def diffuse(model: ChunkGrid[bool], repeat=1):
"""
Diffuse the voxels in model to their neighboring voxels
:param model: the model to diffuse
:param repeat: number of diffusion steps
:return: diffused model
"""
kernel = np.zeros((3, 3, 3), dtype=float)
kernel[1] = 1
kernel[:, 1] = 1
kernel[:, :, 1] = 1
kernel /= np.sum(kernel)
result = ChunkGrid(model.chunk_size, dtype=float, fill_value=1.0)
result[model] = 0.0
result.pad_chunks(repeat // result.chunk_size + 1)
for r in range(repeat):
tmp = result.copy(empty=True)
for chunk in result.chunks:
padded = chunk.padding(result, 1)
ndimage.convolve(padded,
kernel,
output=padded,
mode='constant',
cval=1.0)
conv = padded[1:-1, 1:-1, 1:-1]
m = model.ensure_chunk_at_index(chunk.index, insert=False)
if m.is_filled():
if m.value:
tmp.ensure_chunk_at_index(chunk.index).set_fill(0.0)
continue
else:
conv[m.to_array()] = 0.0
tmp.ensure_chunk_at_index(chunk.index).set_array(conv)
# Expand chunks
for f, i in ChunkGrid.iter_neighbors_indices(chunk.index):
tmp.ensure_chunk_at_index(i)
result = tmp
result.cleanup(remove=True)
return result
def crust_fix(
crust: ChunkGrid[np.bool8],
outer_fill: ChunkGrid[np.bool8],
crust_outer: ChunkGrid[np.bool8],
crust_inner: ChunkGrid[np.bool8],
min_distance: int = 1,
data_pts: Optional[np.ndarray] = None, # for plotting,
export_path: Optional[str] = None):
CHUNKSIZE = crust.chunk_size
normal_kernel = make_normal_kernel()
inv_outer_fill = ~outer_fill
# Method cache (prevent lookup in loop)
__grid_set_value = ChunkGrid.set_value
__np_sum = np.sum
print("\tCreate Normals: ")
with timed("\t\tTime: "):
# normal_zero = np.zeros(3, dtype=np.float32)
normal_pos = np.array(list(crust_outer.where()))
normal_val = np.full((len(normal_pos), 3), 0.0, dtype=np.float32)
for n, p in enumerate(normal_pos):
x, y, z = p
mask: np.ndarray = outer_fill[x - 1:x + 2, y - 1:y + 2,
z - 1:z + 2]
normal_val[n] = __np_sum(normal_kernel[mask], axis=0)
normal_val = (normal_val.T / np.linalg.norm(normal_val, axis=1)).T
print("\tGrid Normals: ")
with timed("\t\tTime: "):
normals: ChunkGrid[np.float32] = ChunkGrid(
CHUNKSIZE, np.dtype((np.float32, (3, ))), 0.0)
normals[normal_pos] = normal_val
print("\tRender Normal Propagation: ")
with timed("\t\tTime: "):
markers_outer = np.array([
v for p, n in normals.items(mask=crust_outer)
for v in (p, p + n, (np.nan, np.nan, np.nan))
],
dtype=np.float32) + 0.5
markers_outer_tips = np.array(
[p + n for p, n in normals.items(mask=crust_outer)],
dtype=np.float32) + 0.5
ren = CloudRender()
fig = ren.make_figure(title="Crust-Fix: Start Normal Propagation")
fig.add_trace(
ren.make_scatter(markers_outer,
marker=dict(opacity=0.5, ),
mode="lines",
name="Start normal"))
fig.add_trace(
ren.make_scatter(markers_outer_tips,
marker=dict(size=1, symbol='x'),
name="Start nromal end"))
if data_pts is not None:
fig.add_trace(
ren.make_scatter(data_pts, opacity=0.1, size=1, name='Model'))
if export_path:
fig.write_html(os.path.join(export_path, "normal_start.html"))
fig.show()
print("\tNormal Propagation")
with timed("\t\tTime: "):
iterations = CHUNKSIZE * 2
nfield = propagate_normals(iterations, normals, crust_outer,
inv_outer_fill)
field_reset_mask = outer_fill ^ crust_outer
nfield[field_reset_mask] = 0
nfield.cleanup(remove=True)
# print("\tRender Normal Field: ")
# with timed("\t\tTime: "):
#
# markers_crust = np.array(
# [v for p, n in nfield.items(mask=crust) for v in (p, p + n, (np.nan, np.nan, np.nan))],
# dtype=np.float32) + 0.5
# markers_outer = np.array(
# [v for p, n in nfield.items(mask=crust_outer) for v in (p, p + n, (np.nan, np.nan, np.nan))],
# dtype=np.float32) + 0.5
# markers_outer_tips = np.array(
# [p + n for p, n in nfield.items(mask=crust_outer)],
# dtype=np.float32) + 0.5
#
# ren = CloudRender()
# fig = ren.make_figure(title="Crust-Fix: Normal Field")
# fig.add_trace(ren.make_scatter(markers_outer, marker=dict(opacity=0.5, ), mode="lines", name="Start normal"))
# fig.add_trace(ren.make_scatter(markers_outer_tips, marker=dict(size=1, symbol='x'), name="Start normal end"))
# fig.add_trace(ren.make_scatter(markers_crust, marker=dict(opacity=0.5, ), mode="lines", name="Normal field"))
# if data_pts is not None:
# fig.add_trace(ren.make_scatter(data_pts, opacity=0.1, size=1, name='Model'))
# if export_path:
# fig.write_html(os.path.join(export_path, "normal_field.html"))
# fig.show()
print("\tNormal cone: ")
with timed("\t\tTime: "):
medial = ChunkGrid(crust.chunk_size, np.bool8, False)
cone_threshold: float = 0.5 * np.pi
min_norm: float = 1e-15
for chunk in nfield.chunks:
padded = nfield.padding_at(chunk.index,
1,
corners=True,
edges=True)
cones = normal_cone_angles(padded, cone_threshold, min_norm)
medial.ensure_chunk_at_index(chunk.index).set_array(cones.copy())
medial.cleanup(remove=True)
print("\tResult: ")
with timed("\t\tTime: "):
# Remove artifacts where the inner and outer crusts are touching
artifacts_fix = outer_fill.copy().pad_chunks(1)
artifacts_fix.fill_value = False
artifacts_fix = ~dilate(artifacts_fix,
steps=max(0, min_distance) + 2) & ~outer_fill
medial_cleaned = medial & artifacts_fix
medial_cleaned.cleanup(remove=True)
print("\tRender 2: ")
with timed("\t\tTime: "):
time.sleep(0.01)
ren = VoxelRender()
fig = ren.make_figure(title="Crust-Normal-Fix: Result before cleanup")
print("Ren2-medial")
fig.add_trace(ren.grid_voxel(medial, opacity=0.3, name='Medial'))
# fig.add_trace(ren.grid_voxel(medial_cleaned, opacity=0.05, name='Fixed'))
print("Ren2-crust_outer")
fig.add_trace(ren.grid_voxel(crust_outer, opacity=0.05, name='Outer'))
if data_pts is not None:
print("Ren2-data_pts")
fig.add_trace(CloudRender().make_scatter(data_pts,
opacity=0.2,
size=1,
name='Model'))
print("Ren2-show")
if export_path:
fig.write_html(os.path.join(export_path, "medial.html"))
fig.show()
print("\tRender 3: ")
with timed("\t\tTime: "):
time.sleep(0.01)
ren = VoxelRender()
fig = ren.make_figure(title="Crust-Fix: Result after cleanup")
# fig.add_trace(ren.grid_voxel(medial, opacity=0.3, name='Fixed'))
print("Ren2-medial_cleaned")
fig.add_trace(
ren.grid_voxel(medial_cleaned, opacity=0.3, name='Medial-Cleaned'))
print("Ren3-crust_outer")
fig.add_trace(ren.grid_voxel(crust_outer, opacity=0.05, name='Outer'))
if data_pts is not None:
print("Ren3-data_pts")
fig.add_trace(CloudRender().make_scatter(data_pts,
opacity=0.2,
size=1,
name='Model'))
print("Ren3-show")
if export_path:
fig.write_html(os.path.join(export_path, "medial_cleaned.html"))
fig.show()
return medial_cleaned