def main( parsed_args, workflow_cmdline_args=[] ):
this_path = os.path.dirname(__file__)
ilastik_dir = os.path.abspath(os.path.join(this_path, "..%s.." % os.path.sep))
# If necessary, redirect stdout BEFORE logging is initialized
_redirect_output( parsed_args )
_init_logging( parsed_args ) # Initialize logging before anything else
_init_configfile( parsed_args )
_clean_paths( parsed_args, ilastik_dir )
_update_debug_mode( parsed_args )
_init_threading_monkeypatch()
_validate_arg_compatibility( parsed_args )
# Extra initialization functions.
# Called during app startup.
init_funcs = []
lazyflow_config_fn = _prepare_lazyflow_config( parsed_args )
if lazyflow_config_fn:
init_funcs.append( lazyflow_config_fn )
load_fn = _prepare_auto_open_project( parsed_args )
if load_fn:
init_funcs.append( load_fn )
create_fn = _prepare_auto_create_new_project( parsed_args )
if create_fn:
init_funcs.append( create_fn )
_enable_faulthandler()
_init_excepthooks( parsed_args )
eventcapture_mode, playback_args = _prepare_test_recording_and_playback( parsed_args )
if ilastik_config.getboolean("ilastik", "debug"):
message = 'Starting ilastik in debug mode from "%s".' % ilastik_dir
logger.info(message)
print message # always print the startup message
else:
message = 'Starting ilastik from "%s".' % ilastik_dir
logger.info(message)
print message # always print the startup message
# Headless launch
if parsed_args.headless:
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell( workflow_cmdline_args )
for f in init_funcs:
f(shell)
return shell
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, eventcapture_mode, playback_args, *init_funcs))
def main( parsed_args, workflow_cmdline_args=[] ):
_update_debug_mode( parsed_args )
_init_logging( parsed_args ) # Initialize logging before anything else
_init_threading_monkeypatch()
_validate_arg_compatibility( parsed_args )
# Extra initialization functions.
# Called during app startup.
init_funcs = []
load_fn = _prepare_auto_open_project( parsed_args )
if load_fn:
init_funcs.append( load_fn )
create_fn = _prepare_auto_create_new_project( parsed_args )
if create_fn:
init_funcs.append( create_fn )
_enable_faulthandler()
_init_excepthooks( parsed_args )
eventcapture_mode, playback_args = _prepare_test_recording_and_playback( parsed_args )
if ilastik_config.getboolean("ilastik", "debug"):
logger.info("Starting ilastik in debug mode.")
else:
logger.info("Starting ilastik.")
# Headless launch
if parsed_args.headless:
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell( workflow_cmdline_args )
for f in init_funcs:
f(shell)
return shell
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, eventcapture_mode, playback_args, *init_funcs))
def main( parsed_args, workflow_cmdline_args=[] ):
this_path = os.path.dirname(__file__)
ilastik_dir = os.path.abspath(os.path.join(this_path, "..%s.." % os.path.sep))
# If necessary, redirect stdout BEFORE logging is initialized
_redirect_output( parsed_args )
_init_logging( parsed_args ) # Initialize logging before anything else
_init_configfile( parsed_args )
_update_debug_mode( parsed_args )
_init_threading_logging_monkeypatch()
_init_threading_h5py_monkeypatch()
_validate_arg_compatibility( parsed_args )
# Extra initialization functions.
# These are called during app startup, but before the shell is created.
preinit_funcs = []
preinit_funcs.append( _import_opengm ) # Must be first (or at least before vigra).
lazyflow_config_fn = _prepare_lazyflow_config( parsed_args )
if lazyflow_config_fn:
preinit_funcs.append( lazyflow_config_fn )
# More initialization functions.
# These will be called AFTER the shell is created.
# The shell is provided as a parameter to the function.
postinit_funcs = []
load_fn = _prepare_auto_open_project( parsed_args )
if load_fn:
postinit_funcs.append( load_fn )
create_fn = _prepare_auto_create_new_project( parsed_args )
if create_fn:
postinit_funcs.append( create_fn )
_enable_faulthandler()
_init_excepthooks( parsed_args )
eventcapture_mode, playback_args = _prepare_test_recording_and_playback( parsed_args )
if ilastik_config.getboolean("ilastik", "debug"):
message = 'Starting ilastik in debug mode from "%s".' % ilastik_dir
logger.info(message)
print message # always print the startup message
else:
message = 'Starting ilastik from "%s".' % ilastik_dir
logger.info(message)
print message # always print the startup message
# Headless launch
if parsed_args.headless:
# If any applet imports the GUI in headless mode, that's a mistake.
# To help developers catch such mistakes, we replace PyQt with a dummy module, so we'll see import errors.
import ilastik
dummy_module_dir = os.path.join( os.path.split(ilastik.__file__)[0], "headless_dummy_modules" )
sys.path.insert(0, dummy_module_dir)
# Run pre-init
for f in preinit_funcs:
f()
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell( workflow_cmdline_args )
# Run post-init
for f in postinit_funcs:
f(shell)
return shell
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, eventcapture_mode, playback_args, preinit_funcs, postinit_funcs))
from ilastik.shell.gui.startShellGui import startShellGui
from predictionViewerWorkflow import PredictionViewerWorkflow
if __name__ == "__main__":
startShellGui( PredictionViewerWorkflow )
def main( parsed_args, workflow_cmdline_args=[] ):
this_path = os.path.dirname(__file__)
ilastik_dir = os.path.abspath(os.path.join(this_path, "..%s.." % os.path.sep))
_update_debug_mode( parsed_args )
# If necessary, redirect stdout BEFORE logging is initialized
_redirect_output( parsed_args )
_init_logging( parsed_args ) # Initialize logging before anything else
_init_configfile( parsed_args )
_init_threading_logging_monkeypatch()
_init_threading_h5py_monkeypatch()
_validate_arg_compatibility( parsed_args )
# Extra initialization functions.
# These are called during app startup, but before the shell is created.
preinit_funcs = []
preinit_funcs.append( _import_opengm ) # Must be first (or at least before vigra).
lazyflow_config_fn = _prepare_lazyflow_config( parsed_args )
if lazyflow_config_fn:
preinit_funcs.append( lazyflow_config_fn )
# More initialization functions.
# These will be called AFTER the shell is created.
# The shell is provided as a parameter to the function.
postinit_funcs = []
load_fn = _prepare_auto_open_project( parsed_args )
if load_fn:
postinit_funcs.append( load_fn )
create_fn = _prepare_auto_create_new_project( parsed_args )
if create_fn:
postinit_funcs.append( create_fn )
_enable_faulthandler()
_init_excepthooks( parsed_args )
eventcapture_mode, playback_args = _prepare_test_recording_and_playback( parsed_args )
if ilastik_config.getboolean("ilastik", "debug"):
message = 'Starting ilastik in debug mode from "%s".' % ilastik_dir
logger.info(message)
print message # always print the startup message
else:
message = 'Starting ilastik from "%s".' % ilastik_dir
logger.info(message)
print message # always print the startup message
# Headless launch
if parsed_args.headless:
# If any applet imports the GUI in headless mode, that's a mistake.
# To help developers catch such mistakes, we replace PyQt with a dummy module, so we'll see import errors.
import ilastik
dummy_module_dir = os.path.join( os.path.split(ilastik.__file__)[0], "headless_dummy_modules" )
sys.path.insert(0, dummy_module_dir)
# Run pre-init
for f in preinit_funcs:
f()
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell( workflow_cmdline_args )
# Run post-init
for f in postinit_funcs:
f(shell)
return shell
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, eventcapture_mode, playback_args, preinit_funcs, postinit_funcs))
from ilastik.shell.gui.startShellGui import startShellGui
from layerViewerWorkflow import LayerViewerWorkflow
def debug_with_new(shell, workflow):
"""
(Function for debug and testing.)
"""
projFilePath = "/magnetic/test_project.ilp"
# New project
shell.createAndLoadNewProject(projFilePath)
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
#info.filePath = '/magnetic/gigacube.h5'
info.filePath = '/magnetic/5d.npy'
#info.filePath = '/magnetic/synapse_small.npy'
#info.filePath = '/magnetic/singleslice.h5'
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.Dataset.resize(1)
opDataSelection.Dataset[0].setValue(info)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
startShellGui( LayerViewerWorkflow )
#startShellGui( LayerViewerWorkflow, debug_with_new )
help="specify a file which adds a hint overlay")
parser.add_option("--pmapoverlay",
dest="pmapoverlayFile", default=None,
help="specify a file which adds a pmap overlay")
options, args = parser.parse_args()
if len(args)==0:
workflowKwargs={'hintoverlayFile' : options.hintoverlayFile,
'pmapoverlayFile' : options.pmapoverlayFile }
def loadProject(shell):
pass
startShellGui(functools.partial(CarvingWorkflow, **workflowKwargs),loadProject)
elif len(args)==1:
projectFilename = args[0]
def loadProject(shell):
shell.openProjectFile(projectFilename)
workflowKwargs={'hintoverlayFile' : options.hintoverlayFile,
'pmapoverlayFile' : options.pmapoverlayFile }
startShellGui( functools.partial(CarvingWorkflow, **workflowKwargs), loadProject)
elif len(args) == 2:
carvingGraphFilename = os.path.abspath(args[0]).replace("\\","/")
projectFilename = args[1]
from optparse import OptionParser
usage = "%prog [options] <carving graph filename> <project filename to be created>"
parser = OptionParser(usage)
# import sys
# sys.argv.append("/magnetic/denk.h5")
# sys.argv.append("/magnetic/carving_test.ilp")
(options, args) = parser.parse_args()
if len(args) == 2:
carvingGraphFilename = args[0]
projectFilename = args[1]
def loadProject(shell, workflow):
if not os.path.exists(projectFilename):
shell.createAndLoadNewProject(projectFilename)
else:
shell.openProjectFile(projectFilename)
workflow.setCarvingGraphFile(carvingGraphFilename)
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
info.filePath = carvingGraphFilename + "/graph/raw"
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.Dataset.resize(1)
opDataSelection.Dataset[0].setValue(info)
shell.setSelectedAppletDrawer(2)
startShellGui( CarvingWorkflow, loadProject, windowTitle="Carving %s" % carvingGraphFilename,
workflowKwargs={'carvingGraphFile': carvingGraphFilename} )
else:
parser.error("incorrect number of arguments")
from ilastik.shell.gui.startShellGui import startShellGui
from labelImageViewerWorkflow import LabelImageViewerWorkflow
if __name__ == "__main__":
startShellGui( LabelImageViewerWorkflow )
init_funcs.append( loadProject )
if parsed_args.playback_script is not None:
from ilastik.utility.gui.eventRecorder import EventPlayer
def play_recording(shell):
player = EventPlayer(parsed_args.playback_speed)
player.play_script(parsed_args.playback_script)
init_funcs.append( partial(play_recording) )
if parsed_args.exit_on_failure:
old_excepthook = sys.excepthook
def print_exc_and_exit(*args):
old_excepthook(*args)
sys.stderr.write("Exiting early due to an unhandled exception. See error output above.\n")
from PyQt4.QtGui import QApplication
QApplication.exit(1)
sys.excepthook = print_exc_and_exit
from ilastik.shell.gui.startShellGui import startShellGui
from pixelClassificationWorkflow import PixelClassificationWorkflow
startShellGui( PixelClassificationWorkflow, *init_funcs )
# Start the GUI with a debug project
#startShellGui( PixelClassificationWorkflow )
#startShellGui( PixelClassificationWorkflow, debug_with_existing )
#startShellGui( PixelClassificationWorkflow, debug_with_new )
# Test special transpose-on-import feature
#startShellGui( PixelClassificationWorkflow, debug_with_imported )
def main(parsed_args, workflow_cmdline_args=[], init_logging=True):
"""
init_logging: Skip logging config initialization by setting this to False.
(Useful when opening multiple projects in a Python script.)
"""
if parsed_args.headless:
# If any applet imports the GUI in headless mode, that's a mistake.
# To help developers catch such mistakes, we replace PyQt with a dummy
# module, so we'll see import errors.
import ilastik
dummy_module_dir = os.path.join(
os.path.split(ilastik.__file__)[0], "headless_dummy_modules")
sys.path.insert(0, dummy_module_dir)
this_path = os.path.dirname(__file__)
ilastik_dir = os.path.abspath(
os.path.join(this_path, "..%s.." % os.path.sep))
_import_h5py_with_utf8_encoding()
_update_debug_mode(parsed_args)
_update_hbp_mode(parsed_args)
# If necessary, redirect stdout BEFORE logging is initialized
_redirect_output(parsed_args)
if init_logging:
_init_logging(parsed_args) # Initialize logging before anything else
_init_configfile(parsed_args)
_init_threading_logging_monkeypatch()
# Extra initialization functions.
# These are called during app startup, but before the shell is created.
preinit_funcs = []
# Must be first (or at least before vigra).
preinit_funcs.append(_import_opengm)
lazyflow_config_fn = _prepare_lazyflow_config(parsed_args)
if lazyflow_config_fn:
preinit_funcs.append(lazyflow_config_fn)
# More initialization functions.
# These will be called AFTER the shell is created.
# The shell is provided as a parameter to the function.
postinit_funcs = []
load_fn = _prepare_auto_open_project(parsed_args)
if load_fn:
postinit_funcs.append(load_fn)
create_fn = _prepare_auto_create_new_project(parsed_args)
if create_fn:
postinit_funcs.append(create_fn)
faulthandler.enable()
_init_excepthooks(parsed_args)
if ilastik_config.getboolean("ilastik", "debug"):
message = 'Starting ilastik in debug mode from "%s".' % ilastik_dir
logging.basicConfig(level=logging.DEBUG)
logger.info(message)
print(message) # always print the startup message
else:
message = 'Starting ilastik from "%s".' % ilastik_dir
logger.info(message)
print(message) # always print the startup message
# Headless launch
if parsed_args.headless:
# Run pre-init
for f in preinit_funcs:
f()
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell(workflow_cmdline_args)
# Run post-init
for f in postinit_funcs:
f(shell)
return shell
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, preinit_funcs, postinit_funcs))
# Set some features
import numpy
featApplet = workflow.applets[2]
featureGui = featApplet.gui
opFeatures = featApplet.topLevelOperator
# sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0
selections = numpy.array([
[True, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False], # ST EVs
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False], # GGM
[False, False, False, False, False, False, False]
])
opFeatures.SelectionMatrix.setValue(selections)
opFeatures.Scales.setValue(featureGui.ScalesList)
opFeatures.FeatureIds.setValue(featureGui.FeatureIds)
# Select the labeling drawer
shell.setSelectedAppletDrawer(3)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
startShellGui(PixelClassificationWithVigraWatershedWorkflow)
#startShellGui( PixelClassificationWithVigraWatershedWorkflow, debug_with_new )
#startShellGui( PixelClassificationWithVigraWatershedWorkflow, debug_with_existing )
from ilastik.shell.gui.startShellGui import startShellGui
from chaingraphTrackingWorkflow import ChaingraphTrackingWorkflow
debug_testing = False
if debug_testing:
def test(shell, workflow):
#projFilePath = '/home/bergs/Downloads/synapse_detection_training1.ilp'
#projFilePath = '/home/bkausler/withLabelImageAndRegionCenters.ilp'
#projFilePath = '/home/mschiegg/hufnagel2012-08-03/375-386_classification.ilp'
projFilePath = '/home/mschiegg/hufnagel2012-08-03/segmentation/375-386_tracking.ilp'
#shell.createAndLoadNewProject(projFilePath)
shell.openProjectFile(projFilePath)
#from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
#info = DatasetInfo()
#info.filePath = '/magnetic/gigacube.h5'
#info.filePath = '/home/mschiegg/hufnagel2012-08-03/375-386diff_results_rgb.h5'
#info.filePath = '/magnetic/synapse_small.npy'
#info.filePath = '/magnetic/singleslice.h5'
#opDataSelection = workflow.dataSelectionApplet.topLevelOperator
#opDataSelection.Dataset.resize(1)
#opDataSelection.Dataset[0].setValue(info)
shell.setSelectedAppletDrawer(2)
startShellGui( ChaingraphTrackingWorkflow, test )
else:
startShellGui( ChaingraphTrackingWorkflow )
# Import the project
shell.importProject(importedFilePath, newProjectFilePath)
# Select the labeling drawer
shell.setSelectedAppletDrawer(3)
if __name__ == "__main__":
from optparse import OptionParser
usage = "%prog [options] filename"
parser = OptionParser(usage)
(options, args) = parser.parse_args()
# Start the GUI
if len(args) == 1:
def loadProject(shell, workflow):
shell.openProjectFile(args[0])
startShellGui( PixelClassificationWorkflow, loadProject )
elif len(args) == 0:
startShellGui( PixelClassificationWorkflow )
else:
parser.error("incorrect number of arguments")
# Start the GUI with a debug project
#startShellGui( PixelClassificationWorkflow )
#startShellGui( PixelClassificationWorkflow, debug_with_existing )
#startShellGui( PixelClassificationWorkflow, debug_with_new )
# Test special transpose-on-import feature
#startShellGui( PixelClassificationWorkflow, debug_with_imported )
#predictionInfo.filePath = '/magnetic/synapse_debug_data/block256_spots_predictions.h5/cube'
#predictionInfo.filePath = '/magnetic/synapse_small_4d_synapse_predictions.h5/volume/data'
predictionInfo.filePath = '/magnetic/validation_slices_20_40_3200_4000_1200_2000_pred.h5/volume/data'
opPredDataSelection = workflow.predictionSelectionApplet.topLevelOperator
opPredDataSelection.Dataset.resize(1)
opPredDataSelection.Dataset[0].setValue(predictionInfo)
# Select the feature drawer
shell.setSelectedAppletDrawer(2)
def debug_with_existing(shell):
"""
(Function for debug and testing.)
"""
# Open an existing project
#projFilePath = "/magnetic/objectLabels_good.ilp"
#projFilePath = "/magnetic/object_prediction.ilp"
projFilePath = "/magnetic/stuart_object_predictions.ilp"
shell.openProjectFile(projFilePath)
# Select a default drawer
shell.setSelectedAppletDrawer(2)
if __name__ == '__main__':
startShellGui( SynapseBlockwiseWorkflow )
#startShellGui( SynapseBlockwiseWorkflow, debug_with_new )
#startShellGui( SynapseBlockwiseWorkflow, debug_with_existing )
from ilastik.shell.gui.startShellGui import startShellGui
from synapsePixelClassificationWorkflow import SynapsePixelClassificationWorkflow
if __name__ == '__main__':
startShellGui( SynapsePixelClassificationWorkflow )
sys.excepthook = print_exc_and_exit
install_thread_excepthook()
# Show uncaught exceptions to the user (default behavior)
elif not ilastik_config.getboolean('ilastik', 'debug') and not parsed_args.headless:
old_excepthook = sys.excepthook
def exception_dialog(*exc_info):
old_excepthook(*exc_info)
try:
from ilastik.shell.gui.startShellGui import shell
shell.postErrorMessage( exc_info[0].__name__, str(exc_info[1]) )
except:
pass
sys.excepthook = exception_dialog
install_thread_excepthook()
if ilastik_config.getboolean("ilastik", "debug"):
logger.info("Starting ilastik in debug mode.")
# Headless launch
if parsed_args.headless:
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell( workflow_cmdline_args )
for f in init_funcs:
f(shell)
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, parsed_args.start_recording, *init_funcs))
featureGui = workflow.featureSelectionApplet.gui
opFeatures = workflow.featureSelectionApplet.topLevelOperator
# sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0
selections = numpy.array( [[False, False, False, True, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False], # ST EVs
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False], # GGM
[False, False, False, False, False, False, False]] )
opFeatures.SelectionMatrix.setValue(selections)
opFeatures.Scales.setValue( featureGui.ScalesList )
opFeatures.FeatureIds.setValue( featureGui.FeatureIds )
# Select the labeling drawer
shell.setSelectedAppletDrawer(3)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
# Start the GUI
#import os
#os.execl('/home/akreshuk/voluminave/bin/activate')
startShellGui( AutocontextClassificationWorkflow )
# Start the GUI with a debug project
#startShellGui( AutocontextClassificationWorkflow, debug_with_existing )
# startShellGui( AutocontextClassificationWorkflow, debug_with_new )
def main(parsed_args, workflow_cmdline_args=[], init_logging=True):
"""
init_logging: Skip logging config initialization by setting this to False.
(Useful when opening multiple projects in a Python script.)
"""
this_path = os.path.dirname(__file__)
ilastik_dir = os.path.abspath(
os.path.join(this_path, "..%s.." % os.path.sep))
_import_h5py_with_utf8_encoding()
_update_debug_mode(parsed_args)
_update_hbp_mode(parsed_args)
# If necessary, redirect stdout BEFORE logging is initialized
_redirect_output(parsed_args)
if init_logging:
_init_logging(parsed_args) # Initialize logging before anything else
_init_configfile(parsed_args)
_init_threading_logging_monkeypatch()
_init_preferences()
# Extra initialization functions.
# These are called during app startup, but before the shell is created.
preinit_funcs = []
# Must be first (or at least before vigra).
preinit_funcs.append(_import_opengm)
lazyflow_config_fn = _prepare_lazyflow_config(parsed_args)
if lazyflow_config_fn:
preinit_funcs.append(lazyflow_config_fn)
# More initialization functions.
# These will be called AFTER the shell is created.
# The shell is provided as a parameter to the function.
postinit_funcs = []
load_fn = _prepare_auto_open_project(parsed_args)
if load_fn:
postinit_funcs.append(load_fn)
create_fn = _prepare_auto_create_new_project(parsed_args)
if create_fn:
postinit_funcs.append(create_fn)
faulthandler.enable()
_init_excepthooks(parsed_args)
if ilastik_config.getboolean("ilastik", "debug"):
message = 'Starting ilastik in debug mode from "%s".' % ilastik_dir
logging.basicConfig(level=logging.DEBUG)
logger.info(message)
print(message) # always print the startup message
else:
message = 'Starting ilastik from "%s".' % ilastik_dir
logger.info(message)
print(message) # always print the startup message
# Headless launch
if parsed_args.headless:
# Run pre-init
for f in preinit_funcs:
f()
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell(workflow_cmdline_args)
# Run post-init
for f in postinit_funcs:
f(shell)
return shell
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(
startShellGui(workflow_cmdline_args, preinit_funcs,
postinit_funcs))
from layerViewerWorkflow import LayerViewerWorkflow
def debug_with_new(shell, workflow):
"""
(Function for debug and testing.)
"""
projFilePath = "/magnetic/test_project.ilp"
# New project
shell.createAndLoadNewProject(projFilePath)
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
#info.filePath = '/magnetic/gigacube.h5'
info.filePath = '/magnetic/5d.npy'
#info.filePath = '/magnetic/synapse_small.npy'
#info.filePath = '/magnetic/singleslice.h5'
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.Dataset.resize(1)
opDataSelection.Dataset[0].setValue(info)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
startShellGui(LayerViewerWorkflow)
#startShellGui( LayerViewerWorkflow, debug_with_new )
#!/usr/bin/env python
from ilastik.shell.gui.startShellGui import startShellGui
from optparse import OptionParser
import ilastik.workflows
from ilastik.workflow import getWorkflowFromName
usage = "%prog [options] <project file>"
parser = OptionParser(usage)
parser.add_option("--workflow",
dest="workflow", default=None,
help="specify a workflow that should be loaded")
options, args = parser.parse_args()
if len(args)==0:
startShellGui(workflowClass=options.workflow)
elif len(args)==1:
def loadProject(shell):
shell.openProjectFile(args[0])
workflowClass = getWorkflowFromName(options.workflow)
startShellGui(workflowClass,loadProject)
from ilastik.shell.gui.startShellGui import startShellGui
from ilastik.shell.gui.eventRecorder import EventRecorder
from thresholdMaskingWorkflow import ThresholdMaskingWorkflow
debug_testing = False
if debug_testing:
def test(shell):
projFilePath = '/Users/bergs/MyProject.ilp'
shell.openProjectFile(projFilePath)
eventRecorder = EventRecorder( parent=shell )
eventRecorder.start()
startShellGui( ThresholdMaskingWorkflow, test )
else:
startShellGui( ThresholdMaskingWorkflow )
featApplet = workflow.applets[2]
featureGui = featApplet.gui
opFeatures = featApplet.topLevelOperator
# sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0
selections = numpy.array( [[True, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False], # ST EVs
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False], # GGM
[False, False, False, False, False, False, False]] )
opFeatures.SelectionMatrix.setValue(selections)
opFeatures.Scales.setValue( featureGui.ScalesList )
opFeatures.FeatureIds.setValue( featureGui.FeatureIds )
# Select the labeling drawer
shell.setSelectedAppletDrawer(3)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
startShellGui( PixelClassificationWithVigraWatershedWorkflow )
#startShellGui( PixelClassificationWithVigraWatershedWorkflow, debug_with_new )
#startShellGui( PixelClassificationWithVigraWatershedWorkflow, debug_with_existing )
from ilastik.shell.gui.startShellGui import startShellGui
from featureSelectionWorkflow import FeatureSelectionWorkflow
debug_testing = False
if debug_testing:
def test(shell, workflow):
#projFilePath = '/home/bergs/Downloads/synapse_detection_training1.ilp'
projFilePath = '/magnetic/MyProject.ilp'
shell.openProjectFile(projFilePath)
startShellGui( FeatureSelectionWorkflow, test )
else:
startShellGui( FeatureSelectionWorkflow )
help="specify a file which adds a hint overlay")
parser.add_option("--pmapoverlay",
dest="pmapoverlayFile", default=None,
help="specify a file which adds a pmap overlay")
options, args = parser.parse_args()
if len(args)==0:
workflowKwargs={'hintoverlayFile' : options.hintoverlayFile,
'pmapoverlayFile' : options.pmapoverlayFile }
def loadProject(shell):
pass
startShellGui(functools.partial(CarvingWorkflow, **workflowKwargs),loadProject)
elif len(args)==1:
projectFilename = args[0]
def loadProject(shell):
shell.openProjectFile(projectFilename)
workflowKwargs={'hintoverlayFile' : options.hintoverlayFile,
'pmapoverlayFile' : options.pmapoverlayFile }
startShellGui( functools.partial(CarvingWorkflow, **workflowKwargs), loadProject)
elif len(args) == 2:
carvingGraphFilename = os.path.abspath(args[0]).replace("\\","/")
projectFilename = args[1]
from ilastik.shell.gui.startShellGui import startShellGui
from deviationFromMeanWorkflow import DeviationFromMeanWorkflow
debug_testing = False
if debug_testing:
def test(shell):
#projFilePath = '/home/bergs/Downloads/synapse_detection_training1.ilp'
projFilePath = '/home/bergs/MyProject.ilp'
shell.openProjectFile(projFilePath)
startShellGui( DeviationFromMeanWorkflow, test )
else:
startShellGui( DeviationFromMeanWorkflow )
from ilastik.shell.gui.startShellGui import startShellGui
from thresholdMaskingWorkflow import ThresholdMaskingWorkflow
debug_testing = True
if debug_testing:
def test(shell):
import h5py
#projFilePath = '/home/bergs/Downloads/synapse_detection_training1.ilp'
projFilePath = '/home/bergs/gigacube.ilp'
shell.openProjectFile(projFilePath)
startShellGui(ThresholdMaskingWorkflow, test)
else:
startShellGui(ThresholdMaskingWorkflow)
def debug_with_new(shell, workflow):
"""
(Function for debug and testing.)
"""
projFilePath = "/magnetic/test_watershed_project.ilp"
# New project
shell.createAndLoadNewProject(projFilePath)
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
#info.filePath = '/magnetic/gigacube.h5'
#info.filePath = '/magnetic/synapse_small.npy'
info.filePath = '/magnetic/synapse_small.npy_results.h5'
#info.filePath = '/magnetic/singleslice.h5'
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.Dataset.resize(1)
opDataSelection.Dataset[0].setValue(info)
# Select the watershed drawer
shell.setSelectedAppletDrawer(1)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
startShellGui(VigraWatershedWorkflow)
#startShellGui( VigraWatershedWorkflow, debug_with_new )
sys.excepthook = print_exc_and_exit
install_thread_excepthook()
# Show uncaught exceptions to the user (default behavior)
elif not ilastik_config.getboolean('ilastik', 'debug') and not parsed_args.headless:
old_excepthook = sys.excepthook
def exception_dialog(*exc_info):
old_excepthook(*exc_info)
try:
from ilastik.shell.gui.startShellGui import shell
shell.postErrorMessage( exc_info[0].__name__, str(exc_info[1]) )
except:
pass
sys.excepthook = exception_dialog
install_thread_excepthook()
if ilastik_config.getboolean("ilastik", "debug"):
logger.info("Starting ilastik in debug mode.")
# Headless launch
if parsed_args.headless:
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell( workflow_cmdline_args )
for f in init_funcs:
f(shell)
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, eventcapture_mode, playback_args, *init_funcs))
sys.stderr.write("Exiting early due to an unhandled exception. See error output above.\n")
QApplication.exit(1)
sys.excepthook = print_exc_and_exit
install_thread_excepthook()
# Show uncaught exceptions to the user (default behavior)
elif not ilastik_config.getboolean('ilastik', 'debug') and not parsed_args.headless:
old_excepthook = sys.excepthook
def exception_dialog(*args):
old_excepthook(*args)
try:
from ilastik.shell.gui.startShellGui import shell
shell.postErrorMessage(args[0].__name__, args[1].message)
except:
pass
sys.excepthook = exception_dialog
install_thread_excepthook()
if ilastik_config.getboolean("ilastik", "debug"):
logger.info("Starting ilastik in debug mode.")
# Headless launch
if parsed_args.headless:
from ilastik.shell.headless.headlessShell import HeadlessShell
shell = HeadlessShell( workflow_cmdline_args )
for f in init_funcs:
f(shell)
# Normal launch
else:
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit(startShellGui(workflow_cmdline_args, parsed_args.start_recording, *init_funcs))
from ilastik.shell.gui.startShellGui import startShellGui
from fillMissingSlicesWorkflow import FillMissingSlicesWorkflow
debug_testing = False
if debug_testing:
def test(shell, workflow):
#projFilePath = '/home/bergs/Downloads/synapse_detection_training1.ilp'
projFilePath = '/magnetic/MyProject.ilp'
shell.openProjectFile(projFilePath)
startShellGui( FillMissingSlicesWorkflow, test )
else:
startShellGui( FillMissingSlicesWorkflow )
from ilastik.shell.gui.startShellGui import startShellGui from stopWatchWorkflow import StopWatchWorkflow startShellGui( StopWatchWorkflow )
#info.filePath = '/magnetic/synapse_small.npy'
info.filePath = '/magnetic/synapse_small.npy_results.h5'
#info.filePath = '/magnetic/singleslice.h5'
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.Dataset.resize(1)
opDataSelection.Dataset[0].setValue(info)
# Select the watershed drawer
shell.setSelectedAppletDrawer(1)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
from optparse import OptionParser
usage = "%prog [options] filename"
parser = OptionParser(usage)
(options, args) = parser.parse_args()
# Start the GUI
if len(args) == 1:
def loadProject(shell):
shell.openProjectFile(args[0])
startShellGui( VigraWatershedWorkflow, loadProject )
elif len(args) == 0:
startShellGui( VigraWatershedWorkflow )
else:
parser.error("incorrect number of arguments")
shell.setSelectedAppletDrawer(1)
def debug_with_new(shell, workflow):
"""
(Function for debug and testing.)
"""
projFilePath = "/magnetic/test_project.ilp"
# New project
shell.createAndLoadNewProject(projFilePath)
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
info.filePath = '/magnetic/gigacube.h5'
#info.filePath = '/magnetic/synapse_small.npy'
#info.filePath = '/magnetic/singleslice.h5'
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.Dataset.resize(1)
opDataSelection.Dataset[0].setValue(info)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
startShellGui(LabelingWorkflow)
#startShellGui( LabelingWorkflow, debug_with_new )
#startShellGui( LabelingWorkflow, debug_with_existing )
# Select the labeling drawer
shell.setSelectedAppletDrawer(3)
if __name__ == "__main__":
from optparse import OptionParser
usage = "%prog [options] filename"
parser = OptionParser(usage)
(options, args) = parser.parse_args()
# Start the GUI
if len(args) == 1:
def loadProject(shell, workflow):
shell.openProjectFile(args[0])
startShellGui(PixelClassificationWorkflow, loadProject)
elif len(args) == 0:
startShellGui(PixelClassificationWorkflow)
else:
parser.error("incorrect number of arguments")
# Start the GUI with a debug project
#startShellGui( PixelClassificationWorkflow )
#startShellGui( PixelClassificationWorkflow, debug_with_existing )
#startShellGui( PixelClassificationWorkflow, debug_with_new )
# Test special transpose-on-import feature
#startShellGui( PixelClassificationWorkflow, debug_with_imported )
"""
(Function for debug and testing.)
"""
projFilePath = "/magnetic/test_watershed_project.ilp"
# New project
shell.createAndLoadNewProject(projFilePath)
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
#info.filePath = '/magnetic/gigacube.h5'
#info.filePath = '/magnetic/synapse_small.npy'
info.filePath = '/magnetic/synapse_small.npy_results.h5'
#info.filePath = '/magnetic/singleslice.h5'
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.Dataset.resize(1)
opDataSelection.Dataset[0].setValue(info)
# Select the watershed drawer
shell.setSelectedAppletDrawer(1)
# Save the project
shell.onSaveProjectActionTriggered()
if __name__ == "__main__":
startShellGui( VigraWatershedWorkflow )
#startShellGui( VigraWatershedWorkflow, debug_with_new )
onfinish = None
if parsed_args.exit_on_success:
onfinish = QApplication.quit
if parsed_args.playback_script is not None:
from ilastik.utility.gui.eventRecorder import EventPlayer
def play_recording(shell):
player = EventPlayer(parsed_args.playback_speed)
player.play_script(parsed_args.playback_script, onfinish)
init_funcs.append( partial(play_recording) )
if parsed_args.exit_on_failure:
old_excepthook = sys.excepthook
def print_exc_and_exit(*args):
old_excepthook(*args)
sys.stderr.write("Exiting early due to an unhandled exception. See error output above.\n")
QApplication.exit(1)
sys.excepthook = print_exc_and_exit
install_thread_excepthook()
# Import all possible workflows so they are registered with the base class
import ilastik.workflows
# Ask the base class to give us the workflow type
from ilastik.workflow import Workflow
workflowClass = Workflow.getSubclass(parsed_args.workflow)
# Launch the GUI
from ilastik.shell.gui.startShellGui import startShellGui
sys.exit( startShellGui( workflowClass, *init_funcs ) )
from optparse import OptionParser
usage = "%prog [options] filename"
parser = OptionParser(usage)
parser.add_option("-b", "--binary",
action="store_true",
dest="binary",
default=False,
help="use binary workflow")
(options, args) = parser.parse_args()
#options.binary = True
if options.binary:
workflow = binary_workflow
else:
workflow = pixel_workflow
# Start the GUI
if len(args) == 1:
def loadProject(shell):
shell.openProjectFile(args[0])
startShellGui(workflow, loadProject)
elif len(args) == 0:
startShellGui(workflow)
#startShellGui(workflow, debug_with_new)
#startShellGui(workflow, debug_with_existing)
else:
parser.error("incorrect number of arguments")
init_funcs.append(loadProject)
onfinish = None
if parsed_args.exit_on_success:
onfinish = QApplication.quit
if parsed_args.playback_script is not None:
def play_recording(shell):
player = EventPlayer(parsed_args.playback_speed)
player.play_script(parsed_args.playback_script, onfinish)
init_funcs.append( partial(play_recording) )
if parsed_args.exit_on_failure:
old_excepthook = sys.excepthook
def print_exc_and_exit(*args):
old_excepthook(*args)
sys.stderr.write("Exiting early due to an unhandled exception. See error output above.\n")
QApplication.exit(1)
sys.excepthook = print_exc_and_exit
install_thread_excepthook()
if parsed_args.debug:
ilastik_config.set('ilastik', 'debug', 'true')
if ilastik_config.getboolean("ilastik", "debug"):
logger.info("Starting ilastik in debug mode.")
sys.exit(startShellGui(None,*init_funcs))
shell.createAndLoadNewProject(projFilePath)
workflow = shell.projectManager.workflow
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
rawInfo = DatasetInfo()
#rawInfo.filePath = '/magnetic/synapse_debug_data/block256.h5/cube'
#rawInfo.filePath = '/magnetic/synapse_small_4d.h5/volume/data'
rawInfo.filePath = '/magnetic/validation_slices_20_40_3200_4000_1200_2000.h5/volume/data'
opRawDataSelection = workflow.rawDataSelectionApplet.topLevelOperator
opRawDataSelection.Dataset.resize(1)
opRawDataSelection.Dataset[0].setValue(rawInfo)
predictionInfo = DatasetInfo()
#predictionInfo.filePath = '/magnetic/synapse_debug_data/block256_spots_predictions.h5/cube'
#predictionInfo.filePath = '/magnetic/synapse_small_4d_synapse_predictions.h5/volume/data'
predictionInfo.filePath = '/magnetic/validation_slices_20_40_3200_4000_1200_2000_pred.h5/volume/data'
opPredDataSelection = workflow.predictionSelectionApplet.topLevelOperator
opPredDataSelection.Dataset.resize(1)
opPredDataSelection.Dataset[0].setValue(predictionInfo)
# Select the feature drawer
shell.setSelectedAppletDrawer(2)
if __name__ == '__main__':
startShellGui( SynapseObjectClassificationWorkflow )
#startShellGui( SynapseObjectClassificationWorkflow, debug_with_new )
#startShellGui( SynapseObjectClassificationWorkflow, debug_with_existing )
