def volumina_n_layer(data, labels = None):
app = QApplication(sys.argv)
import volumina
from volumina.api import Viewer
v = Viewer ()
v.title = " Volumina Demo "
v.showMaximized ()
for ind, d in enumerate(data):
layer_name = "layer_" + str(ind)
if labels is not None:
layer_name = labels[ind]
# get data type of the elements d, to determine
# if we use a grayscale overlay (float32) or a randomcolors overlay (uint) for labels
data_type = d.dtype
if data_type == np.float32 or data_type == np.float64:
v.addGrayscaleLayer(d , name = layer_name)
else:
v.addRandomColorsLayer(d.astype(np.uint32), name = layer_name)
app.exec_()
def volumina_flexible_layer(data, layer_types, labels=None):
assert len(layer_types) == len(data)
app = QApplication (sys.argv)
import volumina
from volumina.api import Viewer
v = Viewer ()
v.title = " Volumina Demo "
v.showMaximized ()
for i, d in enumerate(data):
layer_name = "layer_" + str(i)
if labels is not None:
layer_name = labels[i]
# get data type of the elements d, to determine
# if we use a grayscale overlay (float32) or a randomcolors overlay (uint) for labels
data_type = d.dtype
if layer_types[i] == 'Grayscale':
v.addGrayscaleLayer(d , name = layer_name)
elif layer_types[i] == 'RandomColors':
v.addRandomColorsLayer(d.astype(np.uint32), name=layer_name)
elif layer_types[i] == 'Red':
v.addAlphaModulatedLayer(d , name=layer_name, tintColor=QColor(255,0,0))
elif layer_types[i] == 'Green':
v.addAlphaModulatedLayer(d , name=layer_name, tintColor=QColor(0,255,0))
elif layer_types[i] == 'Blue':
v.addAlphaModulatedLayer(d , name=layer_name, tintColor=QColor(0,0,255))
else:
raise KeyError("Invalid Layer Type, %s!" % layer_types[i])
app.exec_()
def volumina_single_layer(data): app = QApplication (sys.argv) from volumina.api import Viewer v = Viewer () v.title = " Volumina Demo " v.showMaximized () v.addGrayscaleLayer (data , name =" raw data ") app . exec_ ()
def addHocViewer(grayData=None, segData=None, title="viewer", visu=True):
if visu:
app = QApp.Instance().app
v = Viewer()
if grayData is not None:
for name in grayData.keys():
data = grayData[name]
if hasVigra:
if isinstance(data, vigra.arraytypes.VigraArray):
v.addGrayscaleLayer(data.view(numpy.ndarray), name=name)
else:
v.addGrayscaleLayer(data, name=name)
else:
v.addGrayscaleLayer(data, name=name)
if segData is not None:
for name in segData.keys():
data = segData[name]
if hasVigra:
if isinstance(data, vigra.arraytypes.VigraArray):
v.addColorTableLayer(data.view(numpy.ndarray), name=name)
else:
v.addColorTableLayer(data, name=name)
else:
v.addGrayscaleLayer(data, name=name)
v.setWindowTitle(title)
v.showMaximized()
app.exec_()
def addHocViewer(grayData=None, segData=None, title="viewer", visu=True):
if visu:
app = QApp.Instance().app
v = Viewer()
if grayData is not None:
for name in grayData.keys():
data = grayData[name]
if _hasVigra:
if isinstance(data, vigra.arraytypes.VigraArray):
v.addGrayscaleLayer(data.view(numpy.ndarray),
name=name)
else:
v.addGrayscaleLayer(data, name=name)
else:
v.addGrayscaleLayer(data, name=name)
if segData is not None:
for name in segData.keys():
data = segData[name]
if _hasVigra:
if isinstance(data, vigra.arraytypes.VigraArray):
v.addColorTableLayer(data.view(numpy.ndarray),
name=name)
else:
v.addColorTableLayer(data, name=name)
else:
v.addGrayscaleLayer(data, name=name)
v.setWindowTitle(title)
v.showMaximized()
app.exec_()
def streaming_n_layer(files, keys, labels=None, block_shape=[100, 100, 100]):
from volumina.api import Viewer
from volumina.pixelpipeline.datasources import LazyflowSource
from lazyflow.graph import Graph
from lazyflow.operators.ioOperators.opStreamingHdf5Reader import OpStreamingHdf5Reader
from lazyflow.operators import OpCompressedCache
app = QApplication(sys.argv)
v = Viewer()
graph = Graph()
def mkH5source(fname, gname):
h5file = h5py.File(fname)
dtype = h5file[gname].dtype
source = OpStreamingHdf5Reader(graph=graph)
source.Hdf5File.setValue(h5file)
source.InternalPath.setValue(gname)
op = OpCompressedCache(parent=None, graph=graph)
op.BlockShape.setValue(block_shape)
op.Input.connect(source.OutputImage)
return op.Output, dtype
#rawSource = mkH5source(data[0], keys[0])
#v.addGrayscaleLayer(rawSource, name = 'raw')
for i, f in enumerate(files):
if labels is not None:
layer_name = labels[i]
else:
layer_name = "layer_%i" % (i)
source, dtype = mkH5source(f, keys[i])
if np.dtype(dtype) in (np.dtype('uint8'), np.dtype('float32'),
np.dtype('float64')):
v.addGrayscaleLayer(source, name=layer_name)
else:
v.addRandomColorsLayer(source, name=layer_name)
v.setWindowTitle("Streaming Viewer")
v.showNormal()
app.exec_()
def view(dset):
from volumina.api import Viewer
from PyQt4.QtGui import QApplication
app = QApplication([])
v = Viewer()
if isinstance(dset, str):
f = h5py.File(dset, 'r')
d = f["volume/data"].value
f.close()
v.setWindowTitle(dset)
v.addGrayscaleLayer(d, name="raw")
elif isinstance(dset, numpy.ndarray):
v.addGrayscaleLayer(dset, name="raw")
else:
raise RuntimeError("%r" % dset)
v.showMaximized()
app.exec_()
def view_HDF5(inpaths):
app = QApplication(sys.argv)
v = Viewer()
for inpath in inpaths:
if "n_1_" in inpath:
prefix = "n_1_"
elif "n_2_" in inpath:
prefix = "n_2_"
else:
prefix = ""
if "h5" in inpath:
#data = vigra.readHDF5(inpath, "data")
print
print "inpath", inpath
data = read_h5(inpath)
file = inpath.split("/")[-1]
name = prefix + file.split(".")[0]
if "prob_files" in inpath or "seeds" in inpath or "trimap" in inpath:
data = binarize_predict(data)
file = inpath.split("/")[-2] + "_" + inpath.split("/")[-1]
name = prefix + file.split(".")[0]
print "type", type(data)
if "test_data" in inpath or "prob_files" in inpath or "seeds" in inpath or "trimap" in inpath:
v.addGrayscaleLayer(data, name=name)
# if "trimaps" in inpath or "dense" in inpath or "sup_maps" in inpath or "seg_maps" in inpath:
# v.addRandomColorsLayer(255*data, name=name+"_color")
else:
v.addRandomColorsLayer(255*data, name=name+"_color")
if "png" in inpath:
img = vigra.impex.readImage(inpath)
img = np.asarray(img)
file = inpath.split("/")[-1]
name = file.split(".")[0]
print "type",type(img)
v.addGrayscaleLayer(img, name=name)
#v.addRandomColorsLayer(255*img, name=name+"color")
v.showMaximized()
app.exec_()
def volumina_double_layer(data, overlay): # get data type of the elements of overlay, to determine # if we use a grayscale overlay (float32) or a randomcolors overlay (uint) for labels mask = [] for i in range( len(overlay.shape) ): mask.append(0) mask = tuple(mask) data_type = type(overlay[mask]) app = QApplication (sys.argv) from volumina.api import Viewer v = Viewer () v.title = " Volumina Demo " v.showMaximized () v.addGrayscaleLayer(data , name = " raw data ") if data_type == np.float32: v.addGrayscaleLayer(overlay , name = " overlay ") else: v.addRandomColorsLayer(overlay, name = " overlay ") app . exec_ ()
tvbai20 = vigra.readHDF5(ptvbai20, 'data')
tvc5 = vigra.readHDF5(ptvc5, 'data')
m1 = vigra.readHDF5(pm1, 'data')
m2 = vigra.readHDF5(pm2, 'data')
m3 = vigra.readHDF5(pm3, 'data')
g1 = vigra.readHDF5(pg1, 'data')
gf5 = vigra.readHDF5(pgf5, 'data')
gm3 = vigra.readHDF5(pgm3, 'data')
diff = gf5-data
app = QApplication(sys.argv)
v = Viewer()
print "add layers"
v.addGrayscaleLayer(data, name="raw")
v.addGrayscaleLayer(nlm, name="non local mean")
v.addGrayscaleLayer(nlm2, name="non local mean (on presmoothed)")
v.addGrayscaleLayer(tvbi2, name="tv bregman 2.0 isotropic")
v.addGrayscaleLayer(tvbai20, name="tv bregman 20.0 anisotropic")
v.addGrayscaleLayer(tvc5, name="tv Chambolle 2.0")
v.addGrayscaleLayer(m1, name="median 1")
v.addGrayscaleLayer(m2, name="median 2")
v.addGrayscaleLayer(m3, name="median 3")
v.addGrayscaleLayer(g1.view(numpy.ndarray), name="gauss 1")
v.addGrayscaleLayer(gf5.view(numpy.ndarray), name="gauss guided filter 5")
v.addGrayscaleLayer(gm3.view(numpy.ndarray), name="median guided filter 3")
v.setWindowTitle("smoothings")
v.showMaximized()
app.exec_()
item1.setPath(path1)
# Create images
back = (numpy.ones((100, 200, 300)) * 0).astype(numpy.uint8)
back[0:60, 0:60, 0:60] = 255
back[40:80, 40:80, 40:80] = 120
back[40:100, 40:100, 0:40] = 80
back[0:45, 50:100, 0:100] = 200
ol = (numpy.zeros((100, 200, 300))).astype(numpy.uint8)
# ol[0:99, 0:99, 0:99] = 120
# ol[0:99, 120:140, 0:99] = 255
ol[:] = back
back.shape = (1,)+back.shape+(1,)
ol.shape = (1,)+ol.shape+(1,)
# Add layers
l1 = v.addGrayscaleLayer(back, name="back")
l1.visible = True
l2 = v.addColorTableLayer(ol, name="overlay")
# Add the path to the graphics scene
# v.editor.imageScenes[0].addItem(item1)
# v.editor.imageScenes[1].addItem(item1)
v.editor.imageScenes[2].addItem(item1)
v.setWindowTitle("Clickable Border Viewer")
v.show()
app.exec_()
f = pylab.figure()
for n, arr in enumerate(imgs):
arr = arr.squeeze()
f.add_subplot(1, len(imgs), n)
pylab.imshow(arr.swapaxes(0, 1))
pylab.show()
else:
if False:
pmapSmooth2 = dn.diffusion3d(p.copy() * 255.0, param)
vigra.impex.writeHDF5(pmapSmooth2, "sub.h5", "dc_1.00_2.50")
if True:
pmapSmooth1 = vigra.impex.readHDF5("sub.h5", "dc_0.75_2")
pmapSmooth2 = vigra.impex.readHDF5("sub.h5", "dc_1.00_2.50")
app = QApplication(sys.argv)
v = Viewer()
v.addGrayscaleLayer(pmapSmooth1, name="pmapSmooth_0.75_2.00")
v.addGrayscaleLayer(pmapSmooth2, name="pmapSmooth_1.00_2.50")
v.addGrayscaleLayer(p, name="pmap")
v.addGrayscaleLayer(d, name="raw")
#v.addGrayscaleLayer(bf.grayscaleErosion(data,sigma=2.5), name="e")
#v.addGrayscaleLayer(dt, name="dt")
v.setWindowTitle("data")
v.showMaximized()
app.exec_()
sys.exit()
import numpy
import skneuro
import vigra
from volumina.api import Viewer
from PyQt4.QtGui import QApplication
import skneuro.denoising as dn
p = '/home/tbeier/Desktop/blocks/data_sub_3.h5'
data = vigra.impex.readHDF5(p, 'data')[0:200, :,
0:200].astype('uint8').squeeze()
app = QApplication(sys.argv)
v = Viewer()
v.addGrayscaleLayer(data, name="raw")
with vigra.Timer("get ranks 8*2"):
a = dn.ballRankOrder(data,
radius=12,
takeNth=2,
ranks=(0.01, 0.1, 0.5, 0.9, 0.99),
useHistogram=True,
minVal=0.0,
maxVal=255.0,
nBins=256)
v.addGrayscaleLayer(a, name="0.5 8* 2")
v.setWindowTitle("data")
v.showMaximized()
app.exec_()
##-----
app = QApplication(sys.argv)
v = Viewer()
graph = Graph()
def mkH5source(fname, gname):
h5file = h5py.File(fname)
source = OpStreamingHdf5Reader(graph=graph)
source.Hdf5File.setValue(h5file)
source.InternalPath.setValue(gname)
op = OpCompressedCache(parent=None, graph=graph)
op.BlockShape.setValue([100, 100, 100])
op.Input.connect(source.OutputImage)
return op.Output
rawSource = mkH5source("raw.h5", "raw")
segSource = mkH5source("seg.h5", "seg")
v.addGrayscaleLayer(rawSource, name="raw")
v.addColorTableLayer(segSource, name="seg")
v.setWindowTitle("streaming viewer")
v.showMaximized()
app.exec_()
labels = vigra.readHDF5(lPath, 'data')
labelsS = vigra.readHDF5(lsPath, 'data')
#labelsSS = vigra.readHDF5(lssPath, 'data')
labelsPS = vigra.readHDF5("/mnt/CLAWS1/tbeier/data/stack_with_holes/lps.h5", 'data')
print ew.shape
print "datashape",data.shape
print "resshape",smoothedT.shape
app = QApplication(sys.argv)
v = Viewer()
v.addGrayscaleLayer(data, name="raw")
v.addGrayscaleLayer(smoothedT, name="smoothedT")
v.addGrayscaleLayer(ew, name="hessian ew")
v.addGrayscaleLayer(ews, name="hessian ews")
v.addGrayscaleLayer(ewss, name="hessian ewss")
v.addGrayscaleLayer(pEws, name="hessian p80ews")
#v.addGrayscaleLayer(dd, name="diff ews")
v.addColorTableLayer(labels, name="labels")
v.addColorTableLayer(labelsS, name="labelsS")
#v.addColorTableLayer(labelsSS, name="labelsSS")
v.addColorTableLayer(labelsPS, name="labelsPS")
v.setWindowTitle("stack with holes")
v.showMaximized()
app.exec_()
##-----
app = QApplication(sys.argv)
v = Viewer()
graph = Graph()
def mkH5source(fname, gname):
h5file = h5py.File(fname)
source = OpStreamingH5N5Reader(graph=graph)
source.H5N5File.setValue(h5file)
source.InternalPath.setValue(gname)
op = OpCompressedCache(parent=None, graph=graph)
op.BlockShape.setValue([100, 100, 100])
op.Input.connect(source.OutputImage)
return op.Output
rawSource = mkH5source("raw.h5", "raw")
segSource = mkH5source("seg.h5", "seg")
v.addGrayscaleLayer(rawSource, name="raw")
v.addColorTableLayer(segSource, name="seg")
v.setWindowTitle("streaming viewer")
v.showMaximized()
app.exec_()
# This program is free software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software Foundation, # Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # # Copyright 2011-2014, the ilastik developers from volumina.api import Viewer from PyQt4.QtGui import QApplication import numpy app = QApplication([]) v = Viewer() a = (255*numpy.random.random((1, 50,60,70,10) )).astype(numpy.uint8) v.addGrayscaleLayer(a, name="raw") v.showMaximized() app.exec_()
fname = args[0][:x+3]
gname = args[0][x+4:]
#load data
try:
f = h5py.File(fname, 'r')
except:
raise RuntimeError("Could not load '%s'" % fname)
raw = f[gname].value.squeeze()
assert raw.ndim == 3
assert raw.dtype == numpy.uint8
f.close()
app = QApplication([])
v = Viewer()
direct = True
raw.shape = (1,)+raw.shape+(1,)
l1 = v.addGrayscaleLayer(raw, name="raw", direct=True)
#######################################################################################################################
skeletons = Skeletons()
e = SkeletonInterpreter(v.editor, skeletons, v)
v.editor.eventSwitch.interpreter = e
v.show()
app.exec_()
from volumina.api import Viewer
from PyQt4.QtGui import QApplication
import skneuro.denoising as dn
p = '/home/tbeier/Desktop/blocks/data_sub_3.h5'
data = vigra.impex.readHDF5(p,'data')[0:200,:,0:200].astype('uint8').squeeze()
app = QApplication(sys.argv)
v = Viewer()
v.addGrayscaleLayer(data, name="raw")
with vigra.Timer("get ranks 8*2"):
a = dn.ballRankOrder(data,
radius=12,
takeNth=2,
ranks=(0.01,0.1, 0.5, 0.9, 0.99),
useHistogram=True,
minVal=0.0,
maxVal=255.0,
nBins=256)
v.addGrayscaleLayer(a, name="0.5 8* 2")
item1 = ClickablePathItem(v.editor.imageScenes[2], clickable_width=11)
item1.set_path_from_coordinates(c_x, c_y)
# Create images
back = (numpy.ones((100, 200, 300)) * 0).astype(numpy.uint8)
back[0:60, 0:60, 0:60] = 255
back[40:80, 40:80, 40:80] = 120
back[40:100, 40:100, 0:40] = 80
back[0:45, 50:100, 0:100] = 200
ol = (numpy.zeros((100, 200, 300))).astype(numpy.uint8)
# ol[0:99, 0:99, 0:99] = 120
# ol[0:99, 120:140, 0:99] = 255
ol[:] = back
back.shape = (1,)+back.shape+(1,)
ol.shape = (1,)+ol.shape+(1,)
# Add layers
l1 = v.addGrayscaleLayer(back, name="back")
l1.visible = True
l2 = v.addColorTableLayer(ol, name="overlay")
# Add the path to the graphics scene
# v.editor.imageScenes[0].addItem(item1)
# v.editor.imageScenes[1].addItem(item1)
# v.editor.imageScenes[2].addItem(item1)
v.setWindowTitle("Clickable Border Viewer")
v.show()
app.exec_()
sigma = float(sigma)
return (-1.0 / sigma) * gauss(x, mean, sigma) + ((
(-x + mean) / sigma)**2) * gauss(x, mean, sigma)
for x in range(patchSize[0]):
for y in range(patchSize[1]):
for z in range(patchSize[2]):
dgx = gauss2d(x, radius[0], sigma[0])
gy = gauss(y, radius[1], sigma[1])
gz = gauss(z, radius[2], sigma[2])
kernel[x, y, z] = dgx * gy * gz
return kernel
kernel = makeFilter(radius, sigma)
kernel /= numpy.sum(kernel)
kernel -= kernel.min()
kernel /= kernel.max()
app = QApplication(sys.argv)
v = Viewer()
v.addGrayscaleLayer(kernel, name="raw")
v.setWindowTitle("kernel")
v.showMaximized()
app.exec_()
print "seg "
labels = vigra.readHDF5(lPath, 'data')
labelsS = vigra.readHDF5(lsPath, 'data')
#labelsSS = vigra.readHDF5(lssPath, 'data')
labelsPS = vigra.readHDF5(
"/mnt/CLAWS1/tbeier/data/stack_with_holes/lps.h5", 'data')
print ew.shape
print "datashape", data.shape
print "resshape", smoothedT.shape
app = QApplication(sys.argv)
v = Viewer()
v.addGrayscaleLayer(data, name="raw")
v.addGrayscaleLayer(smoothedT, name="smoothedT")
v.addGrayscaleLayer(ew, name="hessian ew")
v.addGrayscaleLayer(ews, name="hessian ews")
v.addGrayscaleLayer(ewss, name="hessian ewss")
v.addGrayscaleLayer(pEws, name="hessian p80ews")
#v.addGrayscaleLayer(dd, name="diff ews")
v.addColorTableLayer(labels, name="labels")
v.addColorTableLayer(labelsS, name="labelsS")
#v.addColorTableLayer(labelsSS, name="labelsSS")
v.addColorTableLayer(labelsPS, name="labelsPS")
v.setWindowTitle("stack with holes")
v.showMaximized()
app.exec_()
from volumina.api import Viewer from PyQt4.QtGui import QApplication import numpy app = QApplication([]) v = Viewer() a = (255*numpy.random.random((1, 50,60,70,10) )).astype(numpy.uint8) v.addGrayscaleLayer(a, name="raw") v.showMaximized() app.exec_()
f.add_subplot(1, len(imgs), n)
pylab.imshow(arr.swapaxes(0,1))
pylab.show()
else:
if False:
pmapSmooth2 = dn.diffusion3d(p.copy()*255.0, param)
vigra.impex.writeHDF5(pmapSmooth2, "sub.h5", "dc_1.00_2.50")
if True :
pmapSmooth1 = vigra.impex.readHDF5("sub.h5", "dc_0.75_2")
pmapSmooth2 = vigra.impex.readHDF5("sub.h5", "dc_1.00_2.50")
app = QApplication(sys.argv)
v = Viewer()
v.addGrayscaleLayer(pmapSmooth1, name="pmapSmooth_0.75_2.00")
v.addGrayscaleLayer(pmapSmooth2, name="pmapSmooth_1.00_2.50")
v.addGrayscaleLayer(p, name="pmap")
v.addGrayscaleLayer(d, name="raw")
#v.addGrayscaleLayer(bf.grayscaleErosion(data,sigma=2.5), name="e")
#v.addGrayscaleLayer(dt, name="dt")
v.setWindowTitle("data")
v.showMaximized()
app.exec_()
sys.exit()
gname = args[0][x + 4:]
# load data
f = h5py.File(fname, "r")
raw = f[gname].value
assert raw.ndim == 3
assert raw.dtype == numpy.uint8
f.close()
app = QApplication([])
v = Viewer()
direct = True
raw.shape = (1, ) + raw.shape + (1, )
l1 = v.addGrayscaleLayer(raw, name="raw", direct=True)
l1.visible = direct
colortable = [
QColor(0, 0, 0, 0).rgba(),
QColor(255, 0, 0).rgba(),
QColor(0, 255, 0).rgba(),
QColor(0, 0, 255).rgba()
]
s = ((raw // 64)).astype(numpy.uint8)
def onClick(layer, pos5D, pos):
print("here i am: ", pos5D, s[pos5D])
from volumina.api import Viewer
from volumina.pixelpipeline.datasources import LazyflowSource
import sys
from lazyflow.graph import Graph
from lazyflow.operators.ioOperators.opStreamingHdf5Reader import OpStreamingHdf5Reader
from lazyflow.operators import OpCompressedCache
from PyQt4.QtGui import QApplication
app = QApplication(sys.argv)
v = Viewer()
#raw layer
v.addGrayscaleLayer(raw, name="test")
#predict layer
#predict = np.array(predict[:,:,:,0,0]) * 255
#v.addColorTableLayer(predict.astype(np.float32), name="prediction")
v.addGrayscaleLayer(predict.astype(np.float32), name="org")
#trimap layer
tm = np.array(tm)*255
print np.unique(tm)
#v.addColorTableLayer(tm.astype(np.float32), name="trimap")
#v.addGrayscaleLayer(tm.astype(np.float32), name="tm")
#gt layer
#v.addGrayscaleLayer(gt.astype(np.float32), name="groundtruth")
