from their combination and get the other? Either by using the RGB values or using the images in some software?
Note that the type/formula/function/relation that I am looking for will be only for specific single colors and their combinations which I have already measured (do not care if it is valid beyond the dataset that I am working with)
My question is about color tracking... What is the color threshold value for white in python ? I need to track the white color alone in a group of pictures. So I need to separate the white color. In order to do so I need to know the threshold value of white color...
It depends on your pictures. Assuming that you're going to threshold using the RGB values, the RGB value for white is (255, 255, 255). But this value holds true for pure white color. If you have real-world pictures, you might have clearly white color at certain areas in your image but they wouldn't have the value (225, 255, 255). Factors like the shadow, lighting conditions, angle etc. contribute to the variance from pure white color value.
In order to threshold correctly, you need to check the range of values for your set of pictures. I recently worked on a similar problem and for my case, the range of values was as follows:
Red channel: 200-255
Green channel: 180-255
Blue channel: 140-255
But please note that this accepts a lot of variation of white like light yellow. It will highly depend on your case so make sure you check the range on your data.
One way of that can be by displaying/showing your image using skimage and then hovering over white areas, it will display the RGB value on the bottom right corner of the image. Here is the code for showing an image in skimage:
from skimage import io
def show(img):
io.imshow(img)
io.show()
You can create a range of values/threshold from the values you notice this way.
I'm fairly new to GIMP
I have some black-and-white images in RGB mode. I want to highlight some areas in plain Red (ie, zero Blue+Green), some in plain Blue (ie, zero Red+Green), and the rest in plain Green (ie, zero Red+Blue)
I will be selecting several areas using Paths, though a simple rectangle would be fine for now
The final image will be Green, with 2+ selections of Red, and 2+ selections of Blue
I have experimented with multiple layers & multiple images, but I always get problems with the selection areas
Thanks in advance !
If what you want is keep the value of the R (or G or B) channel in the selection, while setting the other two components to 0:
Create a layer group above your image layer
Add a transparent layer in the group, name it "Green", bucket-fill with green
Add a transparent layer in the group, above "Green", name it "Red+Blue"
Set the group to "Multiply" mode. You should see your image in green.
To add red/blue, make a selection, make sure "Red+Blue" is the active layer, and bucket fill the selection with Red or Blue.
Notes
With some selection tools, (path, ellipse...) you may have to use Select>Sharpen before the bucket-fill to make sure that there are no partially selected pixels
To see the original image when making selections, just make the group invisible.
You can also use two separate layers for Red and Blue (both above the Green one, in the layer group)
If what you want is just areas of #FF0000 and #0000FF over a #00FF00 background, then just hide the initial image layer when exporting.
How can I retain a specific colour of an object (or layer) but change the transparency?
I have 2 objects which I want to have a specific colour but currently the opacity is 100%. I need to maintain the current colours but with a opacity of 50%.
Obviously if I change the opacity the colours change (dependent on the background). I need to know how to get an original colour at 100% opacity to make my desired colour at 50% opacity.
Okay so couldn't find a specific way to do it with photoshop so I worked out the math based off the RGB values and came up with a formula to do the job.
For each colour channel I used this formula:
Colour value = Desired Colour + (Background Colour - Desired Colour)*(1-1/Desired Opacity)
eg. 30 = 120 + (255-120)*(1-1/0.6)
Obvious only values between 0-255 are applicable and you may need to round values. This also needs to be done 3 times for red, green and blue.
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.