bnd_uv = igl.eigen.MatrixXd() igl.map_vertices_to_circle(V, bnd, bnd_uv) igl.harmonic(V, F, bnd, bnd_uv, 1, initial_guess) # Add dynamic regularization to avoid to specify boundary conditions arap_data = igl.ARAPData() arap_data.with_dynamics = True b = igl.eigen.MatrixXi.Zero(0, 0) bc = igl.eigen.MatrixXd.Zero(0, 0) # Initialize ARAP arap_data.max_iter = 100 # 2 means that we're going to *solve* in 2d igl.arap_precomputation(V, F, 2, b, arap_data) # Solve arap using the harmonic map as initial guess V_uv = igl.eigen.MatrixXd(initial_guess) # important, make a copy of it! igl.arap_solve(bc, arap_data, V_uv) # Scale UV to make the texture more clear V_uv *= 20 # Plot the mesh viewer = igl.glfw.Viewer() viewer.data().set_mesh(V, F) viewer.data().set_uv(V_uv) viewer.callback_key_down = key_down
bnd_uv = igl.eigen.MatrixXd() igl.map_vertices_to_circle(V, bnd, bnd_uv) igl.harmonic(V, F, bnd, bnd_uv, 1, initial_guess) # Add dynamic regularization to avoid to specify boundary conditions arap_data = igl.ARAPData() arap_data.with_dynamics = True b = igl.eigen.MatrixXi.Zero(0, 0) bc = igl.eigen.MatrixXd.Zero(0, 0) # Initialize ARAP arap_data.max_iter = 100 # 2 means that we're going to *solve* in 2d igl.arap_precomputation(V, F, 2, b, arap_data) # Solve arap using the harmonic map as initial guess V_uv = igl.eigen.MatrixXd(initial_guess) # important, make a copy of it! igl.arap_solve(bc, arap_data, V_uv) # Scale UV to make the texture more clear V_uv *= 20 # Plot the mesh viewer = igl.viewer.Viewer() viewer.data.set_mesh(V, F) viewer.data.set_uv(V_uv) viewer.callback_key_down = key_down
igl.readOFF(TUTORIAL_SHARED_PATH + "decimated-knight.off", V, F)
U = igl.eigen.MatrixXd(V)
igl.readDMAT(TUTORIAL_SHARED_PATH + "decimated-knight-selection.dmat", S)
# Vertices in selection
b = igl.eigen.MatrixXd([[t[0] for t in [(i, S[i]) for i in range(0, V.rows())] if t[1] >= 0]]).transpose().castint()
# Centroid
mid = 0.5 * (V.colwiseMaxCoeff() + V.colwiseMinCoeff())
# Precomputation
arap_data.max_iter = 100
igl.arap_precomputation(V, F, V.cols(), b, arap_data)
# Set color based on selection
C = igl.eigen.MatrixXd(F.rows(), 3)
purple = igl.eigen.MatrixXd([[80.0 / 255.0, 64.0 / 255.0, 255.0 / 255.0]])
gold = igl.eigen.MatrixXd([[255.0 / 255.0, 228.0 / 255.0, 58.0 / 255.0]])
for f in range(0, F.rows()):
if S[F[f, 0]] >= 0 and S[F[f, 1]] >= 0 and S[F[f, 2]] >= 0:
C.setRow(f, purple)
else:
C.setRow(f, gold)
# Plot the mesh with pseudocolors
viewer = igl.glfw.Viewer()
viewer.data().set_mesh(U, F)
igl.readOFF(TUTORIAL_SHARED_PATH + "decimated-knight.off", V, F)
U = igl.eigen.MatrixXd(V)
igl.readDMAT(TUTORIAL_SHARED_PATH + "decimated-knight-selection.dmat", S)
# Vertices in selection
b = igl.eigen.MatrixXd([[
t[0] for t in [(i, S[i]) for i in range(0, V.rows())] if t[1] >= 0
]]).transpose().castint()
# Centroid
mid = 0.5 * (V.colwiseMaxCoeff() + V.colwiseMinCoeff())
# Precomputation
arap_data.max_iter = 100
igl.arap_precomputation(V, F, V.cols(), b, arap_data)
# Set color based on selection
C = igl.eigen.MatrixXd(F.rows(), 3)
purple = igl.eigen.MatrixXd([[80.0 / 255.0, 64.0 / 255.0, 255.0 / 255.0]])
gold = igl.eigen.MatrixXd([[255.0 / 255.0, 228.0 / 255.0, 58.0 / 255.0]])
for f in range(0, F.rows()):
if S[F[f, 0]] >= 0 and S[F[f, 1]] >= 0 and S[F[f, 2]] >= 0:
C.setRow(f, purple)
else:
C.setRow(f, gold)
# Plot the mesh with pseudocolors
viewer = igl.glfw.Viewer()
viewer.data().set_mesh(U, F)
def LaplacianDeform(depth_in, handle_3d, intrinsic=None, vis=False):
"""depth_ctrl is a reference Nx3 depth map
Args:
depth_in: the depth predicted by network
handle_3d: the control sparse points, in [x, y, z]
intrinsic: the intrinsic matrix
vis: whether visualize using igl
Output:
depth: the warpped depth through asap
"""
height, width = depth_in.shape[0], depth_in.shape[1]
depth_in, y, x, handle_3d = ReScale(depth_in,
handle_3d,
intrinsic,
get_image_coor=True)
point_3d = uts_3d.depth2xyz(depth_in, intrinsic, False)
select_id = y * width + x
# test_id = range(10)
# select_id = select_id[test_id]
one_hot = np.zeros((point_3d.shape[0]), dtype=np.int32)
one_hot[select_id] = 1
mesh_idx = uts_3d.grid_mesh(height, width)
V = igl.eigen.MatrixXd(np.float64(point_3d))
U = V
F = igl.eigen.MatrixXi(np.int32(mesh_idx))
S = igl.eigen.MatrixXd(np.float64(one_hot))
b = igl.eigen.MatrixXi(np.int32(select_id))
P_origin = igl.eigen.MatrixXd(np.float64(point_3d[select_id, :]))
P = igl.eigen.MatrixXd(np.float64(handle_3d))
bc = igl.eigen.MatrixXd(np.float64(handle_3d))
arap_data = igl.ARAPData()
# Set color based on selection
# C = igl.eigen.MatrixXd(F.rows(), 3)
# purple = igl.eigen.MatrixXd([[80.0 / 255.0, 64.0 / 255.0, 255.0 / 255.0]])
# gold = igl.eigen.MatrixXd([[255.0 / 255.0, 228.0 / 255.0, 58.0 / 255.0]])
# pdb.set_trace()
# for f in range(0, F.rows()):
# if S[F[f, 0]] > 0 or S[F[f, 1]] > 0 or S[F[f, 2]] > 0:
# C.setRow(f, purple)
# else:
# C.setRow(f, gold)
# # Plot the mesh with pseudocolors
# viewer = igl.viewer.Viewer()
# viewer.data.set_mesh(V, F)
# viewer.data.set_colors(C)
# viewer.core.is_animating = False
# viewer.launch()
if vis:
viewer = igl.viewer.Viewer()
viewer.data.set_mesh(U, F)
viewer.data.add_points(P, igl.eigen.MatrixXd([[1, 0, 0]]))
viewer.core.is_animating = False
viewer.launch()
# start compute deform
arap_data.max_iter = 30
arap_data.ym = 450
igl.arap_precomputation(V, F, V.cols(), b, arap_data)
igl.arap_solve(bc, arap_data, U)
if vis:
viewer = igl.viewer.Viewer()
viewer.data.set_mesh(V, F)
# viewer.data.add_points(P_origin, igl.eigen.MatrixXd([[0, 0, 1]]))
# viewer.data.add_points(P, igl.eigen.MatrixXd([[0, 1, 0]]))
viewer.core.is_animating = False
viewer.launch()
point_3d_new = np.float32(np.array(U, dtype='float64', order='C'))
depth = uts_3d.xyz2depth(point_3d_new, intrinsic, depth_in.shape)
mask = depth <= 0
max_depth = np.max(depth)
depth_inpaint = cv2.inpaint(np.uint8(depth / max_depth * 255),
np.uint8(mask), 5, cv2.INPAINT_TELEA)
depth[mask] = np.float32(depth_inpaint[mask]) * max_depth / 255
return depth
