class PlanarSliceSourceTest(ut.TestCase):
def setUp(self):
self.raw = np.random.randint(0, 100, (10, 3, 3, 128, 3))
self.a = ArraySource(self.raw)
self.ss = PlanarSliceSource(self.a, projectionAlongTZC)
def testRequest(self):
self.ss.setThrough(0, 1)
self.ss.setThrough(2, 2)
self.ss.setThrough(1, 127)
sl = self.ss.request((slice(None), slice(None))).wait()
self.assertTrue(np.all(sl == self.raw[1, :, :, 127, 2]))
sl_bounded = self.ss.request((slice(0, 3), slice(1, None))).wait()
numpy.testing.assert_array_equal(sl_bounded, self.raw[1, 0:3, 1:, 127,
2])
def testDirtynessPropagation(self):
self.ss.setThrough(0, 1)
self.ss.setThrough(2, 2)
self.ss.setThrough(1, 127)
check_mock = mock.Mock()
self.ss.isDirty.connect(check_mock)
self.a.setDirty(np.s_[1:2, :, 1:2, 127:128, 2:3])
self.ss.isDirty.disconnect(check_mock)
check_mock.assert_called_once_with(np.s_[:, 1:2])
def setUp( self ):
GenericArraySourceTest.setUp(self)
self.lena = np.load(os.path.join(volumina._testing.__path__[0], 'lena.npy'))
self.raw = np.zeros((1,512,512,1,1))
self.raw[0,:,:,0,0] = self.lena
self.source = ArraySource( self.raw )
self.samesource = ArraySource( self.raw )
self.othersource = ArraySource( np.array(self.raw) )
def setUp(self):
GenericArraySourceTest.setUp(self)
self.cells2d = np.load(os.path.join(volumina._testing.__path__[0], "2d_cells_apoptotic_1channel.npy"))
y, x = self.cells2d.shape
self.raw = np.zeros((1, y, x, 1, 1))
self.raw[0, :, :, 0, 0] = self.cells2d
self.source = ArraySource(self.raw)
self.samesource = ArraySource(self.raw)
self.othersource = ArraySource(np.array(self.raw))
def setUp( self ):
dataShape = (1, 900, 400, 10, 1) # t,x,y,z,c
data = np.indices(dataShape)[3].astype(np.uint8) # Data is labeled according to z-index
self.ds1 = ArraySource( data )
self.CONSTANT = 13
self.ds2 = ConstantSource( self.CONSTANT )
self.layer1 = GrayscaleLayer( self.ds1, normalize=False )
self.layer1.visible = True
self.layer1.opacity = 1.0
self.layer2 = GrayscaleLayer( self.ds2, normalize=False )
self.lsm = LayerStackModel()
self.pump = ImagePump( self.lsm, SliceProjection(), sync_along=(0,1,2) )
def setupLayers(self):
layers = []
op = self.topLevelOperatorView
# Superpixels
if op.Superpixels.ready():
layer = ColortableLayer( LazyflowSource(op.Superpixels), self._sp_colortable )
layer.colortableIsRandom = True
layer.name = "Superpixels"
layer.visible = True
layer.opacity = 0.5
layers.append(layer)
del layer
# Debug layers
if op.debug_results:
for name, compressed_array in op.debug_results.items():
axiskeys = op.Superpixels.meta.getAxisKeys()[:-1] # debug images don't have a channel axis
permutation = map(lambda key: axiskeys.index(key) if key in axiskeys else None, 'txyzc')
arraysource = ArraySource( TransposedView(compressed_array, permutation) )
if compressed_array.dtype == np.uint32:
layer = ColortableLayer(arraysource, self._sp_colortable)
else:
layer = GrayscaleLayer(arraysource)
# TODO: Normalize? Maybe the drange should be included with the debug image.
layer.name = name
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
del layer
# Threshold
if op.ThresholdedInput.ready():
layer = ColortableLayer( LazyflowSource(op.ThresholdedInput), self._threshold_colortable )
layer.name = "Thresholded Input"
layer.visible = True
layer.opacity = 1.0
layers.append(layer)
del layer
# Raw Data (grayscale)
if op.Input.ready():
layer = self._create_grayscale_layer_from_slot( op.Input, op.Input.meta.getTaggedShape()['c'] )
layer.name = "Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
del layer
# Raw Data (grayscale)
if op.RawData.ready():
layer = self.createStandardLayerFromSlot( op.RawData )
layer.name = "Raw Data"
layer.visible = True
layer.opacity = 1.0
layers.append(layer)
del layer
return layers
def createWidget(self, parent):
a = (numpy.random.random((1, 100, 200, 300, 1)) * 255).astype(numpy.uint8)
source = ArraySource(a)
layerstack = LayerStackModel()
layerstack.append(GrayscaleLayer(source))
editor = VolumeEditor(layerstack, labelsink=None, parent=self)
widget = VolumeEditorWidget(parent=parent)
if not _has_lazyflow:
widget.setEnabled(False)
widget.init(editor)
editor.dataShape = a.shape
return widget
def setUp( self ):
dataShape = (1, 900, 400, 10, 1) # t,x,y,z,c
data = np.indices(dataShape)[3] # Data is labeled according to z-index
self.ds1 = ArraySource( data )
self.CONSTANT = 13
self.ds2 = ConstantSource( self.CONSTANT )
self.layer1 = GrayscaleLayer( self.ds1 )
self.layer1.visible = True
self.layer1.opacity = 1.0
self.layer2 = GrayscaleLayer( self.ds2 )
self.lsm = LayerStackModel()
self.pump = ImagePump( self.lsm, SliceProjection() )
def showStuff(raw_name,
pred_viewer1,
pred_viewer2,
cutout_name,
one_extra=None):
# display the raw and annotations for cremi challenge data
raw = vigra.impex.readHDF5(indir + datasets[raw_name], "data", order='C')
# raw_old = vigra.readHDF5(indir+datasets["raw_bad"], "data", order = 'C')
defect_prediction_128 = vigra.impex.readHDF5(indir +
datasets[pred_viewer2],
"data",
order='C')
defect_prediction_150 = vigra.impex.readHDF5(indir +
datasets[pred_viewer1],
"data",
order='C')
cutout_from_150_pred = vigra.impex.readHDF5(indir + datasets[cutout_name],
"data",
order='C')
####################################################################################################################
# only used for fast testing stuff
#change_one = vigra.readHDF5(indir+datasets["segmentation_on_equalized_image"], "data", order = 'C')
#pdb.set_trace()
#defect_prediction_150[1,:,:] = change_one[0,:,:,0]
####################################################################################################################
# defect_prediction_150 = gt[..., 0]
cutout = numpy.asarray(cutout_from_150_pred)
rawdata = numpy.asarray(raw)
# rawdata_old = numpy.asarray(raw_old)
# op5ify
# shape5d = rawdata.shape
shape5d = (1, ) + rawdata.shape + (1, )
print shape5d, rawdata.shape, rawdata.dtype
app = QApplication([])
v = Viewer()
direct = False
# layer for raw data
rawdata = numpy.reshape(rawdata, shape5d)
rawsource = ArraySource(rawdata)
v.dataShape = shape5d
lraw = GrayscaleLayer(rawsource, direct=direct)
lraw.visible = True
lraw.name = "raw"
v.layerstack.append(lraw)
# layer for cutout regions from raw data
cutout = numpy.reshape(cutout, shape5d)
cutoutsource = ArraySource(cutout)
lcutout = GrayscaleLayer(cutoutsource, direct=direct)
lcutout.visible = False
lcutout.name = "cut_out"
v.layerstack.append(lcutout)
# layer for first prediction result
defect_prediction_128 = numpy.reshape(defect_prediction_128, shape5d)
synsource = ArraySource(defect_prediction_128)
ct = create_random_16bit()
ct[0] = 0
lsyn = ColortableLayer(synsource, ct)
lsyn.name = pred_viewer2
lsyn.visible = False
v.layerstack.append(lsyn)
# layer for second prediction result
segm = numpy.reshape(defect_prediction_150, shape5d)
segsource = ArraySource(segm)
ct = create_random_16bit()
ct[0] = 0
lseg = ColortableLayer(segsource, ct)
lseg.name = pred_viewer1
lseg.visible = False
v.layerstack.append(lseg)
if one_extra is None:
v.showMaximized()
app.exec_()
if one_extra is not None:
# layer for third prediction result
extra_prediction = vigra.readHDF5(indir + datasets[one_extra],
"data",
order='C')
extra_pred_reshaped = numpy.reshape(extra_prediction, shape5d)
segsource = ArraySource(extra_pred_reshaped)
ct = create_random_16bit()
ct[0] = 0
# ct = create_default_16bit()
lseg = ColortableLayer(segsource, ct)
lseg.name = one_extra
lseg.visible = False
v.layerstack.append(lseg)
v.showMaximized()
app.exec_()
class DirtyPropagationTest( ut.TestCase ):
def setUp( self ):
dataShape = (1, 900, 400, 10, 1) # t,x,y,z,c
data = np.indices(dataShape)[3].astype(np.uint8) # Data is labeled according to z-index
self.ds1 = ArraySource( data )
self.CONSTANT = 13
self.ds2 = ConstantSource( self.CONSTANT )
self.layer1 = GrayscaleLayer( self.ds1, normalize=False )
self.layer1.visible = True
self.layer1.opacity = 1.0
self.layer2 = GrayscaleLayer( self.ds2, normalize=False )
self.lsm = LayerStackModel()
self.pump = ImagePump( self.lsm, SliceProjection(), sync_along=(0,1,2) )
def testEverythingDirtyPropagation( self ):
self.lsm.append(self.layer2)
tiling = Tiling((900,400), blockSize=100)
tp = TileProvider(tiling, self.pump.stackedImageSources)
tp.requestRefresh(QRectF(100,100,200,200))
tp.waitForTiles()
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == self.CONSTANT))
self.assertTrue(np.all(aimg[:,:,3] == 255))
NEW_CONSTANT = self.CONSTANT+1
self.ds2.constant = NEW_CONSTANT
tp.requestRefresh(QRectF(100,100,200,200))
tp.waitForTiles()
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == NEW_CONSTANT))
self.assertTrue(np.all(aimg[:,:,3] == 255))
def testOutOfViewDirtyPropagation( self ):
self.lsm.append(self.layer1)
tiling = Tiling((900,400), blockSize=100)
tp = TileProvider(tiling, self.pump.stackedImageSources)
# Navigate down to the second z-slice
self.pump.syncedSliceSources.through = [0,1,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.waitForTiles()
# Sanity check: Do we see the right data on the second
# slice? (should be all 1s)
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == 1))
self.assertTrue(np.all(aimg[:,:,3] == 255))
# Navigate down to the third z-slice
self.pump.syncedSliceSources.through = [0,2,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.waitForTiles()
# Sanity check: Do we see the right data on the third
# slice?(should be all 2s)
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == 2))
self.assertTrue(np.all(aimg[:,:,3] == 255))
# Navigate back up to the second z-slice
self.pump.syncedSliceSources.through = [0,1,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.waitForTiles()
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == 1))
self.assertTrue(np.all(aimg[:,:,3] == 255))
# Change some of the data in the (out-of-view) third z-slice
slicing = (slice(None), slice(100,300), slice(100,300),
slice(2,3), slice(None))
slicing = tuple(slicing)
self.ds1._array[slicing] = 99
self.ds1.setDirty( slicing )
# Navigate back down to the third z-slice
self.pump.syncedSliceSources.through = [0,2,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.waitForTiles()
# Even though the data was out-of-view when it was
# changed, it should still have new values. If dirtiness
# wasn't propagated correctly, the cache's old values will
# be used. (For example, this fails if you comment out the
# call to setDirty, above.)
# Shrink accessed rect by 1 pixel on each side (Otherwise,
# tiling overlap_draw causes getTiles() to return
# surrounding tiles that we haven't actually touched in
# this test)
tiles = tp.getTiles(QRectF(101,101,198,198))
for tile in tiles:
aimg = byte_view(tile.qimg)
# Use any() because the tile borders may not be
# perfectly aligned with the data we changed.
self.assertTrue(np.any(aimg[:,:,0:3] == 99))
class DirtyPropagationTest( ut.TestCase ):
def setUp( self ):
dataShape = (1, 900, 400, 10, 1) # t,x,y,z,c
data = np.indices(dataShape)[3] # Data is labeled according to z-index
self.ds1 = ArraySource( data )
self.CONSTANT = 13
self.ds2 = ConstantSource( self.CONSTANT )
self.layer1 = GrayscaleLayer( self.ds1 )
self.layer1.visible = True
self.layer1.opacity = 1.0
self.layer2 = GrayscaleLayer( self.ds2 )
self.lsm = LayerStackModel()
self.pump = ImagePump( self.lsm, SliceProjection() )
def testEverythingDirtyPropagation( self ):
self.lsm.append(self.layer2)
tiling = Tiling((900,400), blockSize=100)
tp = TileProvider(tiling, self.pump.stackedImageSources)
try:
tp.requestRefresh(QRectF(100,100,200,200))
tp.join()
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == self.CONSTANT))
self.assertTrue(np.all(aimg[:,:,3] == 255))
NEW_CONSTANT = self.CONSTANT+1
self.ds2.constant = NEW_CONSTANT
tp.requestRefresh(QRectF(100,100,200,200))
tp.join()
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == NEW_CONSTANT))
self.assertTrue(np.all(aimg[:,:,3] == 255))
finally:
tp.notifyThreadsToStop()
tp.joinThreads()
def testOutOfViewDirtyPropagation( self ):
self.lsm.append(self.layer1)
tiling = Tiling((900,400), blockSize=100)
tp = TileProvider(tiling, self.pump.stackedImageSources)
try:
# Navigate down to the second z-slice
self.pump.syncedSliceSources.through = [0,1,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.join()
# Sanity check: Do we see the right data on the second slice? (should be all 1s)
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == 1))
self.assertTrue(np.all(aimg[:,:,3] == 255))
# Navigate down to the third z-slice
self.pump.syncedSliceSources.through = [0,2,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.join()
# Sanity check: Do we see the right data on the third slice?(should be all 2s)
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == 2))
self.assertTrue(np.all(aimg[:,:,3] == 255))
# Navigate back up to the second z-slice
self.pump.syncedSliceSources.through = [0,1,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.join()
for tile in tiles:
aimg = byte_view(tile.qimg)
self.assertTrue(np.all(aimg[:,:,0:3] == 1))
self.assertTrue(np.all(aimg[:,:,3] == 255))
# Change some of the data in the (out-of-view) third z-slice
slicing = (slice(None), slice(100,300), slice(100,300), slice(2,3), slice(None))
slicing = tuple(slicing)
self.ds1._array[slicing] = 99
self.ds1.setDirty( slicing )
# Navigate back down to the third z-slice
self.pump.syncedSliceSources.through = [0,2,0]
tp.requestRefresh(QRectF(100,100,200,200))
tp.join()
# Even though the data was out-of-view when it was changed, it should still have new values.
# If dirtiness wasn't propagated correctly, the cache's old values will be used.
# (For example, this fails if you comment out the call to setDirty, above.)
tiles = tp.getTiles(QRectF(100,100,200,200))
for tile in tiles:
aimg = byte_view(tile.qimg)
# Use any() because the tile borders may not be perfectly aligned with the data we changed.
self.assertTrue(np.any(aimg[:,:,0:3] == 99))
finally:
tp.notifyThreadsToStop()
tp.joinThreads()
def setupLayers(self):
logger.debug("setupLayers")
layers = []
def onButtonsEnabled(slot, roi):
currObj = self.topLevelOperatorView.CurrentObjectName.value
hasSeg = self.topLevelOperatorView.HasSegmentation.value
self.labelingDrawerUi.currentObjectLabel.setText(currObj)
self.labelingDrawerUi.save.setEnabled(hasSeg)
self.topLevelOperatorView.CurrentObjectName.notifyDirty(
onButtonsEnabled)
self.topLevelOperatorView.HasSegmentation.notifyDirty(onButtonsEnabled)
self.topLevelOperatorView.opLabelArray.NonzeroBlocks.notifyDirty(
onButtonsEnabled)
# Labels
labellayer, labelsrc = self.createLabelLayer(direct=True)
if labellayer is not None:
labellayer._allowToggleVisible = False
layers.append(labellayer)
# Tell the editor where to draw label data
self.editor.setLabelSink(labelsrc)
#uncertainty
#if self._showUncertaintyLayer:
# uncert = self.topLevelOperatorView.Uncertainty
# if uncert.ready():
# colortable = []
# for i in range(256-len(colortable)):
# r,g,b,a = i,0,0,i
# colortable.append(QColor(r,g,b,a).rgba())
# layer = ColortableLayer(LazyflowSource(uncert), colortable, direct=True)
# layer.name = "Uncertainty"
# layer.visible = True
# layer.opacity = 0.3
# layers.append(layer)
#segmentation
seg = self.topLevelOperatorView.Segmentation
#seg = self.topLevelOperatorView.MST.value.segmentation
#temp = self._done_lut[self.MST.value.supervoxelUint32[sl[1:4]]]
if seg.ready():
#source = RelabelingArraySource(seg)
#source.setRelabeling(numpy.arange(256, dtype=numpy.uint8))
# assign to the object label color, 0 is transparent, 1 is background
colortable = [
QColor(0, 0, 0, 0).rgba(),
QColor(0, 0, 0, 0).rgba(), labellayer._colorTable[2]
]
for i in range(256 - len(colortable)):
r, g, b = numpy.random.randint(0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
layer = ColortableLayer(LazyflowSource(seg),
colortable,
direct=True)
layer.name = "Segmentation"
layer.setToolTip("This layer displays the <i>current</i> segmentation. Simply add foreground and background " \
"labels, then press <i>Segment</i>.")
layer.visible = True
layer.opacity = 0.3
layers.append(layer)
#done
doneSeg = self.topLevelOperatorView.DoneSegmentation
if doneSeg.ready():
#FIXME: if the user segments more than 255 objects, those with indices that divide by 255 will be shown as transparent
#both here and in the _doneSegmentationColortable
colortable = 254 * [QColor(230, 25, 75).rgba()]
colortable.insert(0, QColor(0, 0, 0, 0).rgba())
#have to use lazyflow because it provides dirty signals
layer = ColortableLayer(LazyflowSource(doneSeg),
colortable,
direct=True)
layer.name = "Completed segments (unicolor)"
layer.setToolTip("In order to keep track of which objects you have already completed, this layer " \
"shows <b>all completed object</b> in one color (<b>blue</b>). " \
"The reason for only one color is that for finding out which " \
"objects to label next, the identity of already completed objects is unimportant " \
"and destracting.")
layer.visible = False
layer.opacity = 0.5
layers.append(layer)
layer = ColortableLayer(LazyflowSource(doneSeg),
self._doneSegmentationColortable,
direct=True)
layer.name = "Completed segments (one color per object)"
layer.setToolTip("<html>In order to keep track of which objects you have already completed, this layer " \
"shows <b>all completed object</b>, each with a random color.</html>")
layer.visible = False
layer.opacity = 0.5
layer.colortableIsRandom = True
self._doneSegmentationLayer = layer
layers.append(layer)
#supervoxel
sv = self.topLevelOperatorView.Supervoxels
if sv.ready():
colortable = []
for i in range(256):
r, g, b = numpy.random.randint(0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
layer = ColortableLayer(LazyflowSource(sv),
colortable,
direct=True)
layer.name = "Supervoxels"
layer.setToolTip("<html>This layer shows the partitioning of the input image into <b>supervoxels</b>. The carving " \
"algorithm uses these tiny puzzle-piceces to piece together the segmentation of an " \
"object. Sometimes, supervoxels are too large and straddle two distinct objects " \
"(undersegmentation). In this case, it will be impossible to achieve the desired " \
"segmentation. This layer helps you to understand these cases.</html>")
layer.visible = False
layer.colortableIsRandom = True
layer.opacity = 0.5
layers.append(layer)
# Visual overlay (just for easier labeling)
overlaySlot = self.topLevelOperatorView.OverlayData
if overlaySlot.ready():
overlay5D = self.topLevelOperatorView.OverlayData.value
layer = GrayscaleLayer(ArraySource(overlay5D), direct=True)
layer.visible = True
layer.name = 'Overlay'
layer.opacity = 1.0
# if the flag window_leveling is set the contrast
# of the layer is adjustable
layer.window_leveling = True
self.labelingDrawerUi.thresToolButton.show()
layers.append(layer)
del layer
inputSlot = self.topLevelOperatorView.InputData
if inputSlot.ready():
layer = GrayscaleLayer(LazyflowSource(inputSlot), direct=True)
layer.name = "Input Data"
layer.setToolTip(
"<html>The data originally loaded into ilastik (unprocessed).</html>"
)
#layer.visible = not rawSlot.ready()
layer.visible = True
layer.opacity = 1.0
# Window leveling is already active on the Overlay,
# but if no overlay was provided, then activate window_leveling on the raw data instead.
if not overlaySlot.ready():
# if the flag window_leveling is set the contrast
# of the layer is adjustable
layer.window_leveling = True
self.labelingDrawerUi.thresToolButton.show()
layers.append(layer)
del layer
filteredSlot = self.topLevelOperatorView.FilteredInputData
if filteredSlot.ready():
layer = GrayscaleLayer(LazyflowSource(filteredSlot))
layer.name = "Filtered Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
return layers
def setupLayers(self):
layers = []
op = self.topLevelOperatorView
ravelerLabelsSlot = op.RavelerLabels
if ravelerLabelsSlot.ready():
colortable = []
for _ in range(256):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
ravelerLabelLayer = ColortableLayer(LazyflowSource(ravelerLabelsSlot), colortable, direct=True)
ravelerLabelLayer.name = "Raveler Labels"
ravelerLabelLayer.visible = False
ravelerLabelLayer.opacity = 0.4
layers.append(ravelerLabelLayer)
def addFragmentSegmentationLayers(mslot, name):
if mslot.ready():
for index, slot in enumerate(mslot):
if slot.ready():
raveler_label = slot.meta.selected_label
colortable = map(QColor.rgba, self._fragmentColors)
fragSegLayer = ColortableLayer(LazyflowSource(slot), colortable, direct=True)
fragSegLayer.name = "{} #{} ({})".format( name, index, raveler_label )
fragSegLayer.visible = False
fragSegLayer.opacity = 1.0
layers.append(fragSegLayer)
addFragmentSegmentationLayers( op.FragmentedBodies, "Saved Fragments" )
addFragmentSegmentationLayers( op.RelabeledFragments, "Relabeled Fragments" )
addFragmentSegmentationLayers( op.FilteredFragmentedBodies, "CC-Filtered Fragments" )
addFragmentSegmentationLayers( op.WatershedFilledBodies, "Watershed-filled Fragments" )
mslot = op.EditedRavelerBodies
for index, slot in enumerate(mslot):
if slot.ready():
raveler_label = slot.meta.selected_label
# 0=Black, 1=Transparent
colortable = [QColor(0, 0, 0).rgba(), QColor(0, 0, 0, 0).rgba()]
bodyMaskLayer = ColortableLayer(LazyflowSource(slot), colortable, direct=True)
bodyMaskLayer.name = "Raveler Body Mask #{} ({})".format( index, raveler_label )
bodyMaskLayer.visible = False
bodyMaskLayer.opacity = 1.0
layers.append(bodyMaskLayer)
finalSegSlot = op.FinalSegmentation
if finalSegSlot.ready():
colortable = []
for _ in range(256):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
finalLayer = ColortableLayer(LazyflowSource(finalSegSlot), colortable, direct=True)
finalLayer.name = "Final Segmentation"
finalLayer.visible = False
finalLayer.opacity = 0.4
layers.append(finalLayer)
inputSlot = op.InputData
if inputSlot.ready():
layer = GrayscaleLayer( LazyflowSource(inputSlot) )
layer.name = "WS Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
#raw data
rawSlot = self.topLevelOperatorView.RawData
rawLayer = None
if rawSlot.ready():
raw5D = self.topLevelOperatorView.RawData.value
rawLayer = GrayscaleLayer(ArraySource(raw5D), direct=True)
#rawLayer = GrayscaleLayer( LazyflowSource(rawSlot) )
rawLayer.name = "raw"
rawLayer.visible = True
rawLayer.opacity = 1.0
rawLayer.shortcutRegistration = ( "g", ShortcutManager.ActionInfo(
"Postprocessing",
"Raw Data to Top",
"Raw Data to Top",
partial(self._toggleRawDataPosition, rawLayer),
self.viewerControlWidget(),
rawLayer ) )
layers.append(rawLayer)
return layers
o4 = Layer([ConstantSource()])
o4.name = "Fancy Layer II"
o4.opacity = 0.95
model.append(o4)
o5 = Layer([ConstantSource()])
o5.name = "Fancy Layer III"
o5.opacity = 0.65
model.append(o5)
o6 = Layer([ConstantSource()])
o6.name = "Lazyflow Layer"
o6.opacity = 1
testVolume = numpy.random.rand(100, 100, 100, 3).astype("uint8")
source = [ArraySource(testVolume)]
o6._datasources = source
model.append(o6)
view = LayerWidget(None, model)
view.show()
view.updateGeometry()
w = QWidget()
lh = QHBoxLayout(w)
lh.addWidget(view)
up = QPushButton("Up")
down = QPushButton("Down")
delete = QPushButton("Delete")
add = QPushButton("Add")
def setupLayers(self):
layers = []
op = self.topLevelOperatorView
ravelerLabelsSlot = op.RavelerLabels
if ravelerLabelsSlot.ready():
colortable = []
for _ in range(256):
r, g, b = numpy.random.randint(0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
ravelerLabelLayer = ColortableLayer(
LazyflowSource(ravelerLabelsSlot), colortable, direct=True)
ravelerLabelLayer.name = "Raveler Labels"
ravelerLabelLayer.visible = False
ravelerLabelLayer.opacity = 0.4
layers.append(ravelerLabelLayer)
supervoxelsSlot = op.Supervoxels
if supervoxelsSlot.ready():
colortable = []
for i in range(256):
r, g, b = numpy.random.randint(0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
supervoxelsLayer = ColortableLayer(LazyflowSource(supervoxelsSlot),
colortable)
supervoxelsLayer.name = "Input Supervoxels"
supervoxelsLayer.visible = False
supervoxelsLayer.opacity = 1.0
layers.append(supervoxelsLayer)
def addFragmentSegmentationLayers(mslot, name):
if mslot.ready():
for index, slot in enumerate(mslot):
if slot.ready():
raveler_label = slot.meta.selected_label
colortable = []
for i in range(256):
r, g, b = numpy.random.randint(
0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
colortable[0] = QColor(0, 0, 0, 0).rgba()
fragSegLayer = ColortableLayer(LazyflowSource(slot),
colortable,
direct=True)
fragSegLayer.name = "{} #{} ({})".format(
name, index, raveler_label)
fragSegLayer.visible = False
fragSegLayer.opacity = 1.0
layers.append(fragSegLayer)
addFragmentSegmentationLayers(op.MaskedSupervoxels,
"Masked Supervoxels")
addFragmentSegmentationLayers(op.FilteredMaskedSupervoxels,
"Filtered Masked Supervoxels")
addFragmentSegmentationLayers(op.HoleFilledSupervoxels,
"Hole Filled Supervoxels")
addFragmentSegmentationLayers(op.RelabeledSupervoxels,
"Relabeled Supervoxels")
mslot = op.EditedRavelerBodies
for index, slot in enumerate(mslot):
if slot.ready():
raveler_label = slot.meta.selected_label
# 0=Black, 1=Transparent
colortable = [
QColor(0, 0, 0).rgba(),
QColor(0, 0, 0, 0).rgba()
]
bodyMaskLayer = ColortableLayer(LazyflowSource(slot),
colortable,
direct=True)
bodyMaskLayer.name = "Raveler Body Mask #{} ({})".format(
index, raveler_label)
bodyMaskLayer.visible = False
bodyMaskLayer.opacity = 1.0
layers.append(bodyMaskLayer)
finalSegSlot = op.FinalSupervoxels
if finalSegSlot.ready():
colortable = []
for _ in range(256):
r, g, b = numpy.random.randint(0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
finalLayer = ColortableLayer(LazyflowSource(finalSegSlot),
colortable)
finalLayer.name = "Final Supervoxels"
finalLayer.visible = False
finalLayer.opacity = 0.4
layers.append(finalLayer)
inputSlot = op.InputData
if inputSlot.ready():
layer = GrayscaleLayer(LazyflowSource(inputSlot))
layer.name = "WS Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
#raw data
rawSlot = self.topLevelOperatorView.RawData
if rawSlot.ready():
raw5D = self.topLevelOperatorView.RawData.value
layer = GrayscaleLayer(ArraySource(raw5D), direct=True)
#layer = GrayscaleLayer( LazyflowSource(rawSlot) )
layer.name = "raw"
layer.visible = True
layer.opacity = 1.0
layers.append(layer)
return layers
def setUp(self):
self.raw = np.random.randint(0, 100, (10, 3, 3, 128, 3))
self.a = ArraySource(self.raw)
self.ss = PlanarSliceSource(self.a, projectionAlongTZC)
from volumina.colortables import default16_new
from volumina.pixelpipeline.datasources import ArraySinkSource, ArraySource
from volumina.layer import ColortableLayer, GrayscaleLayer
from PyQt5.QtWidgets import QApplication
SHAPE = (1, 600, 800, 1, 1) # volumina expects 5d txyzc
data_arr = (255 * numpy.random.random(SHAPE)).astype(numpy.uint8)
label_arr = numpy.zeros(SHAPE, dtype=numpy.uint8)
##-----
app = QApplication(sys.argv)
v = Viewer()
data_src = ArraySource(data_arr)
data_layer = GrayscaleLayer(data_src)
data_layer.name = "Raw"
data_layer.numberOfChannels = 1
label_src = ArraySinkSource(label_arr)
label_layer = ColortableLayer(label_src,
colorTable=default16_new,
direct=False)
label_layer.name = "Labels"
label_layer.ref_object = None
assert SHAPE == label_arr.shape == data_arr.shape
v.dataShape = SHAPE
v.layerstack.append(data_layer)
def setupLayers( self, currentImageIndex ):
layers = []
def onButtonsEnabled(slot, roi):
currObj = self._carvingApplet.topLevelOperator.opCarving[currentImageIndex].CurrentObjectName.value
hasSeg = self._carvingApplet.topLevelOperator.opCarving[currentImageIndex].HasSegmentation.value
nzLB = self._carvingApplet.topLevelOperator.opLabeling.NonzeroLabelBlocks[currentImageIndex][:].wait()[0]
self.labelingDrawerUi.currentObjectLabel.setText("current object: %s" % currObj)
self.labelingDrawerUi.save.setEnabled(currObj != "" and hasSeg)
self.labelingDrawerUi.saveAs.setEnabled(currObj == "" and hasSeg)
#rethink this
#self.labelingDrawerUi.segment.setEnabled(len(nzLB) > 0)
#self.labelingDrawerUi.clear.setEnabled(len(nzLB) > 0)
self._carvingApplet.topLevelOperator.opCarving[currentImageIndex].CurrentObjectName.notifyDirty(onButtonsEnabled)
self._carvingApplet.topLevelOperator.opCarving[currentImageIndex].HasSegmentation.notifyDirty(onButtonsEnabled)
self._carvingApplet.topLevelOperator.opLabeling.NonzeroLabelBlocks[currentImageIndex].notifyDirty(onButtonsEnabled)
# Labels
labellayer, labelsrc = self.createLabelLayer(currentImageIndex, direct=True)
if labellayer is not None:
layers.append(labellayer)
# Tell the editor where to draw label data
self.editor.setLabelSink(labelsrc)
#segmentation
seg = self._carvingApplet.topLevelOperator.opCarving.Segmentation[currentImageIndex]
#seg = self._carvingApplet.topLevelOperator.opCarving[0]._mst.segmentation
#temp = self._done_lut[self._mst.regionVol[sl[1:4]]]
if seg.ready():
#source = RelabelingArraySource(seg)
#source.setRelabeling(numpy.arange(256, dtype=numpy.uint8))
colortable = [QColor(0,0,0,0).rgba(), QColor(0,0,0,0).rgba(), QColor(0,255,0).rgba()]
for i in range(256-len(colortable)):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
#layer = DirectColorTableLayer(seg, colortable, lazyflow=True)
layer = ColortableLayer(LazyflowSource(seg), colortable, direct=True)
layer.name = "segmentation"
layer.visible = True
layer.opacity = 0.3
layers.append(layer)
#done
done = self._carvingApplet.topLevelOperator.opCarving.DoneObjects[currentImageIndex]
if done.ready():
colortable = [QColor(0,0,0,0).rgba(), QColor(0,0,255).rgba()]
for i in range(254-len(colortable)):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
#have to use lazyflow because it provides dirty signals
#layer = DirectColorTableLayer(done, colortable, lazyflow=True)
layer = ColortableLayer(LazyflowSource(done), colortable, direct=True)
layer.name = "done"
layer.visible = False
layer.opacity = 0.5
layers.append(layer)
doneSeg = self._carvingApplet.topLevelOperator.opCarving.DoneSegmentation[currentImageIndex]
if doneSeg.ready():
layer = ColortableLayer(LazyflowSource(doneSeg), self._doneSegmentationColortable, direct=True)
layer.name = "done seg"
layer.visible = False
layer.opacity = 0.5
self._doneSegmentationLayer = layer
layers.append(layer)
#supervoxel
sv = self._carvingApplet.topLevelOperator.opCarving.Supervoxels[currentImageIndex]
if sv.ready():
for i in range(256):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
#layer = DirectColorTableLayer(sv, colortable, lazyflow=True)
layer = ColortableLayer(LazyflowSource(sv), colortable, direct=True)
layer.name = "supervoxels"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
#
# load additional layer: features / probability map
#
import h5py
f = h5py.File("pmap.h5")
pmap = f["data"].value
#
# here we load the actual raw data from an ArraySource rather than from a LazyflowSource for speed reasons
#
raw = self._carvingApplet.topLevelOperator.opCarving[0]._mst.raw
raw5D = numpy.zeros((1,)+raw.shape+(1,), dtype=raw.dtype)
raw5D[0,:,:,:,0] = raw[:,:,:]
#layer = DirectGrayscaleLayer(raw5D)
layer = GrayscaleLayer(ArraySource(raw5D), direct=True)
layer.name = "raw"
layer.visible = True
layer.opacity = 1.0
#layers.insert(1, layer)
layers.append(layer)
return layers
