def update_visualization(viewer):
global V, F, T, tree, FN, VN, EN, E, EMAP, max_distance, slice_z, overlay
plane = igl.eigen.MatrixXd([
0.0, 0.0, 1.0,
-((1 - slice_z) * V.col(2).minCoeff() + slice_z * V.col(2).maxCoeff())
])
V_vis = igl.eigen.MatrixXd()
F_vis = igl.eigen.MatrixXi()
# Extract triangle mesh slice through volume mesh and subdivide nasty triangles
J = igl.eigen.MatrixXi()
bary = igl.eigen.SparseMatrixd()
igl.marching_tets(V, T, plane, V_vis, F_vis, J, bary)
max_l = 0.03
while True:
l = igl.eigen.MatrixXd()
igl.edge_lengths(V_vis, F_vis, l)
l /= (V_vis.colwiseMaxCoeff() - V_vis.colwiseMinCoeff()).norm()
if l.maxCoeff() < max_l:
break
bad = l.rowwiseMaxCoeff() > max_l
notbad = l.rowwiseMaxCoeff() <= max_l # TODO replace by ~ operator
F_vis_bad = igl.eigen.MatrixXi()
F_vis_good = igl.eigen.MatrixXi()
igl.slice_mask(F_vis, bad, 1, F_vis_bad)
igl.slice_mask(F_vis, notbad, 1, F_vis_good)
igl.upsample(V_vis, F_vis_bad)
F_vis = igl.cat(1, F_vis_bad, F_vis_good)
# Compute signed distance
S_vis = igl.eigen.MatrixXd()
I = igl.eigen.MatrixXi()
N = igl.eigen.MatrixXd()
C = igl.eigen.MatrixXd()
# Bunny is a watertight mesh so use pseudonormal for signing
igl.signed_distance_pseudonormal(V_vis, V, F, tree, FN, VN, EN, EMAP,
S_vis, I, C, N)
# push to [0,1] range
S_vis = 0.5 * (S_vis / max_distance) + 0.5
C_vis = igl.eigen.MatrixXd()
# color without normalizing
igl.parula(S_vis, False, C_vis)
if overlay:
append_mesh(C_vis, F_vis, V_vis, V, F,
igl.eigen.MatrixXd([[0.8, 0.8, 0.8]]))
viewer.data().clear()
viewer.data().set_mesh(V_vis, F_vis)
viewer.data().set_colors(C_vis)
viewer.core.lighting_factor = overlay
def update_visualization(viewer):
global V, F, T, tree, FN, VN, EN, E, EMAP, max_distance, slice_z, overlay
plane = igl.eigen.MatrixXd([0.0, 0.0, 1.0, -((1 - slice_z) * V.col(2).minCoeff() + slice_z * V.col(2).maxCoeff())])
V_vis = igl.eigen.MatrixXd()
F_vis = igl.eigen.MatrixXi()
# Extract triangle mesh slice through volume mesh and subdivide nasty triangles
J = igl.eigen.MatrixXi()
bary = igl.eigen.SparseMatrixd()
igl.slice_tets(V, T, plane, V_vis, F_vis, J, bary)
max_l = 0.03
while True:
l = igl.eigen.MatrixXd()
igl.edge_lengths(V_vis, F_vis, l)
l /= (V_vis.colwiseMaxCoeff() - V_vis.colwiseMinCoeff()).norm()
if l.maxCoeff() < max_l:
break
bad = l.rowwiseMaxCoeff() > max_l
notbad = l.rowwiseMaxCoeff() <= max_l # TODO replace by ~ operator
F_vis_bad = igl.eigen.MatrixXi()
F_vis_good = igl.eigen.MatrixXi()
igl.slice_mask(F_vis, bad, 1, F_vis_bad)
igl.slice_mask(F_vis, notbad, 1, F_vis_good)
igl.upsample(V_vis, F_vis_bad)
F_vis = igl.cat(1, F_vis_bad, F_vis_good)
# Compute signed distance
S_vis = igl.eigen.MatrixXd()
I = igl.eigen.MatrixXi()
N = igl.eigen.MatrixXd()
C = igl.eigen.MatrixXd()
# Bunny is a watertight mesh so use pseudonormal for signing
igl.signed_distance_pseudonormal(V_vis, V, F, tree, FN, VN, EN, EMAP, S_vis, I, C, N)
# push to [0,1] range
S_vis = 0.5 * (S_vis / max_distance) + 0.5
C_vis = igl.eigen.MatrixXd()
# color without normalizing
igl.parula(S_vis, False, C_vis)
if overlay:
append_mesh(C_vis, F_vis, V_vis, V, F, igl.eigen.MatrixXd([[0.8, 0.8, 0.8]]))
viewer.data.clear()
viewer.data.set_mesh(V_vis, F_vis)
viewer.data.set_colors(C_vis)
viewer.core.lighting_factor = overlay
def reconstruct_npz(inname, outname):
"""
Recontruct a 3D shape by deforming a template
:param inname: input path
:return: None (but save reconstruction)
"""
if os.path.exists(outname):
return
with np.load(inname) as npl:
V, F = npl['V'], npl['F']
V = pca_whiten(V)
max_axis = np.argmax((np.max(V, axis=0) - np.min(V, axis=0)))
V = V[:, np.roll(np.arange(3), 1 - max_axis)] # 1 means Y
V *= 1.7
assert (np.max(V, axis=0) - np.min(V, axis=0))[1] > 1.69
while V.shape[0] < 1e4:
eV, eF = p2e(V), p2e(F)
NV, NF = igl.eigen.MatrixXd(), igl.eigen.MatrixXi()
igl.upsample(eV, eF, NV, NF)
V, F = e2p(NV), e2p(NF)
input = trimesh.Trimesh(vertices=V, faces=F, process=False)
scalefactor = 1.0
if global_variables.opt.scale:
input, scalefactor = scale(
input, global_variables.mesh_ref_LR
) #scale input to have the same volume as mesh_ref_LR
if global_variables.opt.clean:
input = clean(input) #remove points that doesn't belong to any edges
test_orientation(input)
inp_V = input.vertices
if inp_V.shape[0] > 1e5:
inp_V = inp_V[
np.random.choice(inp_V.shape[0], int(1e5), replace=False), :]
final_points, final_loss = run(inp_V, scalefactor)
npz_path = os.path.dirname(outname)
if not os.path.exists(npz_path): os.makedirs(npz_path)
np.savez(outname, V=final_points, l=final_loss)
def upsample(mesh):
v = igl.eigen.MatrixXd(mesh.v.astype(np.double))
f = igl.eigen.MatrixXi(mesh.f)
igl.upsample(v, f)
mesh.v = np.array(v, dtype=np.float32, order='C')
mesh.f = np.array(f, dtype=np.int32, order='C')