def crop(self, tmpcrinfo):
"""
Function makes crop of 3d data and seeds and stores it in crinfo.
tmpcrinfo: temporary crop information
"""
# print ('sedds ', str(self.seeds.shape), ' se ',
# str(self.segmentation.shape), ' d3d ', str(self.data3d.shape))
self.data3d = qmisc.crop(self.data3d, tmpcrinfo)
# No, size of seeds should be same as data3d
if self.seeds is not None:
self.seeds = qmisc.crop(self.seeds, tmpcrinfo)
if self.segmentation is not None:
self.segmentation = qmisc.crop(self.segmentation, tmpcrinfo)
self.crinfo = qmisc.combinecrinfo(self.crinfo, tmpcrinfo)
logger.debug("crinfo " + str(self.crinfo))
def test_multiple_crop_and_uncrop(self):
"""
test combination of multiple crop
"""
shape = [10, 10, 5]
img_in = np.random.random(shape)
crinfo1 = [[2, 8], [3, 9], [2, 5]]
crinfo2 = [[2, 5], [1, 4], [1, 2]]
img_cropped = qmisc.crop(img_in, crinfo1)
img_cropped = qmisc.crop(img_cropped, crinfo2)
crinfo_combined = qmisc.combinecrinfo(crinfo1, crinfo2)
img_uncropped = qmisc.uncrop(img_cropped, crinfo_combined, shape)
self.assertTrue(img_uncropped[4, 4, 3] == img_in[4, 4, 3])
def _interactivity_end(self, igc):
logger.debug('_interactivity_end')
#print "sh3", self.data3d.shape
# import pdb; pdb.set_trace()
# scipy.ndimage.zoom(
# self.segmentation,
# 1.0 / self.zoom,
# output=segm_orig_scale,
# mode='nearest',
# order=0
# )
segm_orig_scale = scipy.ndimage.zoom(
self.segmentation,
1.0 / self.zoom,
mode='nearest',
order=0
).astype(np.int8)
seeds = scipy.ndimage.zoom(
igc.seeds,
1.0 / self.zoom,
mode='nearest',
order=0
)
#print np.sum(self.segmentation)*np.prod(self.voxelsize_mm)
# @TODO odstranit hack pro oříznutí na stejnou velikost
# v podstatě je to vyřešeno, ale nechalo by se to dělat elegantněji v zoom
# tam je bohužel patrně bug
shp = [
np.min([segm_orig_scale.shape[0], self.data3d.shape[0]]),
np.min([segm_orig_scale.shape[1], self.data3d.shape[1]]),
np.min([segm_orig_scale.shape[2], self.data3d.shape[2]]),
]
#self.data3d = self.data3d[0:shp[0], 0:shp[1], 0:shp[2]]
self.segmentation = np.zeros(self.data3d.shape, dtype=np.int8)
self.segmentation[
0:shp[0],
0:shp[1],
0:shp[2]] = segm_orig_scale[0:shp[0], 0:shp[1], 0:shp[2]]
del segm_orig_scale
self.iparams['seeds'] = np.zeros(self.data3d.shape, dtype=np.int8)
self.iparams['seeds'][
0:shp[0],
0:shp[1],
0:shp[2]] = seeds[0:shp[0], 0:shp[1], 0:shp[2]]
#
if self.segmentation_smoothing:
self.segm_smoothing(self.smoothing_mm)
#print 'crinfo: ', self.crinfo
#print 'autocrop', self.autocrop
if self.autocrop is True:
#print
#import pdb; pdb.set_trace()
tmpcrinfo = self._crinfo_from_specific_data(
self.segmentation,
self.autocrop_margin)
self.segmentation = self._crop(self.segmentation, tmpcrinfo)
self.data3d = self._crop(self.data3d, tmpcrinfo)
self.crinfo = qmisc.combinecrinfo(self.crinfo, tmpcrinfo)
if self.texture_analysis not in (None, False):
import texture_analysis
# doplnit nějaký kód, parametry atd
#self.orig_scale_segmentation =
# texture_analysis.segmentation(self.data3d,
# self.orig_scale_segmentation, params = self.texture_analysis)
self.segmentation = texture_analysis.segmentation(
self.data3d,
self.segmentation,
self.voxelsize_mm
)
# set label number
self.segmentation[self.segmentation == 1] = self.output_label
#
self.processing_time = time.time() - self.time_start