def __init__(
self,
image=None,
image_file=None,
image_cell_vertex_file=None,
triangulation_file=None,
reconstruction_triangulation=["star", "split", "projected", "flat"],
):
"""Initialize the DRACO object by providing a segmented image.
Image can be passed either as an object of a filename. Cell adjacency information will be extracted from image
at initialization, still, some time can always be saved: if previously extracted, it can be read from existing
file; if not the extrcted information will be saved in the specified files.
Args:
image (SpatialImage): a (non-eroded) segmented label image
image_file (str): a valid path to an image of readable type (.inr, .inr.gz, .tiff...) :
image_cell_vertex_file (str): file to read from if cell-vertices have already been extracted
triangulation_file (str): file to load from if an already existing adjacency complex is to be used
reconstruction_triangulation (list): default values for dual reconstruction triangulation (see dual_reconstruction for more details)
Returns:
None
"""
if image is not None:
self.segmented_image = deepcopy(image)
else:
self.segmented_image = imread(image_file)
self.segmented_image[self.segmented_image == 0] = 1
self.resolution = np.array(self.segmented_image.resolution)
self.size = np.array(self.segmented_image.shape)
self.triangulation_topomesh = None
self.image_graph = None
if image_cell_vertex_file is not None:
try:
self.image_cell_vertex = pickle.load(open(image_cell_vertex_file, "rb"))
except:
self.image_cell_vertex = cell_vertex_extraction(self.segmented_image)
pickle.dump(self.image_cell_vertex, open(image_cell_vertex_file, "wb"))
else:
self.image_cell_vertex = cell_vertex_extraction(self.segmented_image)
self.image_cell_vertex_topomesh = None
self.positions = None
self.cell_layer = None
self.image_labels = None
self.image_cell_volumes = None
self.image_wall_surfaces = None
self.point_topomesh = None
self.delaunay_topomesh = None
self.optimized_delaunay_topomesh = None
self.surface_topomesh = None
self.reconstruction_triangulation = reconstruction_triangulation
self.dual_reconstruction_topomesh = None
self.compute_image_adjacency()
if triangulation_file is not None:
try:
topomesh = pickle.load(open(triangulation_file, "rb"))
self.triangulation_topomesh = topomesh
except:
print "Impossible to load adjacency complex topomesh : FileNotFound ", triangulation_file
inputfile = dirname+"/segmented_images/"+filename+".inr.gz" size = 100. #n_points = int((4.*np.power(size/4.,2.))/(np.power(15.,2))) n_points = 21 print size," -> ",n_points img = sphere_tissue_image(size=size, n_points=n_points) imsave(inputfile,img) #inputfile = "/Users/gcerutti/Developpement/openalea/openalea_marsalt/example/time_0_cut_seg_median.inr" img = imread(inputfile) #img[img==0]=1 #img = SpatialImage(np.concatenate([img[:,:,35:],np.ones((img.shape[0],img.shape[1],5))],axis=2).astype(np.uint16),resolution=img.resolution) cell_vertex_file = dirname+"/output_meshes/"+filename+"/image_cell_vertex.dict" triangulation_file = dirname+"/output_meshes/"+filename+"/"+filename+"_draco_adjacency_complex.pkl" from openalea.container import array_dict world.add(img,"segmented_image",colormap='glasbey',alphamap='constant',bg_id=1,alpha=1.0) #draco = DracoMesh(image=img, image_cell_vertex_file=cell_vertex_file, triangulation_file=triangulation_file) #draco = DracoMesh(image_file=inputfile, image_cell_vertex_file=cell_vertex_file) draco = DracoMesh(image=img)
def _draco_control_changed(self, control_name, old, new):
print control_name, " changed! : ", new
control_names = [c['name'] for c in self._controls]
self._controls[control_names.index(control_name)]['value'] = new
if control_name == 'img_filename':
img_file = new
try:
img = imread(img_file)
assert img.ndim == 3
except:
print "Image type not recognized! Please choose a different file..."
set_default_control(self._controls, 'initialize')
else:
self.name = os.path.split(img_file)[-1].split('.')[0]
set_default_control(self._controls,
'initialize',
value=self._init_button_pressed)
elif control_name == 'display_img':
if new:
self.world.add(self.draco.segmented_image,
self.name + '_segmented_image',
colormap='glasbey',
alphamap='constant',
bg_id=1)
else:
if self.world.has_key(self.name + '_segmented_image'):
self.world.remove(self.name + '_segmented_image')
elif control_name == 'display_cells':
if new:
self.world.add(self.draco.point_topomesh,
self.name + '_image_cells')
self.world[self.name + '_image_cells_vertices'].set_attribute(
'point_radius', self.draco.segmented_image.max())
self.world[self.name + '_image_cells_vertices'].set_attribute(
'display_colorbar', False)
else:
if self.world.has_key(self.name + '_image_cells'):
self.world.remove(self.name + '_image_cells')
elif control_name == 'display_adjacency':
control_names = [c['name'] for c in self._controls]
adjacency_complex = self._controls[control_names.index(
'adjacency_complex')]['value']
if adjacency_complex in ['delaunay', 'L1-L2']:
degree = 3
else:
degree = 2
if new:
self.world.add(self.draco.triangulation_topomesh,
self.name + '_adjacency_complex')
if degree == 3:
self.world[self.name +
'_adjacency_complex_cells'].set_attribute(
'polydata_colormap',
load_colormaps()['grey'])
self.world[self.name +
'_adjacency_complex_cells'].set_attribute(
'intensity_range', (-1, 0))
self.world[self.name + '_adjacency_complex'].set_attribute(
'coef_3', 0.95)
self.world[self.name +
'_adjacency_complex_cells'].set_attribute(
'display_colorbar', False)
else:
self.world[self.name + '_adjacency_complex'].set_attribute(
'display_3', False)
self.world[self.name + '_adjacency_complex'].set_attribute(
'display_2', True)
self.world[self.name +
'_adjacency_complex_faces'].set_attribute(
'polydata_colormap',
load_colormaps()['grey'])
self.world[self.name +
'_adjacency_complex_faces'].set_attribute(
'intensity_range', (-1, 0))
self.world[self.name + '_adjacency_complex'].set_attribute(
'coef_2', 0.98)
self.world[self.name +
'_adjacency_complex_faces'].set_attribute(
'display_colorbar', False)
else:
if self.world.has_key(self.name + '_adjacency_complex'):
self.world.remove(self.name + '_adjacency_complex')
elif control_name == 'display_dual':
if new:
self.world.add(self.draco.dual_reconstruction_topomesh,
self.name + '_dual_reconstruction')
else:
if self.world.has_key(self.name + '_dual_reconstruction'):
self.world.remove(self.name + '_dual_reconstruction')
elif control_name == 'adjacency_complex':
if new == '':
print "Please define a mode for adjacency complex computation"
set_default_control(self._controls, 'compute_adjacency')
else:
set_default_control(
self._controls,
'compute_adjacency',
value=self._compute_adjacency_button_pressed)
self.refresh_manager()
def _draco_control_changed(self, control_name, old, new):
print control_name," changed! : ",new
control_names = [c['name'] for c in self._controls]
self._controls[control_names.index(control_name)]['value'] = new
if control_name == 'img_filename':
img_file = new
try:
img = imread(img_file)
assert img.ndim == 3
except:
print "Image type not recognized! Please choose a different file..."
set_default_control(self._controls,'initialize')
else:
self.name = os.path.split(img_file)[-1].split('.')[0]
set_default_control(self._controls,'initialize',value=self._init_button_pressed)
elif control_name == 'display_img':
if new:
self.world.add(self.draco.segmented_image,self.name+'_segmented_image',colormap='glasbey',alphamap='constant',bg_id=1)
else:
if self.world.has_key(self.name+'_segmented_image'):
self.world.remove(self.name+'_segmented_image')
elif control_name == 'display_cells':
if new:
self.world.add(self.draco.point_topomesh,self.name+'_image_cells')
self.world[self.name+'_image_cells_vertices'].set_attribute('point_radius',self.draco.segmented_image.max())
self.world[self.name+'_image_cells_vertices'].set_attribute('display_colorbar',False)
else:
if self.world.has_key(self.name+'_image_cells'):
self.world.remove(self.name+'_image_cells')
elif control_name == 'display_adjacency':
control_names = [c['name'] for c in self._controls]
adjacency_complex = self._controls[control_names.index('adjacency_complex')]['value']
if adjacency_complex in ['delaunay','L1-L2']:
degree = 3
else:
degree = 2
if new:
self.world.add(self.draco.triangulation_topomesh,self.name+'_adjacency_complex')
if degree == 3:
self.world[self.name+'_adjacency_complex_cells'].set_attribute('polydata_colormap',load_colormaps()['grey'])
self.world[self.name+'_adjacency_complex_cells'].set_attribute('intensity_range',(-1,0))
self.world[self.name+'_adjacency_complex'].set_attribute('coef_3',0.95)
self.world[self.name+'_adjacency_complex_cells'].set_attribute('display_colorbar',False)
else:
self.world[self.name+'_adjacency_complex'].set_attribute('display_3',False)
self.world[self.name+'_adjacency_complex'].set_attribute('display_2',True)
self.world[self.name+'_adjacency_complex_faces'].set_attribute('polydata_colormap',load_colormaps()['grey'])
self.world[self.name+'_adjacency_complex_faces'].set_attribute('intensity_range',(-1,0))
self.world[self.name+'_adjacency_complex'].set_attribute('coef_2',0.98)
self.world[self.name+'_adjacency_complex_faces'].set_attribute('display_colorbar',False)
else:
if self.world.has_key(self.name+'_adjacency_complex'):
self.world.remove(self.name+'_adjacency_complex')
elif control_name == 'display_dual':
if new:
self.world.add(self.draco.dual_reconstruction_topomesh,self.name+'_dual_reconstruction')
else:
if self.world.has_key(self.name+'_dual_reconstruction'):
self.world.remove(self.name+'_dual_reconstruction')
elif control_name == 'adjacency_complex':
if new == '':
print "Please define a mode for adjacency complex computation"
set_default_control(self._controls,'compute_adjacency')
else:
set_default_control(self._controls,'compute_adjacency',value=self._compute_adjacency_button_pressed)
self.refresh_manager()
#filename = "segmentation"
#filename = "olli01_lti6b_150421_sam01_t000_seg_hmin_2"
#filename = "sphere_cells"
filename = "yr02_t132_seg"
dirname = '/Users/gcerutti/Developpement/openalea/openalea_meshing_data/share/data/'
#dirname = shared_data(vplants.meshing_data)
#meshing_dirname = dirname.parent.parent
import os
if not os.path.exists(dirname + "/output_meshes/" + filename):
os.makedirs(dirname + "/output_meshes/" + filename)
inputfile = dirname + "/segmented_images/" + filename + ".inr.gz"
img = imread(inputfile)
#img[img==0]=1
#img = SpatialImage(np.concatenate([img[:,:,35:],np.ones((img.shape[0],img.shape[1],5))],axis=2).astype(np.uint16),voxelsize=img.voxelsize)
cell_vertex_file = dirname + "/output_meshes/" + filename + "/image_cell_vertex.dict"
triangulation_file = dirname + "/output_meshes/" + filename + "/" + filename + "_draco_adjacency_complex.pkl"
from openalea.container import array_dict
world.add(img,
"segmented_image",
colormap='glasbey',
alphamap='constant',
bg_id=1,
alpha=1.0)
import numpy as np
from openalea.image.serial.all import imread
from openalea.cellcomplex.property_topomesh.utils.tissue_analysis_tools import cell_vertex_extraction
from openalea.cellcomplex.property_topomesh.property_topomesh_creation import tetrahedra_topomesh
from vplants.tissue_analysis.temporal_graph_from_image import graph_from_image
from openalea.oalab.colormap.colormap_def import load_colormaps
# filename = "/Users/gcerutti/Developpement/d-tk/gnomon-data/0hrs_plant1_seg_small.inr"
filename = "/data/Yassin/YR_01_ATLAS_iso/segmentations/t10_segmented_new_clean_2.tif"
background_adjacency = False
img = imread(filename)
if 'world' in dir():
world.add(img,
'segmented_image',
colormap='glasbey',
alphamap='constant',
alpha=0.2)
cell_vertex = cell_vertex_extraction(img)
tetras = np.array(cell_vertex.keys())
img_graph = graph_from_image(
img,
spatio_temporal_properties=['barycenter', 'volume'],
ignore_cells_at_stack_margins=True)
positions = img_graph.vertex_property('barycenter')
