def remesh_pending(cg: ChunkedGraph):
mesh_dir = cg.meta.dataset_info["mesh"]
mesh_info = cg.meta.custom_data.get("mesh", {})
unsharded_mesh_path = join(
cg.meta.data_source.WATERSHED,
mesh_dir,
cg.meta.dataset_info["mesh_metadata"]["unsharded_mesh_dir"],
)
pending_path = f"{unsharded_mesh_path}/in-progress"
for task in _get_pending_tasks(pending_path):
fname, l2ids = task
print(f"remeshing IDs {l2ids} from {fname}")
remeshing(
cg,
l2ids,
stop_layer=mesh_info["max_layer"],
mip=mesh_info["mip"],
max_err=mesh_info["max_error"],
cv_sharded_mesh_dir=mesh_dir,
cv_unsharded_mesh_path=unsharded_mesh_path,
)
with Storage(pending_path) as storage: # pylint: disable=not-context-manager
storage.delete_file(fname)
print(f"remesh job for {fname} with {l2ids} complete")
def _remeshing(serialized_cg_info, lvl2_nodes):
cg = chunkedgraph.ChunkedGraph(**serialized_cg_info)
# TODO: stop_layer and mip should be configurable by dataset
meshgen.remeshing(cg,
lvl2_nodes,
stop_layer=4,
mesh_path=None,
mip=1,
max_err=320)
return Response(status=200)
def remeshing(table_id, lvl2_nodes):
lvl2_nodes = np.array(lvl2_nodes, dtype=np.uint64)
cg = app_utils.get_cg(table_id)
current_app.logger.debug(
f"remeshing {lvl2_nodes} {cg.get_serialized_info()}")
# TODO: stop_layer and mip should be configurable by dataset
meshgen.remeshing(cg,
lvl2_nodes,
stop_layer=4,
cv_path=None,
cv_mesh_dir=None,
mip=1,
max_err=320)
def remesh(cg: ChunkedGraph, operation_id: int, l2ids: ndarray):
from cloudvolume.storage import SimpleStorage as Storage
mesh_info = cg.meta.custom_data.get("mesh", {})
mesh_dir, unsharded_mesh_path, bucket_path, file_name = get_remesh_info(
cg, operation_id)
remeshing(
cg,
l2ids,
stop_layer=mesh_info["max_layer"],
mip=mesh_info["mip"],
max_err=mesh_info["max_error"],
cv_sharded_mesh_dir=mesh_dir,
cv_unsharded_mesh_path=unsharded_mesh_path,
)
with Storage(bucket_path) as storage: # pylint: disable=not-context-manager
storage.delete_file(file_name)