Open J-na opened 4 years ago
Hello @J-na,
Are you sure the image is completely "black"? It might be just 0s and 1s so you need to adjust the contrast or simply apply a LUT to see both classes. If you want to have the same LUT as in the plugin, after getting the result image, do the following:
import trainableSegmentation.utils.Utils;
result.setLut( Utils.getGoldenAngleLUT() );
You have more information here.
Hello @iarganda,
Thank you for getting back to me so quick. Intensity analysis confirms that the image contains only pixels with 0 intensity. Applying the golden angle LUT results in this image.
A quick test of the 'color-based segmentation using clustering' seems to produce promising results so i will look into using that instead.
Hello, i want to use Trainable Weka Segmentation to analyse images of fluorescent cell clusters. When manually running the plugin i can load a saved classifier and apply it just fine. However, when automating the segmentation using a beanshell script it returns a black image instead as the result. This is the script used:
The script does return the probability maps as expected , but not the classified image . The used image and expected results are shown here:
The original image The result from manual segmentation The result from running the script with segmentator.applyClassifier(false); , this happens for every image processed using the script The probability from running the script with segmentator.applyClassifier(true);
I am not sure if this is an issue with the script i am using or with the trainable segmentation itself, but i am hoping it is an easy fix. Thanks in advance :)
Edit: I also tried to immediately convert the generated probability using this script posted earlier https://gist.github.com/iarganda/c7fc0a88b8d2737c9d3d , which generated the same black image as generated by segmentator.applyClassifier(false);. Perhaps it is something related to this?