What this macro does is simply particle analysis. ” files contain the information about how many particles ( Counts) were detected in each frame ( Slice). Results files contain center of mass ( XM, YM) for all particles in the movie, without information about in which frame the particles were found. Run(“Analyze Particles…”, “size= 30– 160 circularity= 0.2– 1.00 show=Masks display clear summarize stack”) Run(“Set Measurements…”, “area center shape redirect=None decimal=3”) You need to use your own values for the Size and Circularity Run(“Make Binary”, “method=Default background=Dark thresholded remaining black”) SetThreshold(0, 121) //Use your own values for your image data You need to use your own values for Threshold. In the macro, you need to use your own values for setThreshold and Analyze Particles.
#Imagej batch processing mac#
The macro is just a text file and should work both on Windows and Mac OS. I made an ImageJ macro that will automatically import the sequential JPG files, do Particle Analysis to calculate center of mass, plot it on an image, and save the results in a folder. Now, let us suppose that we made several behavioral recordings and in each recording the image data were saved as sequentially numbered JPEG files. We will use theses numbers (thresholding, area, cirularity) in the following. In this example, the fish areas were 82, 84, 72, 45, 65 and 127 pixels with the circularity of approx. Then, Analyze > Set Measurements > check “ Area“, “ Center of mass“, and “ Shape descriptors“, and run Analyze > Analyze Particles…
Let’s check the area of the individual fish.įirst, Edit > Invert, (fish appears black with the value of 255, background appears white with 0), The value of 121 worked well with this particular example. Thus, optimization of the lighting condition and image processing may be better done in parallel.Īnyway, let’s separate the animals from the background by thresholding.Ĭlick “Apply” at the thresholding value that gives no background noise. The most important thing is finding the optimal lighting condition that gives the highest contrast to reliably isolate the animals from the background through all the frames. It is not essential whether the animal appears white on black background or black in white background in the original image because it is easily inverted programmatically. When two animals intersected in a frame, how can you tell which is which in the next frame? Here I don’t pursue this issue and simply try to obtain the spatial distribution of the individuals in each frame. With multiple individuals, things become extremely hard. If we work on a single individual, we can easily obtain the position (x,y) in each frame and calculate the velocity.
* list is a file list generated using list=getFileList(dir).In behavioral studies, we want to analyze the locomotion. * dir is a directory path usually provided using dir=getDirectory * fileL=listFiles(dir,list) in order to return fileL. If you are going to use a loop you can use this function to get your files of interest: Have you used imageJ's macro recorder to build some of this or just looked up your commands?Īlso as u/web2linc said if you want to run through a bunch of files you will either need to use batch processing or get a list of files to start and then run this as a for loop. You calling the model you have already trained? Is what you have written doing anything at all (opening new windows/saving outputs) or just failing (if so which line?)Ĭall("trainableSegmentation.Weka_Segmentation.loadClassifier", "/Users/JACOBI/Desktop/PADRE.model")
#Imagej batch processing zip#
Description: Converts a folder of images in any format supported by ImageJ's File>Open command (TIFF, JPEG, DICOM, GIF, PNG, PGM, BMP, FITS, ZIP Compressed TIFF) to TIFF, 8-bit TIFF, JPEG, GIF, PNG, PGM, BMP, FITS, Text Image, ZIP or Raw format. Newbie to ImageJ macros or any form of code? This plugin is built into ImageJ 1.43 and later as the Process>Batch>Convert command.
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