def run_onthisthread(self):
"""
Run the Zprojection
This is not in run, so we can bypass run() if we don't want to start a new thread
"""
print 'zproject thread id', QtCore.QThread.currentThreadId()
if os.path.isfile(self.zprojection_output) is False or self.force:
print "Computing z-projection..."
if len(self.imglist) < 1:
self.emit(QtCore.SIGNAL('update(QString)'), "No recon images found!")
reader = Imreader(self.imglist)
try:
im = reader.imread(self.imglist[0])
except HarpDataError as e:
self.update.emit(e.message) # emit back to differnt thread. or...
raise # reraise for autocrop, on same thread
imdims = im.shape
dtype = im.dtype
# make a new list by removing every nth image
sparse_filelist = sorted(self.imglist)[0::self.skip_num]
print "performing z-projection on sparse file list"
max_array = self.max_projection(sparse_filelist, imdims, dtype)
imwrite(self.zprojection_output, max_array)
self.emit(QtCore.SIGNAL('update(QString)'), "Z-projection finished")
def run_onthisthread(self):
"""
Run the Zprojection
This is not in run, so we can bypass run() if we don't want to start a new thread
"""
print 'zproject thread id', QtCore.QThread.currentThreadId()
if os.path.isfile(self.zprojection_output) is False or self.force:
print "Computing z-projection..."
if len(self.imglist) < 1:
self.emit(QtCore.SIGNAL('update(QString)'),
"No recon images found!")
reader = Imreader(self.imglist)
try:
im = reader.imread(self.imglist[0])
except HarpDataError as e:
self.update.emit(
e.message) # emit back to differnt thread. or...
raise # reraise for autocrop, on same thread
imdims = im.shape
dtype = im.dtype
# make a new list by removing every nth image
sparse_filelist = sorted(self.imglist)[0::self.skip_num]
print "performing z-projection on sparse file list"
max_array = self.max_projection(sparse_filelist, imdims, dtype)
imwrite(self.zprojection_output, max_array)
self.emit(QtCore.SIGNAL('update(QString)'), "Z-projection finished")
def run(self, auto=False):
"""
Perform a crop based on previously selected bounding box
:return:
"""
# Get list of files
#imglist = processing.getfilelist(self.in_dir)
imglist = self.app_data.getfilelist(self.in_dir)
if len(imglist) < 1:
raise HarpDataError("no image files found in " + self.in_dir)
if auto:
cb = self.auto_bounding_box(imglist)
#rearange as dims come in a differenbt order from the different methods
cropbox = (cb[2], cb[3], cb[0], cb[1])
else:
cropbox = self.calc_manual_crop()
cropbox = [cropbox[1], cropbox[3], cropbox[0],
cropbox[2]] # rearrange for numpy slicing
first = True
outpathslist = []
reader = Imreader(imglist)
for count, file_ in enumerate(imglist):
try:
im = reader.imread(file_)
except IOError as e:
raise HarpDataError("failed to read {}".format(file_))
else:
if im.shape[0] < 1 or im.shape[1] < 1:
raise HarpDataError('Cannot read file, {}'.format(file_))
if first:
dimcheck = im.shape
first = False
else:
if im.shape != dimcheck:
raise HarpDataError(
"Input files have different shapes {} and {}".format(
dimcheck, imglist[0], file_))
# try:
# pass
# #im[dimcheck] Check for indexing error as .shape is derived from header only
if count % 20 == 0:
if self.thread_terminate_flag.value == 1:
raise HarpDataError('Cancelled')
self.callback("Cropping: {0}/{1} images".format(
count, str(len(imglist))))
filename = os.path.basename(file_)
crop_out = os.path.join(self.out_dir, filename)
try:
imcrop = im[cropbox[0]:cropbox[1], cropbox[2]:cropbox[3]]
except IndexError as e:
raise HarpDataError(
"Crop box out of range. Is {} corrupted?".format(filename))
imwrite(crop_out, imcrop)
outpathslist.append(crop_out)
self.callback("success")
return outpathslist
def run(self, auto=False):
"""
Perform a crop based on previously selected bounding box
:return:
"""
# Get list of files
#imglist = processing.getfilelist(self.in_dir)
imglist = self.app_data.getfilelist(self.in_dir)
if len(imglist) < 1:
raise HarpDataError("no image files found in " + self.in_dir)
if auto:
cb = self.auto_bounding_box(imglist)
#rearange as dims come in a differenbt order from the different methods
cropbox = (cb[2], cb[3], cb[0], cb[1])
else:
cropbox = self.calc_manual_crop()
cropbox = [cropbox[1], cropbox[3], cropbox[0], cropbox[2]] # rearrange for numpy slicing
first = True
outpathslist = []
reader = Imreader(imglist)
for count, file_ in enumerate(imglist):
try:
im = reader.imread(file_)
except IOError as e:
raise HarpDataError("failed to read {}".format(file_))
else:
if im.shape[0] < 1 or im.shape[1] < 1:
raise HarpDataError('Cannot read file, {}'.format(file_))
if first:
dimcheck = im.shape
first = False
else:
if im.shape != dimcheck:
raise HarpDataError("Input files have different shapes {} and {}".
format(dimcheck, imglist[0], file_))
# try:
# pass
# #im[dimcheck] Check for indexing error as .shape is derived from header only
if count % 20 == 0:
if self.thread_terminate_flag.value == 1:
raise HarpDataError('Cancelled')
self.callback(
"Cropping: {0}/{1} images".format(count, str(len(imglist))))
filename = os.path.basename(file_)
crop_out = os.path.join(self.out_dir, filename)
try:
imcrop = im[cropbox[0]:cropbox[1], cropbox[2]: cropbox[3]]
except IndexError as e:
raise HarpDataError("Crop box out of range. Is {} corrupted?".format(filename))
imwrite(crop_out, imcrop)
outpathslist.append(crop_out)
self.callback("success")
return outpathslist
