""" ****************************************************************************************** Written by Jim Rowe (U of Sheffield) Started: 2026-02-19 @BotanicalJim james.rowe at sheffield.ac.uk ****************************************************************************************** """ from ij import IJ, ImageStack, ImagePlus from ij.process import ImageProcessor,ShortProcessor, StackStatistics, ImageConverter, FloatProcessor, ImageConverter from ij.measure import ResultsTable from fiji.util.gui import GenericDialogPlus from java.awt import GridLayout, Font, Color from ij import WindowManager as WM from inra.ijpb.measure import IntrinsicVolumes3D from inra.ijpb.label import LabelImages from inra.ijpb.plugins import AnalyzeRegions3D from inra.ijpb.plugins import ParticleAnalysis3DPlugin, BoundingBox3DPlugin, ExtendBordersPlugin def errorDialog(message): """Outputs a given error for end users""" gd = GenericDialogPlus("Error") gd.addMessage(message) gd.showDialog() return def imageSelectDialog(): """Select label map and training image""" imps = WM.getImageTitles() gd = GenericDialogPlus("Select image") gd.addChoice("Label map", imps, imps[0]) gd.addChoice("ROI map", imps, imps[0]) gd.showDialog() choices=gd.getChoices() labelMap=choices.get(0).getSelectedItem() roiMap=choices.get(1).getSelectedItem() if gd.wasCanceled(): IJ.exit() return labelMap, roiMap def createTrainingResultsTable(labelImp, roiImp): """ Exctracts all data required for each label in the image and writes to a results table to be used in the training - needs the label and ROI map to create the training data""" height=labelImp.getHeight() width=labelImp.getWidth() frames=labelImp.getNFrames() depth=labelImp.getStackSize()/frames size = [width, height, depth] labelgtx=clij2.push(labelImp) roigtx=clij2.push(roiImp) #get label stats rtc = ResultsTable() clij2.statisticsOfLabelledPixels(roigtx, labelgtx, rtc) rtcV = ResultsTable() #create point for graph analysis pointsgtx=clij2.create(size, clij2.Float) clij2.reduceLabelsToCentroids(labelgtx, pointsgtx) pointListgtx=clij2.create([rtc.size()+1, 3], clij2.Float) clij2.labelledSpotsToPointList(pointsgtx, pointListgtx) #create vorenoi for graph analysis vorenoigtx=clij2.create(labelgtx) clij2.extendLabelingViaVoronoi(labelgtx, vorenoigtx) clij2.statisticsOfLabelledPixels(vorenoigtx, vorenoigtx, rtcV) #get offsets from 'top' surface in each dimension localvorenoigtx=clij2.create(size, clij2.Float) localpointsgtx=clij2.create(size, clij2.Float) clij2.copy(pointsgtx, localpointsgtx) clij2.copy(vorenoigtx,localvorenoigtx) #extract z positions to pass into surface mapping function zpos=rtc.getColumn("CENTROID_Z") zops= map(float, zpos) ZminsurfaceOffset = minSurfaceMapping(localpointsgtx, localvorenoigtx, zpos) clij2.flip3D(vorenoigtx, localvorenoigtx, 0,0,1) clij2.flip3D(pointsgtx, localpointsgtx,0,0,1) zpos= map(lambda x: size[2]-x, zpos) ZmaxsurfaceOffset = minSurfaceMapping(localpointsgtx, localvorenoigtx, zpos) localvorenoigtx.close() localpointsgtx.close() xpos=rtc.getColumn("CENTROID_X") xops= map(float, xpos) localvorenoigtx=clij2.create([size[2],size[1],size[0]], clij2.Float) localpointsgtx=clij2.create([size[2],size[1],size[0]], clij2.Float) clij2.transposeXZ(vorenoigtx, localvorenoigtx) clij2.transposeXZ(pointsgtx, localpointsgtx) XminsurfaceOffset = minSurfaceMapping(localpointsgtx, localvorenoigtx, xpos) localvorenoigtx2=clij2.create([size[2],size[1],size[0]], clij2.Float) localpointsgtx2=clij2.create([size[2],size[1],size[0]], clij2.Float) clij2.flip3D(localvorenoigtx,localvorenoigtx2, 0,0,1) clij2.flip3D(localpointsgtx,localpointsgtx2, 0,0,1) localvorenoigtx.close() localpointsgtx.close() xpos= map(lambda x: size[0]-x, xpos) XmaxsurfaceOffset = minSurfaceMapping(localpointsgtx2, localvorenoigtx2, xpos) localvorenoigtx2.close() localpointsgtx2.close() ypos=rtc.getColumn("CENTROID_Y") yops= map(float, xpos) localvorenoigtx=clij2.create([size[0],size[2],size[1]], clij2.Float) localpointsgtx=clij2.create([size[0],size[2],size[1]], clij2.Float) clij2.transposeYZ(vorenoigtx, localvorenoigtx) clij2.transposeYZ(pointsgtx, localpointsgtx) YminsurfaceOffset = minSurfaceMapping(localpointsgtx, localvorenoigtx, ypos) localvorenoigtx2=clij2.create([size[0],size[2],size[1]], clij2.Float) localpointsgtx2=clij2.create([size[0],size[2],size[1]], clij2.Float) clij2.flip3D(localvorenoigtx,localvorenoigtx2, 0,0,1) clij2.flip3D(localpointsgtx,localpointsgtx2, 0,0,1) localvorenoigtx.close() localpointsgtx.close() ypos= map(lambda x: size[1]-x, ypos) YmaxsurfaceOffset = minSurfaceMapping(localpointsgtx2, localvorenoigtx2,ypos) localvorenoigtx2.close() localpointsgtx2.close() #Generate touching and distance matrices touchMatixgtx=clij2.create([rtc.size()+1,rtc.size()+1], clij2.Float) clij2.generateTouchMatrix(vorenoigtx, touchMatixgtx) distanceMatixgtx=clij2.create([rtc.size()+1,rtc.size()+1], clij2.Float) clij2.generateDistanceMatrix(pointListgtx,pointListgtx, distanceMatixgtx) rtcG=ResultsTable() #extract graph theory parameters and wrtie them to the rtG resultstable neighbourCountGTX=clij2.create(rtc.size()+1,1, 1) clij2.countTouchingNeighbors(touchMatixgtx, neighbourCountGTX) clij2.pullToResultsTableColumn(neighbourCountGTX, rtcG, "TOUCHING_NEIGHBORS", 0) neighbourDistGTX=clij2.create(rtc.size()+1,1, 1) clij2.averageDistanceOfTouchingNeighbors(distanceMatixgtx,touchMatixgtx, neighbourDistGTX) clij2.pullToResultsTableColumn(neighbourDistGTX, rtcG, "AV_TOUCH_DISTANCE", 0) clij2.maximumDistanceOfTouchingNeighbors (distanceMatixgtx,touchMatixgtx, neighbourDistGTX) clij2.pullToResultsTableColumn(neighbourDistGTX, rtcG, "MAX_TOUCH_DISTANCE", 0) clij2.minimumDistanceOfTouchingNeighbors (distanceMatixgtx,touchMatixgtx, neighbourDistGTX) clij2.pullToResultsTableColumn(neighbourDistGTX, rtcG, "MIN_TOUCH_DISTANCE", 0) # use vorenoi to work out which ROI are closest to each surface minz=rtcV.getColumn('BOUNDING_BOX_Z') maxz=rtcV.getColumn('BOUNDING_BOX_END_Z') minx=rtcV.getColumn('BOUNDING_BOX_X') maxx=rtcV.getColumn('BOUNDING_BOX_END_X') miny=rtcV.getColumn('BOUNDING_BOX_Y') maxy=rtcV.getColumn('BOUNDING_BOX_END_Y') minZV= map(lambda x: x == float(min(minz)), minz) maxZV= map(lambda x: x == float(max(maxz)), maxz) minXV= map(lambda x: x == float(min(minx)), minx) maxXV= map(lambda x: x == float(max(maxx)), maxx) minYV= map(lambda x: x == float(min(miny)), miny) maxYV= map(lambda x: x == float(max(maxy)), maxy) graphZmin=graphDistCalc(minZV,touchMatixgtx) graphZmax=graphDistCalc(maxZV,touchMatixgtx) graphXmin=graphDistCalc(minXV,touchMatixgtx) graphXmax=graphDistCalc(maxXV,touchMatixgtx) graphYmin=graphDistCalc(minYV,touchMatixgtx) graphYmax=graphDistCalc(maxYV,touchMatixgtx) rtcG.deleteRow(0) headings=rtc.getColumnHeadings() headingList=headings.split() #get morpholib stats PA3d = ParticleAnalysis3DPlugin() morphResults = PA3d.process(labelImp) morphColumnNames = morphResults.getColumnHeadings().split() #combine data tables and display the training data file rtc2= ResultsTable() for j in range(rtc.size()): rtc2.addRow() for i in range(len(headingList)-1): rtc2.addValue(headingList[i], rtc.getColumn(i)[j]) for i in range(len(morphColumnNames)-1): rtc2.addValue(morphColumnNames[i+1].upper().replace(".", "_"),morphResults.getColumn(i)[j]) rtc2.addValue('VORONOI_X_MIN_TOUCH', minXV[j]) rtc2.addValue('VORONOI_X_MAX_TOUCH', maxXV[j]) rtc2.addValue('VORONOI_Y_MIN_TOUCH', minYV[j]) rtc2.addValue('VORONOI_Y_MAX_TOUCH', maxYV[j]) rtc2.addValue('VORONOI_Z_MIN_TOUCH', minZV[j]) rtc2.addValue('VORONOI_Z_MAX_TOUCH', maxZV[j]) rtc2.addValue('GRAPH_DIST_TO_X0', graphXmin[j+1]) rtc2.addValue('GRAPH_DIST_TO_XMAX', graphXmax[j+1]) rtc2.addValue('GRAPH_DIST_TO_Y0', graphYmin[j+1]) rtc2.addValue('GRAPH_DIST_TO_YMAX', graphYmax[j+1]) rtc2.addValue('GRAPH_DIST_TO_Z0', graphZmin[j+1]) rtc2.addValue('GRAPH_DIST_TO_ZMAX', graphZmax[j+1]) rtc2.addValue('XMIN_SURFACE_OFFSET', XminsurfaceOffset[j]) rtc2.addValue('XMAX_SURFACE_OFFSET', XmaxsurfaceOffset[j]) rtc2.addValue('YMIN_SURFACE_OFFSET', YminsurfaceOffset[j]) rtc2.addValue('YMAX_SURFACE_OFFSET', YmaxsurfaceOffset[j]) rtc2.addValue('ZMIN_SURFACE_OFFSET', ZminsurfaceOffset[j]) rtc2.addValue('ZMAX_SURFACE_OFFSET', ZmaxsurfaceOffset[j]) rtc2.addValue("VORENOI_NEIGHBORS", rtcG.getColumn( "TOUCHING_NEIGHBORS")[j]) rtc2.addValue("VOR_AV_TOUCH_DISTANCE", rtcG.getColumn( "AV_TOUCH_DISTANCE")[j]) rtc2.addValue("VOR_MAX_TOUCH_DISTANCE", rtcG.getColumn( "MAX_TOUCH_DISTANCE")[j]) rtc2.addValue("VOR_MIN_TOUCH_DISTANCE", rtcG.getColumn( "MIN_TOUCH_DISTANCE")[j]) rtc2.addValue('LABEL_ID', 11) touchMatixgtx.close() distanceMatixgtx.close() neighbourCountGTX.close() neighbourDistGTX.close() heads=rtc2.getColumnHeadings().split() vorenoigtx.close() pointsgtx.close() pointListgtx.close() return rtc2 def graphDistCalc(inputVector,touchMatixgtx): """Creates a graph distance vector from the given vector where 1 is the start point""" rt=ResultsTable() inputVector.insert(0,0.0) GraphDistances=FloatProcessor(len(inputVector),1, inputVector, None) GraphDistancesImp= ImagePlus("GraphDistances", GraphDistances) Graphgtx=clij2.push(GraphDistancesImp) newGraphgtx=clij2.create(Graphgtx) clij2.copy(Graphgtx,newGraphgtx) gtx=clij2.create(Graphgtx) cropgtx=clij2.create([1,len(inputVector)],clij2.Float) clij2.crop(Graphgtx, cropgtx, 1,len(inputVector)) i=0 # use the maximumOfTouchingNeighbors to expand the network, then add on the orginal vector. Floods then maintains the gradient out while clij2.getMinimumOfAllPixels(cropgtx)==0: i=i+1 clij2.maximumOfTouchingNeighbors(newGraphgtx, touchMatixgtx, gtx) clij2.addImages(gtx, Graphgtx, newGraphgtx) clij2.crop(newGraphgtx, cropgtx, 1,len(inputVector)) if i==1000: # Just in case isolated things are passed print(clij2.getMinimumOfAllPixels(newGraphgtx)) break clij2.pullToResultsTableColumn(newGraphgtx, rt, "placeholder", 0) inverseData=rt.getColumn("placeholder") #reverse direction of the map finalcolumn = map(lambda x: max(inverseData)-x, inverseData) #print(finalcolumn) finalcolumn[0]=0.0 #cleanup Graphgtx.close() newGraphgtx.close() gtx.close() GraphDistancesImp.close() return finalcolumn def minSurfaceMapping(localpointsgtx, localvorenoigtx, pos): """ WORK OUT WHY REPEATING THIS CAUSES CRASHES""" minzTest =map(float, pos) minzTest.insert(0,0.0) pointListgtx=clij2.create([len(minzTest), 3], clij2.Float) clij2.labelledSpotsToPointList(localpointsgtx, pointListgtx) with open('file.txt', 'a') as outfile: outfile.write('\n mid2 \n') outfile.write(clij2.reportMemory()) zPositionsgtx=clij2.create(localvorenoigtx.getDimensions(), clij2.Float) with open('file.txt', 'a') as outfile: outfile.write('\n mid3 \n') outfile.write(clij2.reportMemory()) minzPositionsgtx=clij2.create(zPositionsgtx) minzTestFP=FloatProcessor(len(minzTest),1, minzTest, None) minzTestImp= ImagePlus("minzTestFP", minzTestFP) minzTestgtx=clij2.push(minzTestImp) #generate parametric image of z position, then use a minimum of touching neighbours to identify the top nuceli locally, then blur for a smoother surface clij2.generateParametricImage(localvorenoigtx ,minzTestgtx, zPositionsgtx) clij2.minimumOfTouchingNeighborsMap(zPositionsgtx, localvorenoigtx, minzPositionsgtx, 2, 0) # Flatten vector image: Reassign vector image z position to 0 pointlist2Dgtx = clij2.create(pointListgtx) heightVectorgtx = clij2.create([len(minzTest), 1], clij2.Float) clij2.copy(pointListgtx,pointlist2Dgtx) clij2.drawBox(pointlist2Dgtx, 0,2,0, len(minzTest), 1 , 1, 0) sizel= minzPositionsgtx.getDimensions() sizel[2]=1 #extract surface position from the smoothed surface map localMinzPosgtx0=clij2.create(sizel, clij2.Float) clij2.copySlice(minzPositionsgtx, localMinzPosgtx0, 0) minzPositionsgtx.close() localMinzPosgtx0Smooth=clij2.create(sizel, clij2.Float) clij2.gaussianBlur2D(localMinzPosgtx0,localMinzPosgtx0Smooth,20,20) rtcG2=ResultsTable() clij2.readValuesFromPositions(pointlist2Dgtx, localMinzPosgtx0Smooth, heightVectorgtx) clij2.pullToResultsTableColumn(heightVectorgtx, rtcG2, "SURFACE_Z_DEPTH", 0) surfaceZ=rtcG2.getColumn('SURFACE_Z_DEPTH') #subtract surface depth from z position to get the Z displacement from the surface surfaceOffset= map(lambda x: pos[x]-surfaceZ[x+1], range(len(pos))) pointListgtx.close() localMinzPosgtx0.close() zPositionsgtx.close() minzPositionsgtx.close() pointlist2Dgtx.close() heightVectorgtx.close() localMinzPosgtx0Smooth.close() minzTestgtx.close() return surfaceOffset try: from net.haesleinhuepf.clij2 import CLIJ2 except: errorDialog("""This plugin requires clij2 to function. To install please follow these instructions: 1. Click Help>Update> Manage update sites 2. Make sure the "clij" and "clij2" update sites are selected. 3. Click Close> Apply changes. 4. Close and reopen ImageJ""") clij2 = CLIJ2.getInstance() # *****************************body of code starts**************************************** if __name__ == "__main__": clij2.clear() labelMapName, roiMapName = imageSelectDialog() IJ.log("Label map = " +str(labelMapName)) IJ.log("ROI map = " +str(roiMapName)) #get labels and Roi imageplus, push to gpu labelImp=WM.getImage(labelMapName) roiImp=WM.getImage(roiMapName) rtc2= createTrainingResultsTable(labelImp, roiImp) rtc2.show("Training data") clij2.clear()