def task_generator(self):
for i in range(len(self.processor_spec)):
cs_task = helpers.PartialSpecification(
SeethroughCompareTask,
processor_spec=self.processor_spec[i],
tgt_z_offset=self.tgt_z_offset,
src_stack=self.src_stack,
pad=self.pad,
crop=self.crop,
tgt_stack=self.tgt_stack,
seethrough_limit=self.seethrough_limit[i],
pixel_offset_layer=self.pixel_offset_layer,
)
chunked_job = ChunkedJob(
task_class=cs_task,
dst_layer=self.dst_layer,
chunk_xy=self.chunk_xy,
chunk_z=1,
mip=self.mip,
bcube=self.bcube,
suffix=self.suffix,
)
yield from chunked_job.task_generator
# Each seethrough processor writes to the same mask layer, so we
# wait for each processor to finish to avoid race conditions.
if i < len(self.processor_spec) - 1:
yield scheduling.wait_until_done
def task_generator(self):
for i in range(len(self.processor_spec)):
this_proc = self.processor_spec[i]
this_proc_mip = self.processor_mip[i]
is_last_proc = i == len(self.processor_spec) - 1
this_task = helpers.PartialSpecification(
ApplyProcessorTask,
src_stack=self.src_stack,
processor_spec=this_proc,
pad=self.pad,
crop=self.crop,
)
chunked_job = ChunkedJob(
task_class=this_task,
dst_layer=self.dst_layer,
chunk_xy=self.chunk_xy,
chunk_z=self.chunk_z,
blend_xy=self.blend_xy,
mip=this_proc_mip,
bcube=self.bcube
)
yield from chunked_job.task_generator
if not is_last_proc:
yield scheduling.wait_until_done
next_proc_mip = self.processor_mip[i + 1]
if this_proc_mip > next_proc_mip:
downsample_job = DownsampleJob(
src_layer=self.dst_layer,
chunk_xy=self.chunk_xy,
chunk_z=self.chunk_z,
mip_start=this_proc_mip,
mip_end=next_proc_mip,
bcube=self.bcube
)
yield from downsample_job.task_generator
yield scheduling.wait_until_done
if self.processor_mip[0] > self.processor_mip[-1]:
# good manners
# prepare the ground for the next you
downsample_job = DownsampleJob(
src_layer=self.dst_layer,
chunk_xy=self.chunk_xy,
chunk_z=self.chunk_z,
mip_start=self.processor_mip[-1],
mip_end=self.processor_mip[0],
bcube=self.bcube
)
def task_generator(self):
this_task = helpers.PartialSpecification(
InvertFieldTask,
src_layer=self.src_layer,
pad=self.pad,
crop=self.crop,
)
chunked_job = ChunkedJob(task_class=this_task,
dst_layer=self.dst_layer,
chunk_xy=self.chunk_xy,
chunk_z=self.chunk_z,
blend_xy=self.blend_xy,
mip=self.mip,
bcube=self.bcube)
yield from chunked_job.task_generator
def task_generator(self):
cs_task = helpers.PartialSpecification(
CompareSectionsTask,
processor_spec=self.processor_spec,
tgt_z_offset=self.tgt_z_offset,
src_stack=self.src_stack,
pad=self.pad,
crop=self.crop,
tgt_stack=self.tgt_stack,
)
chunked_job = ChunkedJob(task_class=cs_task,
dst_layer=self.dst_layer,
chunk_xy=self.chunk_xy,
chunk_z=1,
mip=self.mip,
bcube=self.bcube,
suffix=self.suffix)
yield from chunked_job.task_generator
def task_generator(self):
intermediary_fields = []
for i in range(len(self.processor_spec)):
this_proc = self.processor_spec[i]
this_proc_mip = self.processor_mip[i]
this_proc_vv = self.processor_vv[i]
is_last_proc = i == len(self.processor_spec) - 1
if is_last_proc:
# if it's the last processor, the dst_layer is final result
proc_field_layer = self.dst_layer
else:
# if it's not the last processor, need to create intermediate layer
proc_field_layer_name = f'align_field_stage_{i}{self.suffix}'
intermediary_fields.append(proc_field_layer_name)
proc_field_layer = self.src_stack.create_sublayer(
proc_field_layer_name, layer_type='field', overwrite=True)
# In case this field is already written during previous runs,
# disconnect it from the src_stack
self.src_stack.remove_layer(proc_field_layer_name)
# TODO: vector_vote
#if this_proc_vv == 1:
cf_task = helpers.PartialSpecification(
ComputeFieldTask,
src_stack=self.src_stack,
tgt_stack=self.tgt_stack,
processor_spec=this_proc,
pad=self.pad,
crop=self.crop,
tgt_z_offset=self.tgt_z_offset,
clear_nontissue_field=self.clear_nontissue_field)
chunked_job = ChunkedJob(task_class=cf_task,
dst_layer=proc_field_layer,
chunk_xy=self.chunk_xy,
chunk_z=self.chunk_z,
blend_xy=self.blend_xy,
mip=this_proc_mip,
bcube=self.bcube,
suffix=self.suffix)
yield from chunked_job.task_generator
if not is_last_proc:
yield scheduling.wait_until_done
# Now we're sure the proc_field_layer doesn't have stale data,
# add it back
self.src_stack.add_layer(proc_field_layer)
# this processors MIP has the freshest field
proc_field_layer.data_mip = this_proc_mip
next_proc_mip = self.processor_mip[i + 1]
if this_proc_mip < next_proc_mip:
downsample_job = DownsampleJob(src_layer=proc_field_layer,
chunk_xy=self.chunk_xy,
chunk_z=self.chunk_z,
mip_start=this_proc_mip,
mip_end=next_proc_mip,
bcube=self.bcube)
yield from downsample_job.task_generator
yield scheduling.wait_until_done
proc_field_layer.data_mip = next_proc_mip
if self.processor_mip[0] > self.processor_mip[-1]:
# good manners
# prepare the ground for the next you
# downsample the fields all the way down so that the next coarse can start right away
downsample_job = DownsampleJob(src_layer=self.dst_layer,
chunk_xy=self.chunk_xy,
chunk_z=self.chunk_z,
mip_start=self.processor_mip[-1],
mip_end=self.processor_mip[0],
bcube=self.bcube)
yield scheduling.wait_until_done
yield from downsample_job.task_generator
# field is fresh at all mip layers
self.dst_layer.data_mip = None
# Now that the final field is ready,
# remove intermediary fields from the source stack
for intermediary_field in intermediary_fields:
self.src_stack.remove_layer(intermediary_field)
def align(
ctx,
src_layer_spec,
dst_folder,
render_pad,
render_chunk_xy,
processor_spec,
pad,
crop,
processor_mip,
chunk_xy,
start_coord,
end_coord,
coord_mip,
bad_starter_path,
block_size,
stitch_size,
vote_dist,
consensus_threshold,
blur_sigma,
kernel_size,
blend_xy,
force_chunk_xy,
suffix,
seethrough_spec,
seethrough_limit,
seethrough_spec_mip,
decay_dist,
blur_rate,
restart_stage,
restart_suffix,
):
scheduler = ctx.obj["scheduler"]
if suffix is None:
suffix = "_aligned"
else:
suffix = f"_{suffix}"
if (restart_suffix is None) or (restart_stage == 0):
restart_suffix = suffix
if crop is None:
crop = pad
corgie_logger.debug("Setting up layers...")
# TODO: store stitching images in layer other than even & odd
if vote_dist + stitch_size - 2 >= block_size:
raise exceptions.CorgieException(
"block_size too small for stitching + voting requirements (stitch_size + vote_dist)"
)
corgie_logger.debug("Setting up layers...")
src_stack = create_stack_from_spec(src_layer_spec,
name="src",
readonly=True)
src_stack.folder = dst_folder
if force_chunk_xy is None:
force_chunk_xy = chunk_xy
dst_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=dst_folder,
name="dst",
types=["img", "mask"],
readonly=False,
suffix=restart_suffix,
force_chunk_xy=force_chunk_xy,
overwrite=True,
)
even_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=os.path.join(dst_folder, "even"),
name="even",
types=["img", "mask"],
readonly=False,
suffix=suffix,
force_chunk_xy=force_chunk_xy,
overwrite=True,
)
odd_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=os.path.join(dst_folder, "odd"),
name="odd",
types=["img", "mask"],
readonly=False,
suffix=suffix,
force_chunk_xy=force_chunk_xy,
overwrite=True,
)
corgie_logger.debug("Done!")
bcube = get_bcube_from_coords(start_coord, end_coord, coord_mip)
corgie_logger.debug("Calculating blocks...")
skip_list = []
if bad_starter_path is not None:
with open(bad_starter_path) as f:
line = f.readline()
while line:
skip_list.append(int(line))
line = f.readline()
blocks = get_blocks(
start=bcube.z_range()[0],
stop=bcube.z_range()[1],
block_size=block_size,
block_overlap=1,
skip_list=skip_list,
src_stack=src_stack,
even_stack=even_stack,
odd_stack=odd_stack,
)
stitch_blocks = [b.overlap(stitch_size) for b in blocks[1:]]
corgie_logger.debug("All Blocks")
for block, stitch_block in zip(blocks, [None] + stitch_blocks):
corgie_logger.debug(block)
corgie_logger.debug(f"Stitch {stitch_block}")
corgie_logger.debug("\n")
max_blur_mip = (math.ceil(math.log(decay_dist * blur_rate + 1, 2)) +
processor_mip[-1])
corgie_logger.debug(f"Max blur mip for stitching field: {max_blur_mip}")
# Set all field names, adjusting for restart suffix
block_field_name = f"field{suffix}"
stitch_estimated_suffix = f"_stitch_estimated{suffix}"
stitch_estimated_name = f"field{stitch_estimated_suffix}"
stitch_corrected_name = f"stitch_corrected{suffix}"
stitch_corrected_field = None
composed_name = f"composed{suffix}"
if restart_stage <= 2:
stitch_estimated_suffix = f"_stitch_estimated{restart_suffix}"
stitch_estimated_name = f"field{stitch_estimated_suffix}"
stitch_corrected_name = f"stitch_corrected{restart_suffix}"
if restart_stage <= 3:
composed_name = f"composed{restart_suffix}"
render_method = helpers.PartialSpecification(
f=RenderJob,
pad=render_pad,
chunk_xy=render_chunk_xy,
chunk_z=1,
render_masks=False,
)
cf_method = helpers.PartialSpecification(
f=ComputeFieldJob,
pad=pad,
crop=crop,
processor_mip=processor_mip,
processor_spec=processor_spec,
chunk_xy=chunk_xy,
blend_xy=blend_xy,
chunk_z=1,
)
if seethrough_spec != tuple():
assert seethrough_spec_mip is not None
seethrough_method = helpers.PartialSpecification(
f=SeethroughCompareJob,
mip=seethrough_spec_mip,
processor_spec=seethrough_spec,
chunk_xy=chunk_xy,
pad=pad,
crop=pad,
seethrough_limit=seethrough_limit,
)
else:
seethrough_method = None
#restart_stage = 4
#import pdb; pdb.set_trace()
if restart_stage == 0:
corgie_logger.debug("Aligning blocks...")
for block in blocks:
block_bcube = block.get_bcube(bcube)
# Use copies of src & dst so that aligning the stitching blocks
# is not affected by these block fields.
# Copying also allows local compute to not modify objects for other tasks
align_block_job_forv = AlignBlockJob(
src_stack=deepcopy(block.src_stack),
dst_stack=deepcopy(block.dst_stack),
bcube=block_bcube,
render_method=render_method,
cf_method=cf_method,
vote_dist=vote_dist,
seethrough_method=seethrough_method,
suffix=suffix,
copy_start=True,
use_starters=True,
backward=False,
consensus_threshold=consensus_threshold,
blur_sigma=blur_sigma,
kernel_size=kernel_size,
)
scheduler.register_job(
align_block_job_forv,
job_name=f"Forward Align {block} {block_bcube}",
)
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
if restart_stage <= 1:
corgie_logger.debug("Aligning stitching blocks...")
for stitch_block in stitch_blocks:
block_bcube = stitch_block.get_bcube(bcube)
# These blocks will have block-aligned images, but not
# the block_fields that warped them.
align_block_job_forv = AlignBlockJob(
src_stack=deepcopy(stitch_block.src_stack),
dst_stack=deepcopy(stitch_block.dst_stack),
bcube=block_bcube,
render_method=render_method,
cf_method=cf_method,
vote_dist=vote_dist,
seethrough_method=seethrough_method,
suffix=stitch_estimated_suffix,
copy_start=False,
use_starters=False,
backward=False,
consensus_threshold=consensus_threshold,
blur_sigma=blur_sigma,
kernel_size=kernel_size,
)
scheduler.register_job(
align_block_job_forv,
job_name=f"Stitch Align {stitch_block} {block_bcube}",
)
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
# Add in the stitch_estimated fields that were just created above
even_stack.create_sublayer(
stitch_estimated_name,
layer_type="field",
overwrite=False,
)
odd_stack.create_sublayer(
stitch_estimated_name,
layer_type="field",
overwrite=False,
)
if restart_stage <= 2:
if stitch_size > 1:
corgie_logger.debug("Voting over stitching blocks")
stitch_corrected_field = dst_stack.create_sublayer(
stitch_corrected_name, layer_type="field", overwrite=True)
for stitch_block in stitch_blocks:
stitch_estimated_field = stitch_block.dst_stack[
stitch_estimated_name]
block_bcube = bcube.reset_coords(
zs=stitch_block.start,
ze=stitch_block.start + 1,
in_place=False,
)
z_offsets = [
z - block_bcube.z_range()[0]
for z in range(stitch_block.start, stitch_block.stop)
]
vote_stitch_job = VoteJob(
input_fields=[stitch_estimated_field],
output_field=stitch_corrected_field,
chunk_xy=chunk_xy,
bcube=block_bcube,
z_offsets=z_offsets,
mip=processor_mip[-1],
consensus_threshold=consensus_threshold,
blur_sigma=blur_sigma,
kernel_size=kernel_size,
)
scheduler.register_job(
vote_stitch_job,
job_name=f"Stitching Vote {stitch_block} {block_bcube}",
)
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
for stitch_block in stitch_blocks:
block_bcube = bcube.reset_coords(zs=stitch_block.start,
ze=stitch_block.start + 1,
in_place=False)
field_to_downsample = stitch_block.dst_stack[stitch_estimated_name]
if stitch_corrected_field is not None:
field_to_downsample = stitch_corrected_field
# Hack for fafb
field_info = field_to_downsample.get_info()
for scale in field_info['scales']:
scale['chunk_sizes'][-1][-1] = 1
scale['encoding'] = 'raw'
field_to_downsample.cv.store_info(field_info)
field_to_downsample.cv.fetch_info()
downsample_field_job = DownsampleJob(
src_layer=field_to_downsample,
mip_start=processor_mip[-1],
mip_end=max_blur_mip,
bcube=block_bcube,
chunk_xy=
chunk_xy, # TODO: This probably needs to be modified at highest mips
chunk_z=1,
mips_per_task=2,
)
scheduler.register_job(
downsample_field_job,
job_name=f"Downsample stitching field {block_bcube}",
)
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
# Add in the block-align fields
even_stack.create_sublayer(
block_field_name,
layer_type="field",
overwrite=False,
)
odd_stack.create_sublayer(
block_field_name,
layer_type="field",
overwrite=False,
)
composed_field = dst_stack.create_sublayer(composed_name,
layer_type="field",
overwrite=True)
if (restart_stage > 2) and (stitch_size > 1):
stitch_corrected_field = dst_stack.create_sublayer(
stitch_corrected_name, layer_type="field", overwrite=False)
if restart_stage <= 3:
corgie_logger.debug("Stitching blocks...")
for block, stitch_block in zip(blocks[1:], stitch_blocks):
block_bcube = block.broadcastable().get_bcube(bcube)
block_list = block.get_neighbors(dist=decay_dist)
corgie_logger.debug(f"src_block: {block}")
corgie_logger.debug(f"influencing blocks: {block_list}")
z_list = [b.stop for b in block_list]
# stitch_corrected_field used if there is multi-section block overlap,
# which requires voting to produce a corrected field.
# If there is only single-section block overlap, then use
# stitch_estimated_fields from each stitch_block
if stitch_corrected_field is not None:
stitching_fields = [stitch_corrected_field]
else:
# Order with furthest block first (convention of FieldSet).
stitching_fields = [
stitch_block.dst_stack[stitch_estimated_name],
stitch_block.src_stack[stitch_estimated_name],
]
broadcast_job = BroadcastJob(
block_field=block.dst_stack[block_field_name],
stitching_fields=stitching_fields,
output_field=composed_field,
chunk_xy=chunk_xy,
bcube=block_bcube,
pad=pad,
z_list=z_list,
mip=processor_mip[-1],
decay_dist=decay_dist,
blur_rate=blur_rate,
)
scheduler.register_job(broadcast_job,
job_name=f"Broadcast {block} {block_bcube}")
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
if len(blocks) > 1:
block_bcube = blocks[0].get_bcube(bcube)
copy_job = CopyLayerJob(
src_layer=even_stack[block_field_name],
dst_layer=composed_field,
mip=processor_mip[-1],
bcube=block_bcube,
chunk_xy=chunk_xy,
chunk_z=1,
)
scheduler.register_job(
copy_job,
job_name=f"Copy first block_field to composed_field location")
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
if restart_stage <= 4:
if len(blocks) == 1:
block_bcube = blocks[0].get_bcube(bcube)
render_job = RenderJob(
src_stack=src_stack,
dst_stack=dst_stack,
mips=processor_mip[-1],
pad=pad,
bcube=block_bcube,
chunk_xy=chunk_xy,
chunk_z=1,
render_masks=True,
blackout_masks=False,
additional_fields=[even_stack[block_field_name]],
)
scheduler.register_job(
render_job, job_name=f"Render first block {block_bcube}")
else:
block_bcube = bcube.reset_coords(zs=blocks[0].start,
ze=blocks[-1].stop,
in_place=False)
render_job = RenderJob(
src_stack=src_stack,
dst_stack=dst_stack,
mips=processor_mip[-1],
pad=pad,
bcube=block_bcube,
chunk_xy=chunk_xy,
chunk_z=1,
render_masks=True,
blackout_masks=True,
additional_fields=[composed_field],
)
scheduler.register_job(render_job,
job_name=f"Render all blocks {block_bcube}")
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
result_report = (
f"Aligned layers {[str(l) for l in src_stack.get_layers_of_type('img')]}. "
f"Results in {[str(l) for l in dst_stack.get_layers_of_type('img')]}")
corgie_logger.info(result_report)
def align_block(
ctx,
src_layer_spec,
dst_folder,
vote_dist,
render_pad,
render_chunk_xy,
processor_spec,
pad,
crop,
processor_mip,
chunk_xy,
start_coord,
end_coord,
coord_mip,
blend_xy,
force_chunk_xy,
suffix,
copy_start,
use_starters,
seethrough_spec,
seethrough_limit,
seethrough_spec_mip,
mode,
chunk_z=1,
):
scheduler = ctx.obj["scheduler"]
if suffix is None:
suffix = "_aligned"
else:
suffix = f"_{suffix}"
if crop is None:
crop = pad
corgie_logger.debug("Setting up layers...")
src_stack = create_stack_from_spec(src_layer_spec, name="src", readonly=True)
src_stack.folder = dst_folder
force_chunk_xy = chunk_xy if force_chunk_xy else None
dst_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=dst_folder,
name="dst",
types=["img", "mask"],
readonly=False,
suffix=suffix,
force_chunk_xy=force_chunk_xy,
overwrite=True,
)
render_method = helpers.PartialSpecification(
f=RenderJob,
pad=render_pad,
chunk_xy=render_chunk_xy,
chunk_z=1,
render_masks=False,
)
if seethrough_spec != tuple():
assert seethrough_spec_mip is not None
seethrough_method = helpers.PartialSpecification(
f=SeethroughCompareJob,
mip=seethrough_spec_mip,
processor_spec=seethrough_spec,
chunk_xy=chunk_xy,
pad=pad,
crop=pad,
seethrough_limit=seethrough_limit,
)
else:
seethrough_method = None
cf_method = helpers.PartialSpecification(
f=ComputeFieldJob,
pad=pad,
crop=crop,
processor_mip=processor_mip,
processor_spec=processor_spec,
chunk_xy=chunk_xy,
blend_xy=blend_xy,
chunk_z=1,
)
bcube = get_bcube_from_coords(start_coord, end_coord, coord_mip)
if mode == "bidirectional":
z_mid = (bcube.z_range()[1] + bcube.z_range()[0]) // 2
bcube_back = bcube.reset_coords(ze=z_mid, in_place=False)
bcube_forv = bcube.reset_coords(zs=z_mid, in_place=False)
align_block_job_back = AlignBlockJob(
src_stack=src_stack,
dst_stack=dst_stack,
bcube=bcube_back,
render_method=render_method,
cf_method=cf_method,
seethrough_method=seethrough_method,
suffix=suffix,
copy_start=copy_start,
backward=True,
vote_dist=vote_dist,
use_starters=use_starters,
)
scheduler.register_job(
align_block_job_back,
job_name="Backward Align Block {}".format(bcube),
)
align_block_job_forv = AlignBlockJob(
src_stack=src_stack,
dst_stack=deepcopy(dst_stack),
bcube=bcube_forv,
render_method=render_method,
cf_method=cf_method,
seethrough_method=seethrough_method,
suffix=suffix,
copy_start=True,
backward=False,
vote_dist=vote_dist,
use_starters=use_starters,
)
scheduler.register_job(
align_block_job_forv,
job_name="Forward Align Block {}".format(bcube),
)
else:
align_block_job = AlignBlockJob(
src_stack=src_stack,
dst_stack=dst_stack,
bcube=bcube,
render_method=render_method,
cf_method=cf_method,
seethrough_method=seethrough_method,
suffix=suffix,
copy_start=copy_start,
backward=mode == "backward",
vote_dist=vote_dist,
use_starters=use_starters,
)
# create scheduler and execute the job
scheduler.register_job(align_block_job, job_name="Align Block {}".format(bcube))
scheduler.execute_until_completion()
result_report = (
f"Aligned layers {[str(l) for l in src_stack.get_layers_of_type('img')]}. "
f"Results in {[str(l) for l in dst_stack.get_layers_of_type('img')]}"
)
corgie_logger.info(result_report)
def align_block(ctx, src_layer_spec, tgt_layer_spec, dst_folder, render_pad, render_chunk_xy,
processor_spec, pad, crop, processor_mip, chunk_xy, start_coord, end_coord, coord_mip,
suffix, copy_start, mode, chunk_z=1):
scheduler = ctx.obj['scheduler']
if suffix is None:
suffix = '_aligned'
else:
suffix = f"_{suffix}"
if crop is None:
crop = pad
corgie_logger.debug("Setting up layers...")
src_stack = create_stack_from_spec(src_layer_spec,
name='src', readonly=True)
tgt_stack = create_stack_from_spec(tgt_layer_spec,
name='tgt', readonly=True, reference=src_stack)
dst_stack = stack.create_stack_from_reference(reference_stack=src_stack,
folder=dst_folder, name="dst", types=["img", "mask"], readonly=False,
suffix=suffix)
render_method = helpers.PartialSpecification(
f=RenderJob,
pad=render_pad,
chunk_xy=render_chunk_xy,
chunk_z=1,
blackout_masks=False,
render_masks=True,
mip=min(processor_mip)
)
cf_method = helpers.PartialSpecification(
f=ComputeFieldJob,
pad=pad,
crop=crop,
processor_mip=processor_mip,
processor_spec=processor_spec,
chunk_xy=chunk_xy,
chunk_z=1
)
bcube = get_bcube_from_coords(start_coord, end_coord, coord_mip)
if mode == 'bidirectional':
z_mid = (bcube.z_range()[1] + bcube.z_range()[0]) // 2
bcube_back = bcube.reset_coords(ze=z_mid, in_place=False)
bcube_forv = bcube.reset_coords(zs=z_mid, in_place=False)
align_block_job_back = AlignBlockJob(src_stack=src_stack,
tgt_stack=tgt_stack,
dst_stack=dst_stack,
bcube=bcube_back,
render_method=render_method,
cf_method=cf_method,
suffix=suffix,
copy_start=copy_start,
backward=True)
scheduler.register_job(align_block_job_back, job_name="Backward Align Block {}".format(bcube))
align_block_job_forv = AlignBlockJob(src_stack=src_stack,
tgt_stack=tgt_stack,
dst_stack=deepcopy(dst_stack),
bcube=bcube_forv,
render_method=render_method,
cf_method=cf_method,
suffix=suffix,
copy_start=True,
backward=False)
scheduler.register_job(align_block_job_forv, job_name="Forward Align Block {}".format(bcube))
else:
align_block_job = AlignBlockJob(src_stack=src_stack,
tgt_stack=tgt_stack,
dst_stack=dst_stack,
bcube=bcube,
render_method=render_method,
cf_method=cf_method,
suffix=suffix,
copy_start=copy_start,
backward=mode=='backward')
# create scheduler and execute the job
scheduler.register_job(align_block_job, job_name="Align Block {}".format(bcube))
scheduler.execute_until_completion()
result_report = f"Aligned layers {[str(l) for l in src_stack.get_layers_of_type('img')]}. " \
f"Results in {[str(l) for l in dst_stack.get_layers_of_type('img')]}"
corgie_logger.info(result_report)
def seethrough_block(
ctx,
src_layer_spec,
dst_folder,
chunk_xy,
start_coord,
end_coord,
coord_mip,
suffix,
seethrough_spec,
seethrough_limit,
seethrough_spec_mip,
force_chunk_z=1,
):
scheduler = ctx.obj["scheduler"]
if suffix is None:
suffix = "_seethrough"
else:
suffix = f"_{suffix}"
crop, pad = 0, 0
corgie_logger.debug("Setting up layers...")
src_stack = create_stack_from_spec(src_layer_spec,
name="src",
readonly=True)
src_stack.folder = dst_folder
dst_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=dst_folder,
name="dst",
types=["img", "mask"],
readonly=False,
suffix=suffix,
overwrite=True,
force_chunk_z=force_chunk_z,
)
render_method = helpers.PartialSpecification(
f=RenderJob,
pad=pad,
chunk_xy=chunk_xy,
chunk_z=1,
render_masks=False,
)
seethrough_method = helpers.PartialSpecification(
f=SeethroughCompareJob,
mip=seethrough_spec_mip,
processor_spec=seethrough_spec,
chunk_xy=chunk_xy,
pad=pad,
crop=pad,
seethrough_limit=seethrough_limit,
)
bcube = get_bcube_from_coords(start_coord, end_coord, coord_mip)
seethrough_block_job = SeethroughBlockJob(
src_stack=src_stack,
dst_stack=dst_stack,
bcube=bcube,
render_method=render_method,
seethrough_method=seethrough_method,
suffix=suffix,
)
# create scheduler and execute the job
scheduler.register_job(seethrough_block_job,
job_name="Seethrough Block {}".format(bcube))
scheduler.execute_until_completion()
result_report = (
f"Rendered layers {[str(l) for l in src_stack.get_layers_of_type('img')]}. "
f"Results in {[str(l) for l in dst_stack.get_layers_of_type('img')]}")
corgie_logger.info(result_report)
def align(ctx, src_layer_spec, tgt_layer_spec, dst_folder, render_pad,
render_chunk_xy, processor_spec, pad, crop, processor_mip, chunk_xy,
start_coord, end_coord, coord_mip, bad_starter_path, block_size,
block_overlap, blend_xy, force_chunk_xy, suffix, copy_start,
seethrough_spec, seethrough_spec_mip):
scheduler = ctx.obj['scheduler']
if suffix is None:
suffix = '_aligned'
else:
suffix = f"_{suffix}"
if crop is None:
crop = pad
corgie_logger.debug("Setting up layers...")
src_stack = create_stack_from_spec(src_layer_spec,
name='src',
readonly=True)
src_stack.folder = dst_folder
tgt_stack = create_stack_from_spec(tgt_layer_spec,
name='tgt',
readonly=True,
reference=src_stack)
if force_chunk_xy is None:
force_chunk_xy = chunk_xy
dst_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=dst_folder,
name="dst",
types=["img", "mask"],
readonly=False,
suffix=suffix,
force_chunk_xy=force_chunk_xy,
overwrite=True)
even_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=os.path.join(dst_folder, 'even'),
name="even",
types=["img", "mask"],
readonly=False,
suffix=suffix,
force_chunk_xy=force_chunk_xy,
overwrite=True)
odd_stack = stack.create_stack_from_reference(
reference_stack=src_stack,
folder=os.path.join(dst_folder, 'odd'),
name="odd",
types=["img", "mask"],
readonly=False,
suffix=suffix,
force_chunk_xy=force_chunk_xy,
overwrite=True)
corgie_logger.debug("Done!")
bcube = get_bcube_from_coords(start_coord, end_coord, coord_mip)
corgie_logger.debug("Calculating blocks...")
# TODO: read in bad starter sections
bad_starter_sections = []
blocks = []
z = bcube.z_range()[0]
while z < bcube.z_range()[-1]:
block_start = z
block_end = z + block_size
while block_end + block_overlap in bad_starter_sections and \
block_end + block_overlap < bcube.z_range()[-1]:
block_end += 1
block = Block(block_start, block_end + block_overlap)
blocks.append(block)
z = block_end
corgie_logger.debug("Done!")
render_method = helpers.PartialSpecification(
f=RenderJob,
pad=render_pad,
chunk_xy=render_chunk_xy,
chunk_z=1,
render_masks=False,
)
cf_method = helpers.PartialSpecification(f=ComputeFieldJob,
pad=pad,
crop=crop,
processor_mip=processor_mip,
processor_spec=processor_spec,
chunk_xy=chunk_xy,
blend_xy=blend_xy,
chunk_z=1)
if seethrough_spec is not None:
assert seethrough_spec_mip is not None
seethrough_method = helpers.PartialSpecification(
f=CompareSectionsJob,
mip=seethrough_spec_mip,
processor_spec=seethrough_spec,
chunk_xy=chunk_xy,
pad=pad,
crop=pad,
)
else:
seethrough_method = None
corgie_logger.debug("Aligning blocks...")
for i in range(len(blocks)):
block = blocks[i]
block_bcube = bcube.copy()
block_bcube.reset_coords(zs=block.z_start, ze=block.z_end)
if i % 2 == 0:
block_dst_stack = even_stack
else:
block_dst_stack = odd_stack
align_block_job_forv = AlignBlockJob(
src_stack=src_stack,
tgt_stack=tgt_stack,
dst_stack=block_dst_stack,
bcube=block_bcube,
render_method=render_method,
cf_method=cf_method,
seethrough_method=seethrough_method,
suffix=suffix,
copy_start=copy_start,
backward=False)
scheduler.register_job(align_block_job_forv,
job_name=f"Forward Align {block} {block_bcube}")
scheduler.execute_until_completion()
corgie_logger.debug("Done!")
corgie_logger.debug("Stitching blocks...")
#TODO
#stitch_blocks_job = StitchBlockJob(
# blocks=blocks,
# src_stack=src_stack,
# dst_stack=dst_stack,
# bcube=bcube,
# suffix=suffix,
# render_method=render_method,
# cf_method=cf_method
#)
#scheduler.register_job(stitch_blocks_job, job_name=f"Stitch blocks {bcube}")
#scheduler.execute_until_completion()
corgie_logger.debug("Done!")
result_report = f"Aligned layers {[str(l) for l in src_stack.get_layers_of_type('img')]}. " \
f"Results in {[str(l) for l in dst_stack.get_layers_of_type('img')]}"
corgie_logger.info(result_report)