def make_seg_submission(seg_valume_dict):
submission_folder = 'submission'
if not os.path.exists(submission_folder):
os.makedirs(submission_folder)
for name, seg_v in seg_valume_dict.iteritems():
seg_v = seg_v.astype(np.uint64)
neuron_ids = Volume(seg_v,
resolution=(40.0, 4.0, 4.0),
comment="Second submission in 2018")
file = CremiFile(submission_folder + '/' + name + '.hdf', "w")
file.write_neuron_ids(neuron_ids)
def prepare_submission(sample,
path_segm,
inner_path_segm,
path_bbox_slice,
ds_factor=None):
"""
:param path_segm:
:param inner_path_segm:
:param path_bbox_slice: path to the csv file
:param ds_factor: for example (1, 2, 2)
"""
segm = segm_utils.readHDF5(path_segm, inner_path_segm)
bbox_data = np.genfromtxt(path_bbox_slice, delimiter=';', dtype='int')
assert bbox_data.shape[0] == segm.ndim and bbox_data.shape[1] == 2
# bbox_slice = tuple(slice(b_data[0], b_data[1]) for b_data in bbox_data)
if ds_factor is not None:
assert len(ds_factor) == segm.ndim
segm = zoom(segm, ds_factor, order=0)
padding = tuple(
(slc[0], shp - slc[1])
for slc, shp in zip(bbox_data, shape_padded_aligned_datasets[sample]))
padded_segm = np.pad(segm, pad_width=padding, mode="constant")
# Apply Constantin crop and then backalign:
cropped_segm = padded_segm[magic_bboxes[sample]]
tmp_file = path_segm.replace(".h5", "_submission_temp.hdf")
backalign_segmentation(sample,
cropped_segm,
tmp_file,
key="temp_data",
postprocess=False)
# Create a CREMI-style file ready to submit:
final_submission_path = path_segm.replace(".h5", "_submission.hdf")
file = CremiFile(final_submission_path, "w")
# Write volumes representing the neuron and synaptic cleft segmentation.
backaligned_segm = segm_utils.readHDF5(tmp_file, "temp_data")
neuron_ids = Volume(backaligned_segm.astype('uint64'),
resolution=(40.0, 4.0, 4.0),
comment="Emb-submission")
file.write_neuron_ids(neuron_ids)
file.close()
os.remove(tmp_file)
# 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()
