def maybe_download_example_image(folders, file_name, shape=None):
'''Download the given ExampleImages file if not in the directory
folders - sequence of subfolders starting at ExampleImages
file_name - name of file to fetch
Image will be downloaded if not present to CP_EXAMPLEIMAGES directory.
Returns the local path to the file which is often useful.
'''
if shape is None:
shape = (20, 30)
local_path = os.path.join(*tuple([
example_images_directory()] + folders + [file_name]))
if not os.path.exists(local_path):
directory = os.path.join(*tuple([
example_images_directory()] + folders))
if not os.path.isdir(directory):
os.makedirs(directory)
r = np.random.RandomState()
r.seed(np.frombuffer(
hashlib.sha1("/".join(folders) + file_name).digest(),
np.uint8))
img = (r.uniform(size=shape) * 255).astype(np.uint8)
write_image(local_path, img, PT_UINT8)
return local_path
def maybe_download_example_image(folders, file_name, shape=None):
'''Download the given ExampleImages file if not in the directory
folders - sequence of subfolders starting at ExampleImages
file_name - name of file to fetch
Image will be downloaded if not present to CP_EXAMPLEIMAGES directory.
Returns the local path to the file which is often useful.
'''
if shape is None:
shape = (20, 30)
local_path = os.path.join(*tuple([example_images_directory()] + folders +
[file_name]))
if not os.path.exists(local_path):
directory = os.path.join(*tuple([example_images_directory()] +
folders))
if not os.path.isdir(directory):
os.makedirs(directory)
r = np.random.RandomState()
r.seed(
np.frombuffer(
hashlib.sha1("/".join(folders) + file_name).digest(),
np.uint8))
img = (r.uniform(size=shape) * 255).astype(np.uint8)
write_image(local_path, img, PT_UINT8)
return local_path
def test_01_01_write_monochrome_8_bit_tif(self):
r = np.random.RandomState()
r.seed(101)
img = r.randint(0, 256, (11, 33)).astype(np.uint8)
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_01_write_monochrome_8_bit_tif(self):
r = np.random.RandomState()
r.seed(101)
img = r.randint(0, 256, (11, 33)).astype(np.uint8)
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_03_write_color_tiff(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (9, 11, 3))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale = False)
np.testing.assert_array_equal(img, result)
def test_01_03_write_color_tiff(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (9, 11, 3))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_02_write_monchrome_16_bit__tiff(self):
r = np.random.RandomState()
r.seed(102)
img = r.randint(0, 4096, size=(21, 24))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT16)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_02_write_monchrome_16_bit__tiff(self):
r = np.random.RandomState()
r.seed(102)
img = r.randint(0, 4096, size=(21, 24))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT16)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_02_01_write_movie(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (7, 23, 11))
path = self.get_tempfilename(".tif")
for i in range(img.shape[0]):
W.write_image(path, img[i], OME.PT_UINT8, t=i, size_t = img.shape[0])
for i in range(img.shape[0]):
result = load_using_bioformats(path, t=i, rescale = False)
np.testing.assert_array_equal(img[i], result)
def test_02_01_write_movie(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (7, 23, 11))
path = self.get_tempfilename(".tif")
for i in range(img.shape[0]):
W.write_image(path, img[i], OME.PT_UINT8, t=i, size_t=img.shape[0])
for i in range(img.shape[0]):
result = load_using_bioformats(path, t=i, rescale=False)
np.testing.assert_array_equal(img[i], result)
def do_save_image(self,
workspace,
filename,
pixels,
pixel_type,
c=0,
z=0,
t=0,
size_c=1,
size_z=1,
size_t=1,
channel_names=None):
'''Save image using bioformats
workspace - the current workspace
filename - save to this filename
pixels - the image to save
pixel_type - save using this pixel type
c - the image's channel index
z - the image's z index
t - the image's t index
sizeC - # of channels in the stack
sizeZ - # of z stacks
sizeT - # of timepoints in the stack
channel_names - names of the channels (make up names if not present
'''
write_image(filename,
pixels,
pixel_type,
c=c,
z=z,
t=t,
size_c=size_c,
size_z=size_z,
size_t=size_t,
channel_names=channel_names)
def maybe_download_example_image(folders, file_name, shape=None):
"""Download the given ExampleImages file if not in the directory
folders - sequence of subfolders starting at ExampleImages
file_name - name of file to fetch
Image will be downloaded if not present to CP_EXAMPLEIMAGES directory.
Returns the local path to the file which is often useful.
"""
if shape is None:
shape = (20, 30)
local_path = os.path.join(*tuple([example_images_directory()] + folders +
[file_name]))
if not os.path.exists(local_path):
directory = os.path.join(*tuple([example_images_directory()] +
folders))
if not os.path.isdir(directory):
os.makedirs(directory)
random_state = numpy.random.RandomState()
random_state.seed()
image = (random_state.uniform(size=shape) * 255).astype(numpy.uint8)
write_image(local_path, image, "uint8")
return local_path
def make_12_bit_image(folder, filename, shape):
"""Create a 12-bit image of the desired shape
folder - subfolder of example images directory
filename - filename for image file
shape - 2-tuple or 3-tuple of the dimensions of the image. The axis order
is i, j, c or y, x, c
"""
r = np.random.RandomState()
r.seed(np.frombuffer(hashlib.sha1("/".join([folder, filename])).digest(), np.uint8))
img = (r.uniform(size=shape) * 4095).astype(np.uint16)
path = os.path.join(example_images_directory(), folder, filename)
if not os.path.isdir(os.path.dirname(path)):
os.makedirs(os.path.dirname(path))
write_image(path, img, PT_UINT16)
#
# Now go through the file and find the TIF bits per sample IFD (#258) and
# change it from 16 to 12.
#
with open(path, "rb") as fd:
data = np.frombuffer(fd.read(), np.uint8).copy()
offset = np.frombuffer(data[4:8].data, np.uint32)[0]
nentries = np.frombuffer(data[offset : offset + 2], np.uint16)[0]
ifds = []
# Get the IFDs we don't modify
for idx in range(nentries):
ifd = data[offset + 2 + idx * 12 : offset + 14 + idx * 12]
code = ifd[0] + 256 * ifd[1]
if code not in (258, 281):
ifds.append(ifd)
ifds += [
# 12 bits/sample
np.array([2, 1, 3, 0, 1, 0, 0, 0, 12, 0, 0, 0], np.uint8),
# max value = 4095
np.array([25, 1, 3, 0, 1, 0, 0, 0, 255, 15, 0, 0], np.uint8),
]
ifds = sorted(ifds, cmp=(lambda a, b: cmp(a.tolist(), b.tolist())))
old_end = offset + 2 + nentries * 12
new_end = offset + 2 + len(ifds) * 12
diff = new_end - old_end
#
# Fix up the IFD offsets if greater than "offset"
#
for ifd in ifds:
count = np.frombuffer(ifd[4:8].data, np.uint32)[0]
if count > 4:
ifd_off = np.array([np.frombuffer(ifd[8:12].data, np.uint32)[0]]) + diff
if ifd_off > offset:
ifd[8:12] = np.frombuffer(ifd_off.data, np.uint8)
new_data = np.zeros(len(data) + diff, np.uint8)
new_data[:offset] = data[:offset]
new_data[offset] = len(ifds) % 256
new_data[offset + 1] = int(len(ifds) / 256)
for idx, ifd in enumerate(ifds):
new_data[offset + 2 + idx * 12 : offset + 14 + idx * 12] = ifd
new_data[new_end:] = data[old_end:]
with open(path, "wb") as fd:
fd.write(new_data.data)
return path
def make_12_bit_image(folder, filename, shape):
'''Create a 12-bit image of the desired shape
folder - subfolder of example images directory
filename - filename for image file
shape - 2-tuple or 3-tuple of the dimensions of the image. The axis order
is i, j, c or y, x, c
'''
r = np.random.RandomState()
r.seed(
np.frombuffer(
hashlib.sha1("/".join([folder, filename])).digest(), np.uint8))
img = (r.uniform(size=shape) * 4095).astype(np.uint16)
path = os.path.join(example_images_directory(), folder, filename)
if not os.path.isdir(os.path.dirname(path)):
os.makedirs(os.path.dirname(path))
write_image(path, img, PT_UINT16)
#
# Now go through the file and find the TIF bits per sample IFD (#258) and
# change it from 16 to 12.
#
with open(path, "rb") as fd:
data = np.frombuffer(fd.read(), np.uint8).copy()
offset = np.frombuffer(data[4:8].data, np.uint32)[0]
nentries = np.frombuffer(data[offset:offset + 2], np.uint16)[0]
ifds = []
# Get the IFDs we don't modify
for idx in range(nentries):
ifd = data[offset + 2 + idx * 12:offset + 14 + idx * 12]
code = ifd[0] + 256 * ifd[1]
if code not in (258, 281):
ifds.append(ifd)
ifds += [
# 12 bits/sample
np.array([2, 1, 3, 0, 1, 0, 0, 0, 12, 0, 0, 0], np.uint8),
# max value = 4095
np.array([25, 1, 3, 0, 1, 0, 0, 0, 255, 15, 0, 0], np.uint8)
]
ifds = sorted(ifds, cmp=(lambda a, b: cmp(a.tolist(), b.tolist())))
old_end = offset + 2 + nentries * 12
new_end = offset + 2 + len(ifds) * 12
diff = new_end - old_end
#
# Fix up the IFD offsets if greater than "offset"
#
for ifd in ifds:
count = np.frombuffer(ifd[4:8].data, np.uint32)[0]
if count > 4:
ifd_off = np.array([np.frombuffer(ifd[8:12].data, np.uint32)[0]
]) + diff
if ifd_off > offset:
ifd[8:12] = np.frombuffer(ifd_off.data, np.uint8)
new_data = np.zeros(len(data) + diff, np.uint8)
new_data[:offset] = data[:offset]
new_data[offset] = len(ifds) % 256
new_data[offset + 1] = int(len(ifds) / 256)
for idx, ifd in enumerate(ifds):
new_data[offset + 2 + idx * 12:offset + 14 + idx * 12] = ifd
new_data[new_end:] = data[old_end:]
with open(path, "wb") as fd:
fd.write(new_data.data)
return path
def run_create_webpage(self, image_paths, thumb_paths = None,
metadata = None, alter_fn = None):
'''Run the create_webpage module, returning the resulting HTML document
image_paths - list of path / filename tuples. The function will
write an image to each of these and put images and
measurements into the workspace for each.
thumb_paths - if present a list of path / filename tuples. Same as above
metadata - a dictionary of feature / string values
alter_fn - function taking a CreateWebPage module, for you to
alter the module's settings
'''
np.random.seed(0)
module = C.CreateWebPage()
module.module_num = 1
module.orig_image_name.value = IMAGE_NAME
module.web_page_file_name.value = DEFAULT_HTML_FILE
if alter_fn is not None:
alter_fn(module)
pipeline = cpp.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
pipeline.add_module(module)
images = [ (IMAGE_NAME, image_paths)]
if thumb_paths:
images += [ (THUMB_NAME, thumb_paths)]
self.assertEqual(len(image_paths), len(thumb_paths))
module.wants_thumbnails.value = True
module.thumbnail_image_name.value = THUMB_NAME
else:
module.wants_thumbnails.value = False
measurements = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module,
measurements, None, measurements,
None, None)
for i in range(len(image_paths)):
image_number = i+1
if metadata is not None:
for key in metadata.keys():
values = metadata[key]
feature = cpmeas.C_METADATA + "_" + key
measurements[cpmeas.IMAGE, feature, image_number] = values[i]
for image_name, paths in images:
pixel_data = np.random.uniform(size=(10,13))
path_name, file_name = paths[i]
if path_name is None:
path_name = cpprefs.get_default_image_directory()
is_file = True
elif path_name.lower().startswith("http"):
is_file = False
url = path_name + "/" + file_name
if "?" in file_name:
file_name = file_name.split("?", 1)[0]
if is_file:
full_path = os.path.abspath(os.path.join(
self.directory, path_name, file_name))
url = pathname2url(full_path)
path = os.path.split(full_path)[0]
else:
full_path = url
path = path_name
if is_file:
write_image(full_path, pixel_data, PT_UINT8)
path_feature = '_'.join((C_PATH_NAME, image_name))
file_feature = '_'.join((C_FILE_NAME, image_name))
url_feature = '_'.join((C_URL, image_name))
measurements[cpmeas.IMAGE, path_feature, image_number] = \
path
measurements[cpmeas.IMAGE, file_feature, image_number] =\
file_name
measurements[cpmeas.IMAGE, url_feature, image_number] = url
module.post_run(workspace)
return measurements
def run_as_data_tool(self):
from cellprofiler.gui.editobjectsdlg import EditObjectsDialog
import wx
from wx.lib.filebrowsebutton import FileBrowseButton
from cellprofiler.modules.namesandtypes import ObjectsImageProvider
from bioformats import load_image
with wx.Dialog(None) as dlg:
dlg.Title = "Choose files for editing"
dlg.Sizer = wx.BoxSizer(wx.VERTICAL)
sub_sizer = wx.BoxSizer(wx.HORIZONTAL)
dlg.Sizer.Add(sub_sizer, 0, wx.EXPAND | wx.ALL, 5)
new_or_existing_rb = wx.RadioBox(dlg,
style=wx.RA_VERTICAL,
choices=("New", "Existing"))
sub_sizer.Add(new_or_existing_rb, 0, wx.EXPAND)
objects_file_fbb = FileBrowseButton(
dlg,
size=(300, -1),
fileMask=
"Objects file (*.tif, *.tiff, *.png, *.bmp, *.jpg)|*.tif;*.tiff;*.png;*.bmp;*.jpg",
dialogTitle="Select objects file",
labelText="Objects file:",
)
objects_file_fbb.Enable(False)
sub_sizer.AddSpacer(5)
sub_sizer.Add(objects_file_fbb, 0, wx.ALIGN_TOP | wx.ALIGN_RIGHT)
def on_radiobox(event):
objects_file_fbb.Enable(new_or_existing_rb.GetSelection() == 1)
new_or_existing_rb.Bind(wx.EVT_RADIOBOX, on_radiobox)
image_file_fbb = FileBrowseButton(
dlg,
size=(300, -1),
fileMask=
"Objects file (*.tif, *.tiff, *.png, *.bmp, *.jpg)|*.tif;*.tiff;*.png;*.bmp;*.jpg",
dialogTitle="Select guide image file",
labelText="Guide image:",
)
dlg.Sizer.Add(image_file_fbb, 0, wx.EXPAND | wx.ALL, 5)
allow_overlap_checkbox = wx.CheckBox(dlg, -1,
"Allow objects to overlap")
allow_overlap_checkbox.Value = True
dlg.Sizer.Add(allow_overlap_checkbox, 0, wx.EXPAND | wx.ALL, 5)
buttons = wx.StdDialogButtonSizer()
dlg.Sizer.Add(buttons, 0,
wx.ALIGN_CENTER_VERTICAL | wx.ALIGN_RIGHT | wx.ALL,
5)
buttons.Add(wx.Button(dlg, wx.ID_OK))
buttons.Add(wx.Button(dlg, wx.ID_CANCEL))
buttons.Realize()
dlg.Fit()
result = dlg.ShowModal()
if result != wx.ID_OK:
return
self.allow_overlap.value = allow_overlap_checkbox.Value
fullname = objects_file_fbb.GetValue()
guidename = image_file_fbb.GetValue()
if new_or_existing_rb.GetSelection() == 1:
provider = ObjectsImageProvider("InputObjects",
pathname2url(fullname), None, None)
image = provider.provide_image(None)
pixel_data = image.pixel_data
shape = pixel_data.shape[:2]
labels = [pixel_data[:, :, i] for i in range(pixel_data.shape[2])]
else:
labels = None
#
# Load the guide image
#
guide_image = load_image(guidename)
if np.min(guide_image) != np.max(guide_image):
guide_image = (guide_image - np.min(guide_image)) / (
np.max(guide_image) - np.min(guide_image))
if labels is None:
shape = guide_image.shape[:2]
labels = [np.zeros(shape, int)]
with EditObjectsDialog(guide_image, labels, self.allow_overlap,
self.object_name.value) as dialog_box:
result = dialog_box.ShowModal()
if result != wx.OK:
return
labels = dialog_box.labels
n_frames = len(labels)
with wx.FileDialog(None,
style=wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT) as dlg:
dlg.Path = fullname
dlg.Wildcard = ("Object image file (*.tif,*.tiff)|*.tif;*.tiff|"
"Ilastik project file (*.ilp)|*.ilp")
result = dlg.ShowModal()
fullname = dlg.Path
if result == wx.ID_OK:
if fullname.endswith(".ilp"):
self.save_into_ilp(fullname, labels, guidename)
else:
from bioformats.formatwriter import write_image
from bioformats.omexml import PT_UINT16
if os.path.exists(fullname):
os.unlink(fullname)
for i, l in enumerate(labels):
write_image(fullname,
l,
PT_UINT16,
t=i,
size_t=len(labels))
def run_create_webpage(self, image_paths, thumb_paths=None,
metadata=None, alter_fn=None):
'''Run the create_webpage module, returning the resulting HTML document
image_paths - list of path / filename tuples. The function will
write an image to each of these and put images and
measurements into the workspace for each.
thumb_paths - if present a list of path / filename tuples. Same as above
metadata - a dictionary of feature / string values
alter_fn - function taking a CreateWebPage module, for you to
alter the module's settings
'''
np.random.seed(0)
module = C.CreateWebPage()
module.module_num = 1
module.orig_image_name.value = IMAGE_NAME
module.web_page_file_name.value = DEFAULT_HTML_FILE
if alter_fn is not None:
alter_fn(module)
pipeline = cpp.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
pipeline.add_module(module)
images = [(IMAGE_NAME, image_paths)]
if thumb_paths:
images += [(THUMB_NAME, thumb_paths)]
self.assertEqual(len(image_paths), len(thumb_paths))
module.wants_thumbnails.value = True
module.thumbnail_image_name.value = THUMB_NAME
else:
module.wants_thumbnails.value = False
measurements = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module,
measurements, None, measurements,
None, None)
for i in range(len(image_paths)):
image_number = i + 1
if metadata is not None:
for key in metadata.keys():
values = metadata[key]
feature = cpmeas.C_METADATA + "_" + key
measurements[cpmeas.IMAGE, feature, image_number] = values[i]
for image_name, paths in images:
pixel_data = np.random.uniform(size=(10, 13))
path_name, file_name = paths[i]
if path_name is None:
path_name = cpprefs.get_default_image_directory()
is_file = True
elif path_name.lower().startswith("http"):
is_file = False
url = path_name + "/" + file_name
if "?" in file_name:
file_name = file_name.split("?", 1)[0]
if is_file:
full_path = os.path.abspath(os.path.join(
self.directory, path_name, file_name))
url = pathname2url(full_path)
path = os.path.split(full_path)[0]
else:
full_path = url
path = path_name
if is_file:
write_image(full_path, pixel_data, PT_UINT8)
path_feature = '_'.join((C_PATH_NAME, image_name))
file_feature = '_'.join((C_FILE_NAME, image_name))
url_feature = '_'.join((C_URL, image_name))
measurements[cpmeas.IMAGE, path_feature, image_number] = \
path
measurements[cpmeas.IMAGE, file_feature, image_number] = \
file_name
measurements[cpmeas.IMAGE, url_feature, image_number] = url
module.post_run(workspace)
return measurements
def run_as_data_tool(self):
from cellprofiler.gui.editobjectsdlg import EditObjectsDialog
import wx
from wx.lib.filebrowsebutton import FileBrowseButton
from cellprofiler.modules.namesandtypes import ObjectsImageProvider
from bioformats import load_image
with wx.Dialog(None) as dlg:
dlg.Title = "Choose files for editing"
dlg.Sizer = wx.BoxSizer(wx.VERTICAL)
box = wx.StaticBox(dlg, -1, "Choose or create new objects file")
sub_sizer = wx.StaticBoxSizer(box, wx.HORIZONTAL)
dlg.Sizer.Add(sub_sizer, 0, wx.EXPAND | wx.ALL, 5)
new_or_existing_rb = wx.RadioBox(dlg, style=wx.RA_VERTICAL,
choices = ("New", "Existing"))
sub_sizer.Add(new_or_existing_rb, 0, wx.EXPAND)
objects_file_fbb = FileBrowseButton(
dlg, size=(300, -1),
fileMask="Objects file (*.tif, *.tiff, *.png, *.bmp, *.jpg)|*.tif;*.tiff;*.png;*.bmp;*.jpg",
dialogTitle="Select objects file",
labelText="Objects file:")
objects_file_fbb.Enable(False)
sub_sizer.AddSpacer(5)
sub_sizer.Add(objects_file_fbb, 0, wx.ALIGN_TOP | wx.ALIGN_RIGHT)
def on_radiobox(event):
objects_file_fbb.Enable(new_or_existing_rb.GetSelection() == 1)
new_or_existing_rb.Bind(wx.EVT_RADIOBOX, on_radiobox)
image_file_fbb = FileBrowseButton(
dlg, size=(300, -1),
fileMask="Objects file (*.tif, *.tiff, *.png, *.bmp, *.jpg)|*.tif;*.tiff;*.png;*.bmp;*.jpg",
dialogTitle="Select guide image file",
labelText="Guide image:")
dlg.Sizer.Add(image_file_fbb, 0, wx.EXPAND | wx.ALL, 5)
allow_overlap_checkbox = wx.CheckBox(dlg, -1, "Allow objects to overlap")
allow_overlap_checkbox.Value = True
dlg.Sizer.Add(allow_overlap_checkbox, 0, wx.EXPAND | wx.ALL, 5)
buttons = wx.StdDialogButtonSizer()
dlg.Sizer.Add(buttons, 0, wx.ALIGN_CENTER_VERTICAL | wx.ALIGN_RIGHT | wx.ALL, 5)
buttons.Add(wx.Button(dlg, wx.ID_OK))
buttons.Add(wx.Button(dlg, wx.ID_CANCEL))
buttons.Realize()
dlg.Fit()
result = dlg.ShowModal()
if result != wx.ID_OK:
return
self.allow_overlap.value = allow_overlap_checkbox.Value
fullname = objects_file_fbb.GetValue()
guidename = image_file_fbb.GetValue()
if new_or_existing_rb.GetSelection() == 1:
provider = ObjectsImageProvider(
"InputObjects",
pathname2url(fullname),
None, None)
image = provider.provide_image(None)
pixel_data = image.pixel_data
shape = pixel_data.shape[:2]
labels = [pixel_data[:, :, i] for i in range(pixel_data.shape[2])]
else:
labels = None
#
# Load the guide image
#
guide_image = load_image(guidename)
if np.min(guide_image) != np.max(guide_image):
guide_image = ((guide_image - np.min(guide_image)) /
(np.max(guide_image) - np.min(guide_image)))
if labels is None:
shape = guide_image.shape[:2]
labels = [np.zeros(shape, int)]
with EditObjectsDialog(
guide_image, labels,
self.allow_overlap, self.object_name.value) as dialog_box:
result = dialog_box.ShowModal()
if result != wx.OK:
return
labels = dialog_box.labels
n_frames = len(labels)
with wx.FileDialog(None,
style = wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT) as dlg:
dlg.Path = fullname
dlg.Wildcard = ("Object image file (*.tif,*.tiff)|*.tif;*.tiff|"
"Ilastik project file (*.ilp)|*.ilp")
result = dlg.ShowModal()
fullname = dlg.Path
if result == wx.ID_OK:
if fullname.endswith(".ilp"):
self.save_into_ilp(fullname, labels, guidename)
else:
from bioformats.formatwriter import write_image
from bioformats.omexml import PT_UINT16
if os.path.exists(fullname):
os.unlink(fullname)
for i, l in enumerate(labels):
write_image(fullname, l, PT_UINT16,
t = i, size_t = len(labels))
