from cmmlib import cmm
from cmmlib.inout import load_mesh
from cmmlib.vis.weights import show_many_weights
mu = 2.0
K = 6
vms = []
for i, fn in enumerate(['hand_868', 'hand_868_holes2']):
verts, tris = load_mesh('meshes/%s.obj' % fn)
Phi_cpr = cmm.compressed_manifold_modes(verts, tris, K, mu=mu)
Phi_dense = cmm.manifold_harmonics(verts, tris, K)
vms += [(verts, tris, Phi_cpr, 'CMM #%d' % i),
(verts, tris, Phi_dense, 'MH #%d' % i)]
show_many_weights(vms, show_labels=True)
import numpy as np
from cmmlib import cmm
from cmmlib.inout import load_mesh
from cmmlib.vis.weights import show_many_weights
K = 6
verts, tris = load_mesh('meshes/hand_4054.obj')
# compute bases
Phi_cmh = cmm.compressed_manifold_modes(verts, tris, K, mu=2, scaled=False)
Phi_mh = cmm.manifold_harmonics(verts, tris, K, scaled=False)
# reconstruct from bases
verts_rec_cmh = np.dot(Phi_cmh, np.dot(Phi_cmh.T, verts))
verts_rec_mh = np.dot(Phi_mh, np.dot(Phi_mh.T, verts))
show_many_weights(
((verts, tris, None, 'Input'), (verts_rec_mh, tris, None, 'MH reconstr.'),
(verts_rec_cmh, tris, None, 'CMM reconstr.')),
show_labels=True,
actor_options=dict(edge_visibility=True, line_width=1.0))
import numpy as np
from cmmlib import cmm
from cmmlib.inout import load_mesh
from cmmlib.vis.weights import show_many_weights
scape_dir = path.join('meshes', 'scape')
if not path.exists(scape_dir) or not path.exists(
path.join(scape_dir, 'mesh000.off')):
print "SCAPE dataset not found. You need to get it from James Davis."
print "Instructions on this website: "
print "http://robotics.stanford.edu/~drago/Projects/scape/scape.html"
sys.exit(1)
meshes = [
load_mesh(path.join(scape_dir, 'mesh%03d.off' % i), normalize=True)
for i in [0, 7, 10]
]
results = []
for verts, tris in meshes:
Phi_cmh = cmm.compressed_manifold_modes(verts,
tris,
10,
mu=12.5,
scaled=True,
maxiter=2000)
results.append((verts, tris, Phi_cmh))
show_many_weights(results)
import sys
from os import path
import numpy as np
from cmmlib import cmm
from cmmlib.inout import load_mesh
from cmmlib.vis.weights import show_many_weights
scape_dir = path.join('meshes', 'scape')
if not path.exists(scape_dir) or not path.exists(path.join(scape_dir, 'mesh000.off')):
print "SCAPE dataset not found. You need to get it from James Davis."
print "Instructions on this website: "
print "http://robotics.stanford.edu/~drago/Projects/scape/scape.html"
sys.exit(1)
meshes = [load_mesh(path.join(scape_dir, 'mesh%03d.off' % i), normalize=True)
for i in [0, 7, 10]]
results = []
for verts, tris in meshes:
Phi_cmh = cmm.compressed_manifold_modes(
verts, tris, 10, mu=12.5, scaled=True, maxiter=2000)
results.append((verts, tris, Phi_cmh))
show_many_weights(results)
from cmmlib import cmm
from cmmlib.inout import load_mesh
from cmmlib.vis.weights import show_many_weights
mu = 2.0
K = 6
vms = []
for i, fn in enumerate(['hand_868', 'hand_868_holes2']):
verts, tris = load_mesh('meshes/%s.obj' % fn)
Phi_cpr = cmm.compressed_manifold_modes(verts, tris, K, mu=mu)
Phi_dense = cmm.manifold_harmonics(verts, tris, K)
vms += [(verts, tris, Phi_cpr, 'CMM #%d' % i),
(verts, tris, Phi_dense, 'MH #%d' % i)]
show_many_weights(vms, show_labels=True)
import numpy as np
from cmmlib import cmm
from cmmlib.inout import load_mesh
from cmmlib.vis.weights import show_many_weights
K = 6
verts, tris = load_mesh('meshes/hand_4054.obj')
# compute bases
Phi_cmh = cmm.compressed_manifold_modes(verts, tris, K, mu=2, scaled=False)
Phi_mh = cmm.manifold_harmonics(verts, tris, K, scaled=False)
# reconstruct from bases
verts_rec_cmh = np.dot(Phi_cmh, np.dot(Phi_cmh.T, verts))
verts_rec_mh = np.dot(Phi_mh, np.dot(Phi_mh.T, verts))
show_many_weights(
((verts, tris, None, 'Input'),
(verts_rec_mh, tris, None, 'MH reconstr.'),
(verts_rec_cmh, tris, None, 'CMM reconstr.')),
show_labels=True,
actor_options=dict(edge_visibility=True, line_width=1.0))
# for different K, compute the CMMs
Phis = []
for K in Ks:
Phi_cmh = cmm.compressed_manifold_modes(
verts, tris, K, mu, scaled=True, init='varimax')
Phis.append(Phi_cmh)
# color the mesh according to the CMMs
lut = LUTManager(lut_mode='hsv').lut.table.to_array()
colors = []
for K, Phi in zip(Ks, Phis):
# pass Phi through the lookup table depending on it's strength
ti = np.linspace(0, 1, K, endpoint=False) * (lut.shape[0]-1)
lut_rgb = lut[ti.astype(np.int), :3].astype(np.float)
Phi = np.abs(Phi / (Phi.max(0) - Phi.min(0))[np.newaxis])
a = Phi.sum(axis=1)[:, np.newaxis]
Phi_color = (lut_rgb[np.newaxis] * Phi[:, :, np.newaxis]).sum(axis=1)
# mix with grey
color = np.clip(Phi_color * a + 200 * (1-a), 0, 255)
colors.append(color)
results.append((verts, tris, colors))
# visualize!
show_many_weights([
(verts, tris, color.astype(np.uint8)[...,np.newaxis], "#%s K=%d" % (path.basename(fn), K))
for (fn, _, _), (verts, tris, colors) in zip(experiments, results)
for K, color in zip(Ks, colors)],
center=False, show_labels=True,
)