I'm looking to write a macro which requires user input to segment kidneys through thresholding. I'm currently running this:
selectWindow("Cortex");
//run("Threshold...");
title = "WaitForUserDemo";
msg = "If necessary, use the \"Threshold\" tool to\nadjust the threshold, then click \"OK\".";
waitForUser(title, msg);
While the thresholding colour appears, there is no option here to adjust the threshold as the user. Does anyone know how I can get the user to be able to adjust the threshold without having to click "Image -> Adjust - > threshold" each time?
Thanks!
Related
I have sRGB images with color casts. To remove it manually I usually use Photoshop Level Adjustments. Photoshop also have tools for that: Auto Contrast or even better Auto Tone which also takes shadows, midtones & highlights into account.
If I remove the cast manually I adjust each of the RGB channels individually so that the darkest pixels are set to pure black and the lightest to pure white and then redistribute all other values (spreading the histogram). This is a simple approach but shows good results for my images.
In my node.js app I'm using sharp for image processing which uses libvips as its processing engine. I tried to remove the cast with .normalize() but this command works on all channels together and not individual for each of the RGB channels. So it doesn't work for me.
I also asked this question on the sharp project page. I tested the suggestion from lovell to try it with hist_local but the results are not useable for me.
Now I would like to find out how this could be done using the native libvips. I've played around with nip2 GUI and different commands but could not figure out how it could be achieved:
Histogram > Equalise Histogram > Global => Picture looks over saturated
Image > Levels > Scale to 0 - 255 => Channels ar not all spreading from 0 - 255 (I don't understand exactly what this command does?)
Thanks for every hint!
Addition
Here is a example with pictures from Photoshop to show what I want.
The source image is a picture of a frame from a film negative.
Image before processing
Step1 Invert image
Image after inversion
Step2 using Auto tone in Photoshop (works the same way as my description above about manually remove the color cast)
Image after Auto Tone
This last picture is ok for me.
nip2 has a menu item for this.
Load your image and mark a region on it containing the area you'd like to be neutral. It can be any lightness, it doesn't need to be white.
Use File / Open to get the file dialog and you should see the image loaded in your workspace as a thumbnail.
Doubleclick on the thumbnail to open an image view window.
In the view window, zoom and pan to the right spot. The user guide (press F1) has a section on image navigation.
Hold down CTRL and click and drag down and right to mark a rectangular region.
Back in the main window, click Toolkits / Tasks / Capture / White balance. You should see something like:
You can drag an resize your region to change the neutral point. Use the colour picker to set what white means. You can make other whites with (for example) Colour / New / Colour from CCT and link them together.
Click Colour / New / Colour from CCT to make a colour picker from CCT (correlated colour temperature) -- the temperature in Kelvin of that white.
Set it to something interesting, like 4800 for warm white.
Click on the formula for A5.white to edit it, and enter the cell of your CCT widget (A7 in this case).
Now you can drag the region to adjust the pixels to set the neutral from, and drag the CCT slider to set the temperature.
It can be annoying to find things in the toolkit menu. There's a thing for searching toolkits: in the main window, click View / Toolkit browser. You can enter something like "white" and it'll show related toolkit entries.
Here's another answer, but using pyvips and responding to the previous comments. I didn't want to delete the first answer as it still seemed useful.
This version finds the image histogram, searches for thresholds which will select 0.5% and 99.5% of pixels in each image band, then rescales the image so that those pixel values become 0 and 255.
import sys
import pyvips
# trim off this percentage of pixels from the top and bottom
trim_percent = 0.5
def percent(hist, percentage):
"""From a histogram, find the threshold above which lie
#percentage of pixels."""
# normalised cumulative histogram
norm = hist.hist_cum().hist_norm()
# column and row profile over percentage
c, r = (norm > norm.width * percentage / 100).profile()
return r.avg()
image = pyvips.Image.new_from_file(sys.argv[1])
# photographic negative
image = image.invert()
# find image histogram, split to set of separate bands
bands = image.hist_find().bandsplit()
# for each band, the low and high thresholds
low = [percent(band, trim_percent) for band in bands]
high = [percent(band, 100 - trim_percent) for band in bands]
# rescale image
scale = [255.0 / (h - l) for h, l in zip(high, low)]
image = (image - low) * scale
image.write_to_file(sys.argv[2])
It seems to give roughly similar results to the PS button. If I run:
$ ./autolevel.py ~/pics/before.jpg x.jpg
I see:
In the meantime I've found the Simplest Color Balance Algorithm which exactly describes the problem with color casts and there you can also find a C source code.
It is exactly the same solution as John describes in his second answer but as a small piece of c-code.
I'm now trying to use it as C/C++ addon with N-API under node.js.
Is there a possible way to make Color Blob Detection automatically detect a specified color without pressing it ?
Ex I'll just specify what range of color is I want then it would automatically detect the color with the same range.
You probably need to use cv::inRange and define your range of colors as (r1,g1,b1) to (r2,g2,b2). E.g.:
cv::inRange(input, cv::Scalar(0,140,0), cv::Scalar(160,255, 160), output);
I am trying to allow the user to select an appropriate paper size for their printer within my own print settings dialog. Does anyone know a workable solution - preferably cross platform but otherwise OSX.
If I use a TPageSetupDialog then when executed it produces an error in the PASever window of Invalidpmobject although the dialog shows but doesn't seem to affect the current printers paper size. There doesn't seem to be any proerties to see what the user selected either.
I need to set the paper size without actually printing as the user needs to be able to adjust things with the new paper size first.
I finally figured out the problem so here is the solution for anyone else with the problem:
Use TPageSetupDialog but you must set valid pagewidth and pageheight values for the current printer before calling it - otherwise you get an error reported in PAServer window and the printer selection box will be set to "any printer" instead of the current printer name.
Unfortunately you cannot derive the paper size directly from the printer pagewidth and resolution because it reports printable area not paper size. So I set a default of A4 whenever the user chooses another printer. I guess you could set the nearest standard paper size to the calculated value from printer.pagewidth/printer.activeprinter.activedpi.x if you want to take care of printers that do not support A4.
The other point to note is that the default page sizes in the TPageSetupDialog component are wrong. Set the units to mm and use width 210000 and height 297000 (note 10 times bigger than the default values) for A4 size that most printers should support.
I have an image with a group of cells and I need to count them. I did a similar exercise using bwlabel, however this one is a bit more challenging because there are some little cells that I don't want to count. In addition, some cells are on top of each other. I've seem some MATLAB examples online but they all involved functions that aren't available. Do you have any ideas how to separate the overlapping cells?
Here's the image:
To make it clearer: Please help me count the number of red blood cells (which have a circular shape) like so:
The image is in grayscale but I think you can distinguish which ones are red blood cells. They have a distinctive biconcave shape... Everything else doesn't matter. But to be more specific here is an image with all the things that I want to ignore/discard/not count highlighted in red.
The main issue is the overlapping of cells.
The following is an ImageJ macro to do this (which is free software too). I would recommend you use ImageJ (or Fiji), to explore this type of stuff. Then, if you really need it, you can write an Octave program to do it.
run ("8-bit");
setAutoThreshold ("Default");
setOption ("BlackBackground", false);
run ("Convert to Mask");
run ("Fill Holes");
run ("Watershed");
run ("Analyze Particles...", "size=100-Infinity exclude clear add");
This approach gives this result:
And it is point and click equivalent as:
Image > Type > 8-bit
Image > Adjust > Threshold
select "Default" and untick "dark background" on the threshold dialogue. Then click "Apply".
Process > Binary > Fill holes
Process > Binary > Watershed
Analyze > Analyze particles...
7 Set "100-Infinity" as range of valid particle size on the "Analyze particles" dialogue
On ImageJ, if you have a bianry image, watershed actually performs the distance transform, and then the watershed.
Octave has all the functions above except watershed (I plan on implementing it soon).
If you can't use ImageJ for your problem (why not? It can run in headless mode too), then an alternative is to get the area of each object, and if too high, then assume it's multiple cells. It kinda of depends on your question and if can generate a value for average cell size (and error).
Another alternative is to measure the roundness of each object identified. Cells that overlap will be less round, you can identify them that way.
It depends on how much error are you willing to accept on your program output.
This is only to help with "noise" but why not continue using bwlabel and try using bwareaopen to get rid of small objects? It seems the cells are pretty large, just set some size threshold to get rid of small objects http://www.mathworks.com/matlabcentral/answers/46398-removing-objects-which-have-area-greater-and-lesser-than-some-threshold-areas-and-extracting-only-th
As for overlapping cells, maybe setting an upperbound for the size of a single cell. so when you have two cells overlapping, it will classify this as "greater than one cell" or something like that. so it at least acknowledges the shape, but can't determine exactly how many cells are there
From that picture I want to delete all instances of that specific color without having to go manually each pixel at a time.
Thanks
You can use Select / Select Similar to get a selection of all of the pixels with that colour, but bear in mind that Select Similar is affected by the Tolerance setting of the Magic Wand (W) tool.
So, first select the Magic Wand and set the tolerance to zero, then select one of the pixels you want to delete (with Marquee (M) and Edge set to Hard for example), then run Select / Select Similar. You can use the Paint Bucket (G) to replace the selection with whatever colour you want.
Of course, if you do want to catch pixels which aren't exactly the same colour, you can just set the Tolerance slightly higher.