perf: faster multi-resolution meshing

igneous/task_creation/image.py

@@ -244,7 +244,7 @@ def create_downsampling_tasks(
   """
   def ds_shape(mip, chunk_size=None, factor=None):
     nonlocal num_mips
-    if chunk_size:
+    if chunk_size is not None:
       shape = Vec(*chunk_size)
     else:
       shape = vol.meta.chunk_size(mip)[:3]

igneous/tasks/mesh/multires.py

@@ -298,6 +298,7 @@ def generate_lods(
   assert num_lods >= 0, num_lods
 
   lods = [ mesh ]
+  next_mesh = mesh
 
   # from pyfqmr documentation:
   # threshold = alpha * (iteration + K) ** agressiveness
@@ -306,9 +307,9 @@ def generate_lods(
   # deleting a vertex.
   for i in range(1, num_lods+1):
     simplifier = pyfqmr.Simplify()
-    simplifier.setMesh(mesh.vertices, mesh.faces)
+    simplifier.setMesh(next_mesh.vertices, next_mesh.faces)
     simplifier.simplify_mesh(
-      target_count=max(int(len(mesh.faces) / (decimation_factor ** i)), 4),
+      target_count=max(int(len(next_mesh.faces) / decimation_factor), 4),
       aggressiveness=aggressiveness,
       preserve_border=True,
       verbose=False,
@@ -324,6 +325,7 @@ def generate_lods(
     lods.append(
       Mesh(*simplifier.getMesh())
     )
+    next_mesh = lods[-1]
 
   return lods
 
@@ -495,6 +497,54 @@ def create_octree_level_from_mesh(mesh, chunk_shape, lod, num_lods):
   Create submeshes by slicing the orignal mesh to produce smaller chunks
   by slicing them from x,y,z dimensions.
 
+  This creates (2^lod)^3 submeshes.
+  """
+  try:
+    return create_octree_level_from_mesh_accelerated(mesh, chunk_shape, lod, num_lods)
+  except RuntimeError:
+    return create_octree_level_from_mesh_generalized(mesh, chunk_shape, lod, num_lods)
+
+def create_octree_level_from_mesh_accelerated(mesh, chunk_shape, lod, num_lods):
+  """
+  Uses zmesh.chunk_mesh to accelerate slicing meshes, but it can only handle
+  vertices that are one 26-connected grid space apart and raises a RuntimeError
+  if this condition isn't met.
+  """
+  if lod == num_lods - 1:
+    return ([ mesh ], ((0,0,0),) )
+
+  scale = Vec(*(np.array(chunk_shape) * (2 ** lod)))
+  chunked_meshes = zmesh.chunk_mesh(mesh, scale)
+  gpts = list(chunked_meshes.keys())
+
+  nodes = []
+
+  for gpt in gpts:
+    mesh = chunked_meshes[gpt]
+    if mesh.is_empty():
+      continue
+    # test for totally degenerate meshes by checking if 
+    # all of two axes match, meaning the mesh must be a 
+    # point or a line.
+    if np.sum([ np.all(mesh.vertices[:,i] == mesh.vertices[0,i]) for i in range(3) ]) >= 2:
+      continue
+
+    nodes.append(gpt)
+
+  # Sort in Z-curve order
+  nodes.sort(
+    key=functools.cmp_to_key(lambda x, y: cmp_zorder(x, y))
+  )
+
+  submeshes = [ chunked_meshes[node] for node in nodes ]
+
+  return (submeshes, nodes)
+
+def create_octree_level_from_mesh_generalized(mesh, chunk_shape, lod, num_lods):
+  """
+  Create submeshes by slicing the orignal mesh to produce smaller chunks
+  by slicing them from x,y,z dimensions.
+
   This creates (2^lod)^3 submeshes.
   """
   if lod == num_lods - 1:

igneous_cli/cli.py

@@ -1617,9 +1617,8 @@ def memory_used(data_width, shape, factor):
 @click.argument("path", type=CloudPath())
 @click.option('--browser/--no-browser', default=True, is_flag=True, help="Open the dataset in the system's default web browser.")
 @click.option('--port', default=1337, help="localhost server port for the file server.", show_default=True)
-@click.option('--ng', default="https://neuroglancer-demo.appspot.com/", help="Alternative Neuroglancer webpage to use.", show_default=True)
+@click.option('--ng', default=None, help="Alternative Neuroglancer webpage to use.", show_default=True)
 @click.option('--pos', type=Tuple3(), default=None, help="Position in volume to open to.", show_default=True)
-
 def view(path, browser, port, ng, pos):
   """
   Open an on-disk dataset for viewing in neuroglancer.
@@ -1688,6 +1687,17 @@ def view(path, browser, port, ng, pos):
     config["layers"][0]["shader"] = rgb_shader
 
   fragment = urllib.parse.quote(jsonify(config))
+
+  has_alternative_codec = any([
+     scale["encoding"] in ["crackle", "zfpc", "kempressed", "fpzip"]
+     for scale in cv.scales
+  ])
+
+  if ng is None:
+    if has_alternative_codec:
+      ng = "https://allcodecs-dot-neuromancer-seung-import.appspot.com/"
+    else:
+      ng = "https://neuroglancer-demo.appspot.com/"
 
   url = f"{ng}#!{fragment}"
   if browser: