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‎Dockerfile

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FROM python:3.6.9-stretch
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# ---------------------------------------------------------------------------------------------------------------------
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# Install Java
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RUN apt-get update && apt-get install openjdk-8-jdk -y && apt-get clean
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# ---------------------------------------------------------------------------------------------------------------------
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# Install Cytomine python client
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RUN git clone https://github.com/cytomine-uliege/Cytomine-python-client.git && \
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cd /Cytomine-python-client && git checkout tags/v2.3.0.poc.1 && pip install . && \
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rm -r /Cytomine-python-client
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# ---------------------------------------------------------------------------------------------------------------------
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# Install Neubias-W5-Utilities (annotation exporter, compute metrics, helpers,...)
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RUN apt-get update && apt-get install libgeos-dev -y && apt-get clean
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RUN git clone https://github.com/Neubias-WG5/neubiaswg5-utilities.git && \
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cd /neubiaswg5-utilities/ && git checkout tags/v0.8.8 && pip install .
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# install utilities binaries
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RUN chmod +x /neubiaswg5-utilities/bin/*
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RUN cp /neubiaswg5-utilities/bin/* /usr/bin/
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# cleaning
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RUN rm -r /neubiaswg5-utilities
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# ---------------------------------------------------------------------------------------------------------------------
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# Install FIJI
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# Install virtual X server
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RUN apt-get update && apt-get install -y unzip xvfb libx11-dev libxtst-dev libxrender-dev
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# Install Fiji.
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RUN wget https://downloads.imagej.net/fiji/Life-Line/fiji-linux64-20170530.zip
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RUN unzip fiji-linux64-20170530.zip
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RUN mv Fiji.app/ fiji
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# create a sym-link with the name jars/ij.jar that is pointing to the current version jars/ij-1.nm.jar
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RUN cd /fiji/jars && ln -s $(ls ij-1.*.jar) ij.jar
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# Add fiji to the PATH
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ENV PATH $PATH:/fiji
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RUN mkdir -p /fiji/data
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# Clean up
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RUN rm fiji-linux64-20170530.zip
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# ---------------------------------------------------------------------------------------------------------------------
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# ImageJ plugin
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# install FeatureJ
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RUN cd /fiji/plugins && \
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wget -O imagescience.jar \
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https://imagescience.org/meijering/software/download/imagescience.jar
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RUN cd /fiji/plugins && \
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wget -O FeatureJ_.jar \
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https://imagescience.org/meijering/software/download/FeatureJ_.jar
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# ---------------------------------------------------------------------------------------------------------------------
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# add the local files
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ADD LapClosetPartTracker.ijm /fiji/macros/macro.ijm
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ADD wrapper.py /app/wrapper.py
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# set the entrypoint
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ENTRYPOINT ["python", "/app/wrapper.py"]

‎LapClosetPartTracker.ijm

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// Author: Sébastien Tosi (IRB Barcelona)
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// Contact: [email protected]
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// Version: 1.0
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// Date: 27/12/2019
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// Path to input image and results
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inputDir = "C:\\Users\\Seb\\Desktop\\in";
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outputDir = "C:\\Users\\Seb\\Desktop\\out";
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// Parameters for Cytopacq time-lapse
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LapRad = 9;
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Thr = 0.05;
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// Read arguments from command line
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arg = getArgument();
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parts = split(arg, ",");
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for(i=0; i<parts.length; i++)
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{
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nameAndValue = split(parts[i], "=");
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if (indexOf(nameAndValue[0], "input")>-1) inputDir=nameAndValue[1];
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if (indexOf(nameAndValue[0], "output")>-1) outputDir=nameAndValue[1];
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if (indexOf(nameAndValue[0], "LapRad")>-1) LapRad=nameAndValue[1];
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if (indexOf(nameAndValue[0], "Thr")>-1) Thr=nameAndValue[1];
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}
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images = getFileList(inputDir);
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for(img=0; img<images.length; img++)
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{
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setBatchMode(true);
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// Open image
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FileName = images[img];
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open(inputDir+File.separator+FileName);
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// Workflow
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run("FeatureJ Laplacian", "compute smoothing="+d2s(LapRad,0));
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FilterID = getImageID();
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for(i=0;i<nSlices;i++)
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{
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selectImage(FilterID);
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setSlice(i+1);
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run("Find Maxima...", "noise="+d2s(Thr,3)+" output=List exclude light");
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NewX = newArray(nResults);
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NewY = newArray(nResults);
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for(j=0;j<nResults;j++)
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{
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NewX[j] = getResult("X",j);
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NewY[j] = getResult("Y",j);
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}
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if(i==0)
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{
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newImage("Mask", "16-bit black", getWidth(), getHeight(), nSlices);
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MaskID = getImageID();
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NObjs = lengthOf(NewX);
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for(j=0;j<lengthOf(NewX);j++)setPixel(NewX[j],NewY[j],j+1);
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LastX = NewX;
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LastY = NewY;
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}
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else
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{
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selectImage(MaskID);
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setSlice(i+1);
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LastX_buf = newArray(NObjs);
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LastY_buf = newArray(NObjs);
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for(j=0;j<NObjs;j++)
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{
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MinDst2 = 1/0;
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Mink = 0;
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for(k=0;k<lengthOf(NewX);k++)
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{
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Dst2 = (pow(NewX[k]-LastX[j],2)+pow(NewY[k]-LastY[j],2));
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if(Dst2<MinDst2)
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{
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MinDst2 = Dst2;
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Mink = k;
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}
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}
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setPixel(NewX[Mink],NewY[Mink],j);
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LastX_buf[j] = NewX[Mink];
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LastY_buf[j] = NewY[Mink];
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}
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LastX = LastX_buf;
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LastY = LastY_buf;
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}
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}
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// Save label mask
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selectImage(MaskID);
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//run("Bio-Formats Exporter", "save="+outputDir+File.separator+FileName+" compression=Uncompressed");
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save(outputDir+File.separator+FileName);
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run("Close All");
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}
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setBatchMode("exit & display");

‎descriptor.json

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{
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"name": "PartTracking-ImageJ",
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"container-image": {
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"image": "neubiaswg5/w_parttracking-imagej",
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"type": "singularity"
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},
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"schema-version": "cytomine-0.1",
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"description": "Particle tracking based on linking closest intensity minima detected from LoG filtered time-lapse.",
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"command-line": "python wrapper.py CYTOMINE_HOST CYTOMINE_PUBLIC_KEY CYTOMINE_PRIVATE_KEY CYTOMINE_ID_PROJECT CYTOMINE_ID_SOFTWARE LAPRAD THR",
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"inputs": [
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{
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"id": "cytomine_host",
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"value-key": "@ID",
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"command-line-flag": "--@id",
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"name": "Cytomine host",
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"description": "Cytomine server hostname",
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"type": "String",
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"optional": false,
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"set-by-server": true
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},
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{
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"id": "cytomine_public_key",
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"value-key": "@ID",
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"command-line-flag": "--@id",
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"name": "Cytomine public key",
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"description": "Cytomine public key",
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"type": "String",
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"optional": false,
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"set-by-server": true
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},
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{
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"id": "cytomine_private_key",
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"value-key": "@ID",
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"command-line-flag": "--@id",
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"name": "Cytomine private key",
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"description": "Cytomine private key",
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"type": "String",
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"optional": false,
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"set-by-server": true
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},
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{
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"id": "cytomine_id_project",
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"value-key": "@ID",
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"command-line-flag": "--@id",
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"name": "Cytomine project id",
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"description": "Cytomine project id",
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"type": "String",
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"optional": false,
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"set-by-server": true
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},
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{
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"id": "cytomine_id_software",
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"value-key": "@ID",
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"command-line-flag": "--@id",
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"name": "Cytomine software id",
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"description": "Cytomine software id",
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"type": "String",
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"optional": false,
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"set-by-server": true
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},
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{
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"id": "laprad",
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"value-key": "@ID",
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"command-line-flag": "--@id",
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"name": "LoG Radius",
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"description": "Radius for the LoG filter",
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"type": "Number",
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"default-value": 9,
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"optional": true
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},
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{
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"id": "thr",
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"value-key": "@ID",
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"command-line-flag": "--@id",
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"name": "Threshold",
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"description": "Particle detection threshold",
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"type": "Number",
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"default-value": 0.05,
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"optional": true
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}
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]
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}

‎wrapper.py

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import sys
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from cytomine.models import Job
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from subprocess import call
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from neubiaswg5 import CLASS_PRTTRK
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from neubiaswg5.helpers import NeubiasJob, prepare_data, upload_data, upload_metrics
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def main(argv):
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with NeubiasJob.from_cli(argv) as nj:
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problem_cls = CLASS_PRTTRK
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is_2d = True
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nj.job.update(status=Job.RUNNING, progress=0, statusComment="Initialisation...")
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in_images, gt_images, in_path, gt_path, out_path, tmp_path = prepare_data(problem_cls, nj, is_2d=is_2d, **nj.flags)
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# 2. Call the image analysis workflow
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nj.job.update(progress=25, statusComment="Launching workflow...")
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command = "/usr/bin/xvfb-run ./ImageJ-linux64 -macro macro.ijm " \
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"\"input={}, output={}, laprad={}, thr={}\" -batch".format(
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in_path, out_path, nj.parameters.laprad, nj.parameters.thr)
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return_code = call(command, shell=True, cwd="/fiji") # waits for the subprocess to return
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if return_code != 0:
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err_desc = "Failed to execute the ImageJ macro (return code: {})".format(return_code)
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nj.job.update(progress=100, statusComment=err_desc)
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raise ValueError(err_desc)
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# 4. Create and upload annotations
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nj.job.update(progress=70, statusComment="Uploading extracted annotation...")
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upload_data(problem_cls, nj, in_images, out_path, **nj.flags, is_2d=is_2d, monitor_params={
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"start": 70, "end": 90, "period": 0.1
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})
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# 5. Compute and upload the metrics
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nj.job.update(progress=90, statusComment="Computing and uploading metrics (if necessary)...")
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upload_metrics(problem_cls, nj, in_images, gt_path, out_path, tmp_path, **nj.flags)
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# 6. End the job
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nj.job.update(status=Job.TERMINATED, progress=100, statusComment="Finished.")
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if __name__ == "__main__":
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main(sys.argv[1:])
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