def get_arap_solver(self):
if not hasattr(self, '_adjW'):
self._adjW = weights(self._s.V,
faces.faces_to_cell_array(self.T),
weights_type='uniform')
adj, W = self._adjW
return ARAPVertexSolver(adj, W, self._s.V.copy())
def main():
parser = argparse.ArgumentParser()
parser.add_argument('input', type=str)
parser.add_argument('-c', dest='camera_actions', type=str, default=[],
action='append', help='camera actions')
args = parser.parse_args()
z = np.load(args.input)
vis = VisualiseMesh()
# V0 (purple)
V0 = z['V0']
vis.add_mesh(V0, z['T'], actor_name='V0')
lut = vis.actors['V0'].GetMapper().GetLookupTable()
lut.SetTableValue(0, *int2dbl(255, 0, 255))
# V0 w/ X (green)
T_ = faces_to_cell_array(z['T'])
adj, W = weights.weights(V0, T_, weights_type='cotan')
solveV0_X = ARAPVertexSolver(adj, W, V0)
rotM = lambda x: quat.rotationMatrix(quat.quat(x))
V0_X = solveV0_X(map(rotM, z['X']))
V0_X += register.displacement(V0_X, z['V'])
vis.add_mesh(V0_X, z['T'], actor_name='V0_X')
lut = vis.actors['V0_X'].GetMapper().GetLookupTable()
lut.SetTableValue(0, *int2dbl(0, 255, 0))
# V0 w/ Xg (yellow)
if 'Xg' in z.keys():
Xg = z['Xg'][0]
qg = quat.quat(Xg)
Q = [quat.quatMultiply(quat.quat(x), qg) for x in z['X']]
V0_Xg = solveV0_X([quat.rotationMatrix(q) for q in Q])
V0_Xg += register.displacement(V0_Xg, z['V'])
vis.add_mesh(V0_Xg, z['T'], actor_name='V0_Xg')
lut = vis.actors['V0_Xg'].GetMapper().GetLookupTable()
lut.SetTableValue(0, *int2dbl(255, 255, 0))
# V (blue)
vis.add_mesh(z['V'], z['T'], actor_name='V')
# input frame
vis.add_image(z['input_frame'])
# projection constraints
vis.add_projection(z['C'], z['P'])
# apply camera actions sequentially
for action in args.camera_actions:
method, tup, save_after = parse_camera_action(action)
print '%s(*%s), save_after=%s' % (method, tup, save_after)
vis.camera_actions((method, tup))
vis.execute()
def _add_sectioned_arap(self):
if self.core_V is None:
return
# calculate `Xi`
ki = self['ki']
Xb = self['Xb']
y = self['y']
X = self['X']
N = self.core_V.shape[0]
Xi = np.zeros((N, 3), dtype=np.float64)
iter_ki = iter(ki)
for i in xrange(N):
n = next(iter_ki)
if n == 0:
pass
elif n < 0:
Xi[i, :] = X[next(iter_ki)]
else:
yi, Xbi = [], []
for j in xrange(n):
Xbi.append(Xb[next(iter_ki)])
yi.append(y[next(iter_ki)])
# FIXME Potential wrong order and will need to check when
# multiple local basis rotations
Xi[i, :] = reduce(add, map(mul, yi, Xbi))
# setup `solve_V`
T = self['T']
core_V = self.core_V.copy()
adj, W = weights(core_V, faces_to_cell_array(T), weights_type='uniform')
solve_V = ARAPVertexSolver(adj, W, core_V)
# solve for `V1`
rotM = lambda x: rotationMatrix(quat(x))
V1 = solve_V(map(lambda x: rotM(x), Xi))
# apply global rotation and scale
A = self['s'] * rotM(np.ravel(self['Xg']))
V1 = np.dot(V1, np.transpose(A))
# register by translation to the instance vertices
V1 += register.displacement(V1, self[self.vertices_key])
# add as orange actor
self.vis.add_mesh(V1, T, actor_name='arap',
is_base=False,
compute_normals=self.compute_normals,
color=(255, 170, 0))
def _add_deprecated_sectioned_arap(self):
if self.core_V is None:
return
# calculate `Xi`
K = self['K']
Xb = self['Xb']
X = self['X']
y = self['y']
N = self.core_V.shape[0]
Xi = np.zeros((N, 3), dtype=np.float64)
for i in xrange(N):
if K[i, 0] == 0:
pass
elif K[i, 0] < 0:
Xi[i,:] = X[K[i, 1]]
else:
Xi[i,:] = axScale(y[K[i, 0] - 1], Xb[K[i, 1]])
# setup `solve_V`
T = self['T']
core_V = self.core_V.copy()
adj, W = weights(core_V, faces_to_cell_array(T), weights_type='uniform')
solve_V = ARAPVertexSolver(adj, W, core_V)
# solve for `V1`
rotM = lambda x: rotationMatrix(quat(x))
V1 = solve_V(map(lambda x: rotM(x), Xi))
# apply global rotation and scale
A = self['s'] * rotM(np.ravel(self['Xg']))
V1 = np.dot(V1, np.transpose(A))
# register by translation to the instance vertices
V1 += register.displacement(V1, self[self.vertices_key])
# add as orange actor
self.vis.add_mesh(V1, T, actor_name='arap',
is_base=False,
color=(255, 170, 0))
def _add_regular_arap(self):
if self['y'] is not None or self.core_V is None:
return
T = self['T']
core_V = self.core_V.copy()
adj, W = weights(core_V, faces_to_cell_array(T), weights_type='uniform')
solve_V = ARAPVertexSolver(adj, W, core_V)
rotM = lambda x: rotationMatrix(quat(x))
V1 = solve_V(map(lambda x: rotM(x), self['X']))
xg = np.ravel(self['Xg'])
A = self['s'] * rotM(xg)
V1 = np.dot(V1, np.transpose(A))
V1 += register.displacement(V1, self[self.vertices_key])
self.vis.add_mesh(V1, T, actor_name='arap', is_base=False)
lut = self.vis.actors['arap'].GetMapper().GetLookupTable()
lut.SetTableValue(0, 1., 0.667, 0.)
def _add_basis_arap(self):
if self.core_V is None:
return
X = self['X']
y = self['y']
if not isinstance(y, np.ndarray) or len(X) != y.shape[0]:
return
T = self['T']
core_V = self.core_V.copy()
adj, W = weights(core_V, faces_to_cell_array(T), weights_type='uniform')
solve_V = ARAPVertexSolver(adj, W, core_V)
scaled_X = []
for y_, X_ in izip(y, X):
scaled_X.append(map(lambda x: axScale(y_, x), X_))
N = core_V.shape[0]
X = []
for i in xrange(N):
X.append(reduce(axAdd, [X_[i] for X_ in scaled_X]))
rotM = lambda x: rotationMatrix(quat(x))
V1 = solve_V(map(lambda x: rotM(x), X))
xg = np.ravel(self['Xg'])
A = self['s'] * rotM(xg)
V1 = np.dot(V1, np.transpose(A))
V1 += register.displacement(V1, self[self.vertices_key])
self.vis.add_mesh(V1, T, actor_name='arap', is_base=False)
lut = self.vis.actors['arap'].GetMapper().GetLookupTable()
lut.SetTableValue(0, 1., 0., 1.)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('input', type=str)
parser.add_argument('-c',
dest='camera_actions',
type=str,
default=[],
action='append',
help='camera actions')
parser.add_argument('--mean_centre', action='store_true', default=False)
args = parser.parse_args()
print 'args.input:', args.input
files = filter(lambda s: s.endswith('.npz'), os.listdir(args.input))
def sort_key(filename):
root, ext = os.path.splitext(filename)
try:
return int(root)
except ValueError:
return -1
files = map(lambda f: os.path.join(args.input, f),
sorted(files, key=sort_key))
print 'input:'
pprint(files)
# `V0` taken from first frame
print 'V0 <- ', files[0]
z = np.load(files[0])
V0 = z['V']
if args.mean_centre:
V0 -= np.mean(V0, axis=0)
T = z['T']
vis = VisualiseMesh()
# V0 (purple)
vis.add_mesh(V0, T, actor_name='V0')
lut = vis.actors['V0'].GetMapper().GetLookupTable()
lut.SetTableValue(0, *int2dbl(255, 0, 255))
# setup solveV0_X
T_ = faces_to_cell_array(z['T'])
adj, W = weights.weights(V0, T_, weights_type='cotan')
solveV0_X = ARAPVertexSolver(adj, W, V0)
# setup color map
cmap = cm.jet(np.linspace(0., 1., len(files) - 1))
# function to translate axis-angle to rotation matrices
rotM = lambda x: quat.rotationMatrix(quat.quat(x))
# add each actor
for i, file_ in enumerate(files[1:]):
# load instance file
print 'V0_X[%d] <- ' % i, file_
z = np.load(file_)
# output scale and global rotation (axis-angle)
def safe_print(var):
try:
v = z[var].squeeze()
except KeyError:
return
print ' `%s`:' % var, np.around(v, decimals=3)
safe_print('s')
safe_print('Xg')
# solve for the new coordinates and mean centre
V0_X = solveV0_X(map(rotM, z['X']))
if args.mean_centre:
V0_X -= np.mean(V0_X, axis=0)
# add actor and adjust lookup table for visualisation
actor_name = 'V0_X_%d' % i
vis.add_mesh(V0_X, z['T'], actor_name=actor_name)
lut = vis.actors[actor_name].GetMapper().GetLookupTable()
lut.SetTableValue(0, *cmap[i, :3])
# apply camera actions sequentially
for action in args.camera_actions:
method, tup, save_after = parse_camera_action(action)
print '%s(*%s), save_after=%s' % (method, tup, save_after)
vis.camera_actions((method, tup))
vis.execute()
return
# V0 w/ X (green)
V0_X = solveV0_X([quat.rotationMatrix(quat.quat(x)) for x in z['X']])
vis.add_mesh(V0_X, z['T'], actor_name='V0_X')
lut = vis.actors['V0_X'].GetMapper().GetLookupTable()
lut.SetTableValue(0, *int2dbl(0, 255, 0))
# V0 w/ Xg (yellow)
qg = quat.quat(z['Xg'][0])
Q = [quat.quatMultiply(quat.quat(x), qg) for x in z['X']]
V0_Xg = solveV0_X([quat.rotationMatrix(q) for q in Q])
vis.add_mesh(V0_Xg, z['T'], actor_name='V0_Xg')
lut = vis.actors['V0_Xg'].GetMapper().GetLookupTable()
lut.SetTableValue(0, *int2dbl(255, 255, 0))
# V (blue)
vis.add_mesh(z['V'], z['T'], actor_name='V')
# input frame
vis.add_image(z['input_frame'])
# projection constraints
vis.add_projection(z['C'], z['P'])
def main():
# Input
lambdas = np.r_[1e0, 1e0].astype(np.float64)
V, T = box_model(3, 20, 1.0, 1.0)
# Setup `solve_V_X`
adj, W = weights.weights(V,
faces.faces_to_cell_array(T),
weights_type='cotan')
solve_V_X = ARAPVertexSolver(adj, W, V)
# Setup `solve_single`
def solve_single(C, P):
X = np.zeros_like(V)
Xg = np.zeros((1, 3), dtype=np.float64)
s = np.ones((1, 1), dtype=np.float64)
V1 = V.copy()
status = solve_single_rigid_arap_proj(V,
T,
X,
Xg,
s,
V1,
C,
P,
lambdas,
uniformWeights=False,
maxIterations=100,
updateThreshold=1e-6,
gradientThreshold=1e-6,
improvementThreshold=1e-6)
return X, V1
# Setup `C`, `P1` and `P2`
heights = np.unique(V[:, 2])
C1 = np.argwhere(V[:, 2] >= heights[-3]).flatten()
L1 = C1.shape[0]
C2 = np.argwhere(V[:, 2] <= heights[2]).flatten()
L2 = C2.shape[0]
C = np.r_[C1, C2]
P1 = V[C, :2].copy()
P1[:L1, 1] += 10.0
P2 = V[C, :2].copy()
P2[:L1, 0] += 10.0
# Solve for `X1` and `X2`
X1, V1 = solve_single(C, P1)
X2, V2 = solve_single(C, P2)
# Setup `V_from_X1_X2` which "interpolates" `X1` and `X2`
def V_from_X1_X2(a, b):
X12 = map(lambda x: axis_angle.axMakeInterpolated(a, x[0], b, x[1]),
izip(X1, X2))
V12 = solve_V_X(map(lambda x: quat.rotationMatrix(quat.quat(x)), X12))
# Register bottom fixed layers
A, d = right_multiply_rigid_transform(V12[C[L1:]], V[C[L1:]])
V12 = np.dot(V12, A) + d
return V12
# Visualise the interpolation of the distortions
t = np.linspace(-2., 2., 5, endpoint=True)
N = t.shape[0] * t.shape[0]
cmap = cm.jet(np.linspace(0., 1., N, endpoint=True))
vis = VisualiseMesh()
for i, (u, v) in enumerate(product(t, t)):
actor_name = 'V12_%d' % i
V12 = V_from_X1_X2(u, v)
vis.add_mesh(V12, T, actor_name=actor_name)
# Change color of actor
lut = vis.actors[actor_name].GetMapper().GetLookupTable()
lut.SetTableValue(0, *cmap[i, :3])
# Change actor to dense surface (instead of default wireframe)
vis.actor_properties(actor_name, ('SetRepresentation', (3, )))
vis.camera_actions(('SetParallelProjection', (True, )))
vis.execute(magnification=4)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('input', type=str)
parser.add_argument('aux_scales', type=str)
parser.add_argument('-c',
dest='camera_actions',
type=str,
default=[],
action='append',
help='camera actions')
parser.add_argument('-o',
dest='output_directory',
type=str,
default=None,
help='output directory')
parser.add_argument('--rotations_index',
type=int,
default=None,
help='rotations index')
parser.add_argument('--magnification',
type=int,
default=1,
help='magnification')
parser.add_argument('--rigidly_register',
action='store_true',
default=False)
parser.add_argument('--normalise_rotations',
action='store_true',
default=False)
args = parser.parse_args()
print ctime()
print 'args:'
pprint(args.__dict__)
z = np.load(args.input)
vis = VisualiseMesh()
# V0 (purple)
V0 = z['V']
vis.add_mesh(V0, z['T'], actor_name='V0')
lut = vis.actors['V0'].GetMapper().GetLookupTable()
lut.SetTableValue(0, *int2dbl(255, 0, 255))
# setup `solveV0_X`
T_ = faces_to_cell_array(z['T'])
adj, W = weights.weights(V0, T_, weights_type='cotan')
solveV0_X = ARAPVertexSolver(adj, W, V0)
# load X
base_X = z['X']
if args.rotations_index is not None:
base_X = base_X[args.rotations_index]
if args.normalise_rotations:
max_ = np.amax(np.sqrt(np.sum(base_X * base_X, axis=1)))
base_X /= max_
# show additional scales
aux_scales = eval(args.aux_scales)
print 'aux_scales: ', aux_scales
rotM = lambda x: quat.rotationMatrix(quat.quat(x))
N = len(aux_scales)
cmap = cm.jet(np.linspace(0., 1., N, endpoint=True))
for i, scale in enumerate(aux_scales):
print 'scale:', scale
X = map(lambda x: axScale(scale, x), base_X)
V0_X = solveV0_X(map(rotM, X))
if args.rigidly_register:
A, d = right_multiply_rigid_uniform_scale_transform(V0_X, V0)
V0_X = np.dot(V0_X, A) + d
actor_name = 'V0_X_%d' % i
print 'actor_name:', actor_name
vis.add_mesh(V0_X, z['T'], actor_name=actor_name)
lut = vis.actors[actor_name].GetMapper().GetLookupTable()
lut.SetTableValue(0, *cmap[i, :3])
vis.actor_properties(actor_name, ('SetRepresentation', (3, )))
# input frame
try:
input_frame = z['input_frame']
except KeyError:
pass
else:
vis.add_image(input_frame)
# is visualisation interface or to file?
interactive_session = args.output_directory is None
# setup output directory
if not interactive_session and not os.path.exists(args.output_directory):
print 'Creating directory: ', args.output_directory
os.makedirs(args.output_directory)
# n is the index for output files
n = count(0)
# apply camera actions sequentially
for action in args.camera_actions:
method, tup, save_after = parse_camera_action(action)
print '%s(*%s), save_after=%s' % (method, tup, save_after)
vis.camera_actions((method, tup))
# save if required
if not interactive_session and save_after:
full_path = os.path.join(args.output_directory, '%d.png' % next(n))
print 'Output: ', full_path
vis.write(full_path, magnification=args.magnification)
# show if interactive
if interactive_session:
print 'Interactive'
vis.execute(magnification=args.magnification)