def performStage2TilesSegmentation(self, tilesImgDIR, tilesMaskedDIR, tilesSegsDIR, tilesSegBordersDIR, tmpDIR, tilesBase, s1BordersImage, segStatsInfo, minPxlsVal, distThresVal, bandsVal, ncpus):
rsgisUtils = rsgislib.RSGISPyUtils()
imgTiles = glob.glob(os.path.join(tilesImgDIR, tilesBase+"*.kea"))
for imgTile in imgTiles:
baseName = os.path.splitext(os.path.basename(imgTile))[0]
maskedFile = os.path.join(tilesMaskedDIR, baseName + '_masked.kea')
dataType = rsgisUtils.getRSGISLibDataTypeFromImg(imgTile)
imageutils.maskImage(imgTile, s1BordersImage, maskedFile, 'KEA', dataType, 0, 0)
imgTiles = glob.glob(os.path.join(tilesMaskedDIR, tilesBase+"*_masked.kea"))
def stage2threadedTiledImgSeg(imgTile):
baseName = os.path.splitext(os.path.basename(imgTile))[0]
clumpsFile = os.path.join(tilesSegsDIR, baseName + '_segs.kea')
kMeansCentres, imgStretchStats = self.findSegStatsFiles(imgTile, segStatsInfo)
segutils.runShepherdSegmentationPreCalcdStats(imgTile, clumpsFile, kMeansCentres, imgStretchStats, outputMeanImg=None, tmpath=os.path.join(tmpDIR, baseName+'_segstemp'), gdalformat='KEA', noStats=False, noStretch=False, noDelete=False, minPxls=minPxlsVal, distThres=distThresVal, bands=bandsVal, processInMem=False)
p = Pool(ncpus)
p.map(stage2threadedTiledImgSeg, imgTiles)
segTiles = glob.glob(os.path.join(tilesSegsDIR, tilesBase+"*_segs.kea"))
for segTile in segTiles:
baseName = os.path.splitext(os.path.basename(segTile))[0]
borderMaskFile = os.path.join(tilesSegBordersDIR, baseName + '_segsborder.kea')
rastergis.defineBorderClumps(segTile, 'BoundaryClumps')
rastergis.exportCol2GDALImage(segTile, borderMaskFile, 'KEA', rsgislib.TYPE_8UINT, 'BoundaryClumps')
def createStage3ImageSubsets(self, inputImage, s2BordersImage, s3BordersClumps, subsetImgsDIR, subsetImgsMaskedDIR, subImgBaseName, minSize):
segmentation.clump(s2BordersImage, s3BordersClumps, 'KEA', True, 0)
rastergis.populateStats(s3BordersClumps, True, True)
rastergis.spatialExtent(s3BordersClumps, 'minXX', 'minXY', 'maxXX', 'maxXY', 'minYX', 'minYY', 'maxYX', 'maxYY')
rsgisUtils = rsgislib.RSGISPyUtils()
dataType = rsgisUtils.getRSGISLibDataTypeFromImg(inputImage)
ratDS = gdal.Open(s3BordersClumps, gdal.GA_Update)
minX = rat.readColumn(ratDS, "minXX")
maxX = rat.readColumn(ratDS, "maxXX")
minY = rat.readColumn(ratDS, "minYY")
maxY = rat.readColumn(ratDS, "maxYY")
Histogram = rat.readColumn(ratDS, "Histogram")
for i in range(minX.shape[0]):
if i > 0:
subImage = os.path.join(subsetImgsDIR, subImgBaseName + str(i) + '.kea')
#print( "[" + str(minX[i]) + ", " + str(maxX[i]) + "][" + str(minY[i]) + ", " + str(maxY[i]) + "]" )
imageutils.subsetbbox(inputImage, subImage, 'KEA', dataType, minX[i], maxX[i], minY[i], maxY[i])
if Histogram[i] > minSize:
maskedFile = os.path.join(subsetImgsMaskedDIR, subImgBaseName + str(i) + '_masked.kea')
else:
maskedFile = os.path.join(subsetImgsMaskedDIR, subImgBaseName + str(i) + '_burn.kea')
imageutils.maskImage(subImage, s2BordersImage, maskedFile, 'KEA', dataType, 0, 0)
rastergis.populateStats(maskedFile, True, False)
ratDS = None
def createTilesFromMasks(inputImage, tilesBase, tilesMetaDIR, tilesImgDIR,
datatype, gdalformat):
"""
A function to apply the image tile masks defined in createTileMaskImages to the input image to extract the individual tiles.
Where:
:param inputImage: is the input image being tiled.
:param tileMasksBase: is the base path for the tile masks. glob will be used to find them with \*.kea added to the end.
:param outTilesBase: is the base file name for the tiles.
"""
maskFiles = glob.glob(os.path.join(tilesMetaDIR, tilesBase + "*.kea"))
idx = 1
for maskFile in maskFiles:
tileImage = os.path.join(tilesImgDIR, os.path.basename(maskFile))
imageutils.maskImage(inputImage, maskFile, tileImage, gdalformat,
datatype, 0, 0)
imageutils.popImageStats(tileImage, True, 0., True)
