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Add SearchFirst macro for weka classifier
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// SPDX-FileCopyrightText: 2024 Friedrich Miescher Institute for Biomedical Research (FMI), Basel (Switzerland) | ||
// | ||
// SPDX-License-Identifier: MIT | ||
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path = getArgument(); | ||
classifierPath = "/path/to/classifier_v1.model"; | ||
mag_firstpass = 4; | ||
mag_secondpass = 20; | ||
overlap_ratio = 0.05; | ||
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// === don't edit below this line | ||
mag_ratio = mag_firstpass / mag_secondpass; | ||
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// list all files in path | ||
folderName = File.getName(path); | ||
fileList = getFileList(path); | ||
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// setup segmentation folder | ||
parent = File.getParent(path); | ||
seg_folder = parent + File.separator + folderName + "_segmentation"; | ||
File.makeDirectory(seg_folder); | ||
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setBatchMode(false); | ||
// loop over image data files (start with folder name) | ||
for (i = 0; i < fileList.length; i++) { | ||
if (startsWith(fileList[i], folderName) && endsWith(fileList[i], ".tif")) { | ||
process(path, fileList[i], seg_folder); | ||
} | ||
} | ||
run("Quit"); | ||
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function process(folder, tifFile, seg_folder) { | ||
// process a single tif file, write a csv file with coordinates | ||
name = File.getNameWithoutExtension(folder + File.separator + tifFile); | ||
print("Processing: " + name); | ||
open(folder + File.separator + tifFile); | ||
run("Subtract Background...", "rolling=50 light sliding"); | ||
run("Bin...", "x=4 y=4 bin=Average"); | ||
run("Trainable Weka Segmentation"); | ||
wait(300); | ||
call("trainableSegmentation.Weka_Segmentation.loadClassifier", classifierPath); | ||
//call("trainableSegmentation.Weka_Segmentation.getResult"); | ||
call("trainableSegmentation.Weka_Segmentation.getProbability"); | ||
selectImage("Probability maps"); | ||
run("Duplicate...", "use"); | ||
selectImage("class 1"); | ||
saveAs("Tiff", seg_folder + File.separator + name + "_prob.tif"); | ||
run("Gaussian Blur...", "sigma=5 slice"); | ||
setOption("BlackBackground", true); | ||
setThreshold(0.4, 1.0); | ||
run("Convert to Mask", "background=Dark black"); | ||
// Remove small particles | ||
maskId = getImageID(); | ||
// save image for quality control | ||
saveAs("PNG", seg_folder + File.separator + name + "_mask.png"); | ||
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// resize image by overlap ratio and magnification ratio | ||
n_tiles_x = Math.ceil((1 + overlap_ratio) / mag_ratio); // 6 | ||
n_tiles_y = Math.ceil((1 + overlap_ratio) / mag_ratio); | ||
print("n_tiles: " + n_tiles_x); | ||
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w = getWidth(); // 500 | ||
h = getHeight(); | ||
tile_w = (w * (1 - overlap_ratio) * mag_ratio); // 80 | ||
tile_h = (h * (1 - overlap_ratio) * mag_ratio); | ||
print("tile_w: " + tile_w); | ||
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offset_x = w/2; | ||
offset_y = h/2; | ||
margin_x = w * mag_ratio * overlap_ratio; // 20 | ||
margin_y = h * mag_ratio * overlap_ratio; | ||
print("margin_x: " + margin_x); | ||
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crop_w = w - margin_x; // 500 => 480 | ||
crop_h = h - margin_y; | ||
print("crop_w: " + crop_w); | ||
run("Canvas Size...", "width=&crop_w height=&crop_h position=Center"); | ||
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target_w = n_tiles_x * tile_w; // | ||
target_h = n_tiles_y * tile_h; | ||
print("target_w: " + target_w); | ||
run("Canvas Size...", "width=&target_w height=&target_h position=Top-Left zero"); | ||
run("Duplicate...", "title=mask"); // DEBUG | ||
run("32-bit"); | ||
run("Size...", "width=&n_tiles_x height=&n_tiles_y depth=1 constrain average interpolation=None"); | ||
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// write csv | ||
height = getHeight(); | ||
width = getWidth(); | ||
rowIndex = 0; | ||
Table.create("Coordinates " + tifFile); | ||
for (x = 0; x < width; x++) { | ||
for (y = 0; y < height; y++) { | ||
if (getPixel(x, y) > 1.0) { | ||
Table.set("X", rowIndex, 4.0 * (x * tile_w + (0.5 * tile_w) + (margin_x/2))); | ||
Table.set("Y", rowIndex, 4.0 * (y * tile_h + (0.5 * tile_h) + (margin_y/2))); | ||
rowIndex++; | ||
} | ||
} | ||
} | ||
Table.showRowNumbers(true); | ||
Table.saveColumnHeader(false); | ||
Table.update(); | ||
Table.save(folder + File.separator + name + ".csv"); | ||
close(Table.title); | ||
close("*"); | ||
} | ||
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// (optional) read all Z slices for given file | ||
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// |