def SharedPreprocess(self, params, comm_title):
print('Annotator folder is being generated for', comm_title)
targ = Params()
targ.SetUserInfoAnnotator(params['Empty Folder for Annotator'])
if os.path.isdir(targ.surfaces_path) == False:
os.makedirs(targ.surfaces_path, exist_ok=True)
os.makedirs(targ.surfaces_whole_path, exist_ok=True)
if os.path.isdir(targ.skeletons_path) == False:
os.makedirs(targ.skeletons_path, exist_ok=True)
os.makedirs(targ.skeletons_whole_path, exist_ok=True)
if os.path.isdir(targ.volume_path) == False:
os.makedirs(targ.volume_path, exist_ok=True)
if os.path.isdir(targ.paint_path) == False:
os.makedirs(targ.paint_path, exist_ok=True)
return targ
def AnalyzeAnnotFile(self, params):
targ = Params()
targ.SetUserInfoAnnotator(params['Empty Folder for Annotator'])
surface_path = targ.surfaces_whole_path
paint_path = targ.paint_path
whole_mesh_filenames = glob.glob(os.path.join(surface_path, "*.stl"))
ids_volumes = {}
ph = params['Pitch in X (um)']
pw = params['Pitch in Y (um)']
pz = params['Pitch in Z (um)']
##
with h5py.File(targ.volume_file, 'r') as f:
ids_volume = f['volume'][()]
ids_volume = (ids_volume > 0).astype(np.int)
new_labels = np.zeros_like(ids_volume).astype(np.int)
##
## Load surface meshes
id = 1
whole_mesh_filename = os.path.join(surface_path,
str(id).zfill(10) + ".stl")
whole_mesh = trimesh.load(whole_mesh_filename)
surf_vertices = whole_mesh.vertices
surf_faces = whole_mesh.faces
surf_vertices[:, 0] /= pw
surf_vertices[:, 1] /= ph
surf_vertices[:, 2] /= pz
pitch = 1
whole_mesh_name_wo_ext = os.path.splitext(
os.path.basename(whole_mesh_filename))[0]
part_mesh_name_wildcard = os.path.normpath(
os.path.join(paint_path, whole_mesh_name_wo_ext + "-*.pickle"))
part_mesh_filenames = glob.glob(part_mesh_name_wildcard)
## Check whether painted meshes
if part_mesh_filenames == []:
return False
ids = []
for part_mesh_filename in part_mesh_filenames:
with open(part_mesh_filename, 'rb') as file:
data = pickle.load(file)
closed_mesh = self.GetClosedTrimesh(surf_vertices, surf_faces,
data['painted'])
if closed_mesh.volume is None:
continue
###
id = os.path.basename(part_mesh_filename)
id = os.path.splitext(id)[0]
id = int(id.split('-')[1])
print('ID: ', id, ', Volume:', closed_mesh.volume)
ids.append(id)
#filename = os.path.join(targ.paint_path, str(id).zfill(4)+'.stl')
#closed_mesh.export(file_obj=filename)
#continue
###
part_faces = closed_mesh.faces
part_verts = closed_mesh.vertices
unique_ids_verts = np.unique(np.ravel(part_faces))
unique_verts = part_verts[unique_ids_verts]
wmin = np.floor(np.min(unique_verts[:, 0])).astype(int)
hmin = np.floor(np.min(unique_verts[:, 1])).astype(int)
zmin = np.floor(np.min(unique_verts[:, 2])).astype(int)
wmax = np.floor(np.max(unique_verts[:, 0])).astype(int)
hmax = np.floor(np.max(unique_verts[:, 1])).astype(int)
zmax = np.floor(np.max(unique_verts[:, 2])).astype(int)
print('wmin, wmax, wdiff: ', wmin, wmax, wmax - wmin)
print('hmin, hmax, hdiff: ', hmin, hmax, hmax - hmin)
print('zmin, zmax, zdiff: ', zmin, zmax, zmax - zmin)
## Trimesh
# v = self.GetVolumeTrimesh(closed_mesh)
## PyVista
v = self.GetVolumePyVista(part_verts, part_faces, wmin, hmin, zmin,
wmax, hmax, zmax)
#print('dir(v) : ', dir(v))
#print('v.keys(): ', v.keys())
#print('v[12]: ', v[12])
wnum = v.shape[0]
hnum = v.shape[1]
znum = v.shape[2]
wmin += 1
hmin += 1
zmin += 1
print('wnum, hnum, znum : ', wnum, hnum, znum)
new_labels[wmin:wmin + wnum, hmin:hmin + hnum,
zmin:zmin + znum] += v.astype(np.int) * id
####
#### Dilution, clarification, etc
####
new_labels_processed = np.zeros_like(ids_volume)
for id in ids:
## Pickup the target area
print('Dilution, id: ', id)
target_area = morphology.binary_dilation(new_labels == id,
selem=morphology.ball(1),
out=None).astype(np.int)
## Pickup segmented areas
labels_to_pickup_segmentation = morphology.label(
ids_volume * (target_area == 0))
us, counts = np.unique(labels_to_pickup_segmentation,
return_counts=True)
#print('us : ', us)
#print('segmentation count: ', counts)
segmented_us = us[counts < 30]
#print('segmented us : ', segmented_us)
segments = np.zeros_like(ids_volume)
for segmented_u in segmented_us:
segments += (
labels_to_pickup_segmentation == segmented_u).astype(
np.int)
## Merge target area with segmented areas if they are connected.
target_plus_segment = target_area * ids_volume + segments
labels_to_remove_segmented_target = morphology.label(
target_plus_segment > 0)
u, counts = np.unique(labels_to_remove_segmented_target,
return_counts=True)
labels_segmented_target_removed = (
labels_to_remove_segmented_target == u[counts.argsort()[-2]]
).astype(np.int)
## Assign the id to (target area in cytosol) and (segmented area).
new_labels_processed += labels_segmented_target_removed * id
with h5py.File('labels.hdf5', 'w') as f:
f.create_dataset('dendrite', data=new_labels_processed)
with h5py.File('labeled_cytosol.hdf5', 'w') as f:
f.create_dataset('dendrite',
data=new_labels_processed + ids_volume)
return ids_volume, new_labels
