def performClumpingSingleThread(inputImage,
clumpsImage,
tmpDIR='tmp',
width=2000,
height=2000,
gdalformat='KEA'):
"""
Clump the input image using a tiled processing chain allowing large images to be clumped more quickly.
:param inputImage: the input image to be clumped.
:param clumpsImage: the output clumped image.
:param tmpDIR: the temporary directory where intermediate files will be written (default is 'tmp'). Directory will be created and deleted if does not exist.
:param width: int for width of the image tiles used for processing (Default = 2000).
:param height: int for height of the image tiles used for processing (Default = 2000).
:param gdalformat: string with the GDAL image format for the output image (Default = KEA). NOTE. KEA is used as intermediate format internally and therefore needs to be available.
"""
createdTmp = False
if not os.path.exists(tmpDIR):
os.makedirs(tmpDIR)
createdTmp = True
rsgisUtils = rsgislib.RSGISPyUtils()
uidStr = rsgisUtils.uidGenerator()
dataType = rsgisUtils.getRSGISLibDataTypeFromImg(inputImage)
baseName = os.path.splitext(os.path.basename(inputImage))[0] + "_" + uidStr
imgTilesDIR = os.path.join(tmpDIR, "imgtiles_" + uidStr)
tilesClumpsDIR = os.path.join(tmpDIR, "imgclumpstiles_" + uidStr)
tilesImgBase = os.path.join(imgTilesDIR, baseName)
initMergedClumps = os.path.join(tmpDIR,
"MergedInitClumps_" + uidStr + ".kea")
if not os.path.exists(imgTilesDIR):
os.makedirs(imgTilesDIR)
if not os.path.exists(tilesClumpsDIR):
os.makedirs(tilesClumpsDIR)
imageutils.createTiles(inputImage, tilesImgBase, int(width), int(height),
0, False, 'KEA', dataType, 'kea')
imageTiles = glob.glob(tilesImgBase + "*")
for tile in imageTiles:
tilBaseName = os.path.splitext(os.path.basename(tile))[0]
clumpedTile = os.path.join(tilesClumpsDIR, tilBaseName + '_clumps.kea')
segmentation.clump(tile, clumpedTile, 'KEA', True, 0, True)
clumpTiles = glob.glob(os.path.join(tilesClumpsDIR, '*_clumps.kea'))
print("Create Blank Image")
imageutils.createCopyImage(inputImage, initMergedClumps, 1, 0, 'KEA',
rsgislib.TYPE_32UINT)
print("Merge Tiles into Blank Image")
segmentation.mergeClumpImages(clumpTiles, initMergedClumps, True)
print("Merge Tile Boundaries")
segmentation.mergeEquivClumps(initMergedClumps, clumpsImage, gdalformat,
['PixelVal'])
shutil.rmtree(imgTilesDIR)
shutil.rmtree(tilesClumpsDIR)
os.remove(initMergedClumps)
if createdTmp:
shutil.rmtree(tmpDIR)
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
segmentation.eliminateSinglePixels(inputImage, outputImage_1,
outputImage_2, tempFile, gdalformat,
True, ignoreZeros)
except:
print("An error occurred while performing eliminateSinglePixels!")
print(sys.exc_info()[0])
sys.exit(1)
# ------------------------------------------------------------------------------------------------------------------
# Perform clumping
# ------------------------------------------------------------------------------------------------------------------
outputImage_3 = tmpPath + "rsgislib_shep_clump_" + rand_str() + ".tif"
try:
segmentation.clump(outputImage_2, outputImage_3, gdalformat, True, 0)
except:
print("An error occurred while performing clump!")
print(sys.exc_info()[0])
sys.exit(1)
# ------------------------------------------------------------------------------------------------------------------
# Eliminate small segments/clumps
# ------------------------------------------------------------------------------------------------------------------
outputImage_4 = tmpPath + "rsgislib_shep_clump_clean_" + rand_str(
) + ".tif"
minSize = int(float(sys.argv[4]))
spectralThresh = float(sys.argv[5])
try:
def clumpImgFunc(imgs):
"""
Clump an image with values provides as an array for use within a multiprocessing Pool
"""
segmentation.clump(imgs[0], imgs[1], 'KEA', True, 0, True)