def prepare_submission():
from cremi.io import CremiFile
from cremi.Volume import Volume
base = "/home/fabian/drives/datasets/results/nnUNet/test_sets/Task061_CREMI/"
# a+
pred = sitk.GetArrayFromImage(
sitk.ReadImage(join(base, 'results_3d_fullres',
"sample_a+.nii.gz"))).astype(np.uint64)
pred[pred == 0] = 0xffffffffffffffff
out_a = CremiFile(join(base, 'sample_A+_20160601.hdf'), 'w')
clefts = Volume(pred, (40., 4., 4.))
out_a.write_clefts(clefts)
out_a.close()
pred = sitk.GetArrayFromImage(
sitk.ReadImage(join(base, 'results_3d_fullres',
"sample_b+.nii.gz"))).astype(np.uint64)
pred[pred == 0] = 0xffffffffffffffff
out_b = CremiFile(join(base, 'sample_B+_20160601.hdf'), 'w')
clefts = Volume(pred, (40., 4., 4.))
out_b.write_clefts(clefts)
out_b.close()
pred = sitk.GetArrayFromImage(
sitk.ReadImage(join(base, 'results_3d_fullres',
"sample_c+.nii.gz"))).astype(np.uint64)
pred[pred == 0] = 0xffffffffffffffff
out_c = CremiFile(join(base, 'sample_C+_20160601.hdf'), 'w')
clefts = Volume(pred, (40., 4., 4.))
out_c.write_clefts(clefts)
out_c.close()
# Create some dummy annotation data
annotations = Annotations()
for id in [ 0, 1, 2, 3 ]:
location = (random.randint(0, 100), random.randint(0, 100), random.randint(0, 100))
annotations.add_annotation(id, "presynaptic_site", location)
for id in [ 4, 5, 6, 7 ]:
location = (random.randint(0, 100), random.randint(0, 100), random.randint(0, 100))
annotations.add_annotation(id, "postsynaptic_site", location)
for (pre, post) in [ (0, 4), (1, 5), (2, 6), (3, 7) ]:
annotations.set_pre_post_partners(pre, post)
annotations.add_comment(6, "unsure")
# Open a file for writing (deletes previous file, if exists)
file = CremiFile("example.hdf", "w")
# Write the raw volume. This is given here just for illustration. For your
# submission, you don't need to store the raw data. We have it already.
raw = Volume(np.zeros((10,100,100), dtype=np.uint8), resolution=(40.0, 4.0, 4.0))
file.write_raw(raw)
# Write volumes representing the neuron and synaptic cleft segmentation.
neuron_ids = Volume(np.ones((10,100,100), dtype=np.uint64), resolution=(40.0, 4.0, 4.0), comment="just ones")
clefts = Volume(np.zeros((10,100,100), dtype=np.uint64), resolution=(40.0, 4.0, 4.0), comment="just zeros")
file.write_neuron_ids(neuron_ids)
file.write_clefts(clefts)
# Write synaptic partner annotations.
file.write_annotations(annotations)
file.close()
location = (random.randint(0, 100), random.randint(0, 100),
random.randint(0, 100))
annotations.add_annotation(id, "postsynaptic_site", location)
for (pre, post) in [(0, 4), (1, 5), (2, 6), (3, 7)]:
annotations.set_pre_post_partners(pre, post)
annotations.add_comment(6, "unsure")
# Open a file for writing (deletes previous file, if exists)
file = CremiFile("example.hdf", "w")
# Write the raw volume. This is given here just for illustration. For your
# submission, you don't need to store the raw data. We have it already.
raw = Volume(np.zeros((10, 100, 100), dtype=np.uint8),
resolution=(40.0, 4.0, 4.0))
file.write_raw(raw)
# Write volumes representing the neuron and synaptic cleft segmentation.
neuron_ids = Volume(np.ones((10, 100, 100), dtype=np.uint64),
resolution=(40.0, 4.0, 4.0),
comment="just ones")
clefts = Volume(np.zeros((10, 100, 100), dtype=np.uint64),
resolution=(40.0, 4.0, 4.0),
comment="just zeros")
file.write_neuron_ids(neuron_ids)
file.write_clefts(clefts)
# Write synaptic partner annotations.
file.write_annotations(annotations)
file.close()
