def get_bounds(vol, bounds, mip, bounds_mip=0, chunk_size=None):
"""Return bounds of vol at mip, or snap bounds at src_mip to chunk_size
Args:
vol (CloudVolume)
bounds (Bbox-like object)
mip (int): mip level of returned bounds
bounds_mip (int): mip level of input bounds
chunk_size (Vec-like object): if bounds are set, can set chunk_size for snapping
Returns:
Bbox for bounds
"""
if bounds is None:
bounds = vol.meta.bounds(mip)
else:
bounds = Bbox.create(bounds)
bounds = vol.bbox_to_mip(bounds, mip=bounds_mip, to_mip=mip)
if chunk_size is not None:
bounds = bounds.expand_to_chunk_size(chunk_size,
vol.meta.voxel_offset(mip))
bounds = Bbox.clamp(bounds, vol.meta.bounds(mip))
print("Volume Bounds: ", vol.meta.bounds(mip))
print("Selected ROI: ", bounds)
return bounds
def crop(self, bbox):
"""
Crop away all vertices and edges that lie outside of the given bbox.
The edge counts as inside.
Returns: new PrecomputedSkeleton
"""
skeleton = self.clone()
bbox = Bbox.create(bbox)
if skeleton.empty():
return skeleton
nodes_valid_mask = np.array(
[bbox.contains(vtx) for vtx in skeleton.vertices], dtype=np.bool)
nodes_valid_idx = np.where(nodes_valid_mask)[0]
# Set invalid vertices to be duplicates
# so they'll be removed during consolidation
if nodes_valid_idx.shape[0] == 0:
return PrecomputedSkeleton()
first_node = nodes_valid_idx[0]
skeleton.vertices[~nodes_valid_mask] = skeleton.vertices[first_node]
edges_valid_mask = np.isin(skeleton.edges, nodes_valid_idx)
edges_valid_idx = edges_valid_mask[:, 0] * edges_valid_mask[:, 1]
skeleton.edges = skeleton.edges[edges_valid_idx, :]
return skeleton.consolidate()
def create_blackout_tasks(cloudpath: str,
bounds: Bbox,
mip: int = 0,
shape: ShapeType = (2048, 2048, 64),
value: int = 0,
non_aligned_writes: bool = False):
vol = CloudVolume(cloudpath, mip=mip)
shape = Vec(*shape)
bounds = Bbox.create(bounds)
bounds = vol.bbox_to_mip(bounds, mip=0, to_mip=mip)
if not non_aligned_writes:
bounds = bounds.expand_to_chunk_size(vol.chunk_size, vol.voxel_offset)
bounds = Bbox.clamp(bounds, vol.mip_bounds(mip))
class BlackoutTaskIterator(FinelyDividedTaskIterator):
def task(self, shape, offset):
bounded_shape = min2(shape, vol.bounds.maxpt - offset)
return partial(
igneous.tasks.BlackoutTask,
cloudpath=cloudpath,
mip=mip,
shape=shape.clone(),
offset=offset.clone(),
value=value,
non_aligned_writes=non_aligned_writes,
)
def on_finish(self):
vol.provenance.processing.append({
'method': {
'task': 'BlackoutTask',
'cloudpath': cloudpath,
'mip': mip,
'non_aligned_writes': non_aligned_writes,
'value': value,
'shape': shape.tolist(),
'bounds': [
bounds.minpt.tolist(),
bounds.maxpt.tolist(),
],
},
'by':
operator_contact(),
'date':
strftime('%Y-%m-%d %H:%M %Z'),
})
return BlackoutTaskIterator(bounds, shape)
def create_blackout_tasks(cloudpath,
bounds,
mip=0,
shape=(2048, 2048, 64),
value=0,
non_aligned_writes=False):
vol = CloudVolume(cloudpath, mip=mip)
shape = Vec(*shape)
bounds = Bbox.create(bounds)
bounds = vol.bbox_to_mip(bounds, mip=0, to_mip=mip)
bounds = Bbox.clamp(bounds, vol.mip_bounds(mip))
class BlackoutTaskIterator():
def __len__(self):
return num_tasks(bounds, shape)
def __iter__(self):
for startpt in xyzrange(bounds.minpt, bounds.maxpt, shape):
bounded_shape = min2(shape, vol.bounds.maxpt - startpt)
yield igneous.tasks.BlackoutTask(
cloudpath=cloudpath,
mip=mip,
shape=shape.clone(),
offset=startpt.clone(),
value=value,
non_aligned_writes=non_aligned_writes,
)
vol.provenance.processing.append({
'method': {
'task': 'BlackoutTask',
'cloudpath': cloudpath,
'mip': mip,
'non_aligned_writes': non_aligned_writes,
'value': value,
'shape': shape.tolist(),
'bounds': [
bounds.minpt.tolist(),
bounds.maxpt.tolist(),
],
},
'by':
OPERATOR_CONTACT,
'date':
strftime('%Y-%m-%d %H:%M %Z'),
})
return BlackoutTaskIterator()
def create_touch_tasks(self,
cloudpath,
mip=0,
shape=(2048, 2048, 64),
bounds=None):
vol = CloudVolume(cloudpath, mip=mip)
shape = Vec(*shape)
if bounds is None:
bounds = vol.bounds.clone()
bounds = Bbox.create(bounds)
bounds = vol.bbox_to_mip(bounds, mip=0, to_mip=mip)
bounds = Bbox.clamp(bounds, vol.mip_bounds(mip))
class TouchTaskIterator():
def __len__(self):
return num_tasks(bounds, shape)
def __iter__(self):
for startpt in xyzrange(bounds.minpt, bounds.maxpt, shape):
bounded_shape = min2(shape, vol.bounds.maxpt - startpt)
yield igneous.tasks.TouchTask(
cloudpath=cloudpath,
shape=bounded_shape.clone(),
offset=startpt.clone(),
mip=mip,
)
vol.provenance.processing.append({
'method': {
'task': 'TouchTask',
'mip': mip,
'shape': shape.tolist(),
'bounds': [
bounds.minpt.tolist(),
bounds.maxpt.tolist(),
],
},
'by':
OPERATOR_CONTACT,
'date':
strftime('%Y-%m-%d %H:%M %Z'),
})
vol.commit_provenance()
return TouchTaskIterator()
def get_bounds(vol, bounds, shape, mip, chunk_size=None):
if bounds is None:
bounds = vol.bounds.clone()
else:
bounds = Bbox.create(bounds)
bounds = vol.bbox_to_mip(bounds, mip=0, to_mip=mip)
if chunk_size is not None:
bounds = bounds.expand_to_chunk_size(chunk_size,
vol.mip_voxel_offset(mip))
bounds = Bbox.clamp(bounds, vol.mip_bounds(mip))
print("Volume Bounds: ", vol.mip_bounds(mip))
print("Selected ROI: ", bounds)
return bounds
def create_touch_tasks(
self, cloudpath,
mip=0, shape=(2048, 2048, 64),
bounds=None
):
vol = CloudVolume(cloudpath, mip=mip)
shape = Vec(*shape)
if bounds is None:
bounds = vol.bounds.clone()
bounds = Bbox.create(bounds)
bounds = vol.bbox_to_mip(bounds, mip=0, to_mip=mip)
bounds = Bbox.clamp(bounds, vol.mip_bounds(mip))
class TouchTaskIterator(FinelyDividedTaskIterator):
def task(self, shape, offset):
bounded_shape = min2(shape, vol.bounds.maxpt - offset)
return igneous.tasks.TouchTask(
cloudpath=cloudpath,
shape=bounded_shape.clone(),
offset=offset.clone(),
mip=mip,
)
def on_finish(self):
vol.provenance.processing.append({
'method': {
'task': 'TouchTask',
'mip': mip,
'shape': shape.tolist(),
'bounds': [
bounds.minpt.tolist(),
bounds.maxpt.tolist(),
],
},
'by': OPERATOR_CONTACT,
'date': strftime('%Y-%m-%d %H:%M %Z'),
})
vol.commit_provenance()
return TouchTaskIterator(bounds, shape)
