def exp1(W, pt_index, mvt, pathes):
"""
Moving one point with different weights
----
input:
W: float list of length N -> the different weights
pt_index: int -> the index of the vertex we want to move
mvt: float list of length 3 -> the shift we want to apply to the vertex
pathes: 3-tuple -> path to the surfacic mesh, the volumetric .obj and
the volunetric .mesh, in this order
----
output:
times: float array of shape (3, N) -> computation time for each mesh
and for each weight
"""
times = [[], [], []]
v, f = igl.read_triangle_mesh(pathes[0])
anchors = np.array([v[pt_index] + mvt], dtype=np.double)
anchors_id = np.array([pt_index], dtype=np.int)
for w in W:
print("Experience 1, w = {}".format(w))
t1 = time()
v, f = lp_ed.laplacian_editing(pathes[0],
anchors,
anchors_id,
tetra=False,
custom_weight=[w])
lp_ed.save_mesh("exp1_tri_w={}.obj".format(w), v, f)
t2 = time()
v, f = lp_ed.laplacian_editing(pathes[1],
anchors,
anchors_id,
tetra=False,
custom_weight=[w])
lp_ed.save_mesh("exp1_tet_tri_w={}.obj".format(w), v, f)
t3 = time()
v, f = lp_ed.laplacian_editing(pathes[2],
anchors,
anchors_id,
tetra=True,
custom_weight=[w])
lp_ed.save_mesh("exp1_tet_tet_w={}.obj".format(w), v, f)
t4 = time()
times[0].append(t2 - t1)
times[1].append(t3 - t2)
times[2].append(t4 - t3)
dt1, dt2, dt3 = times[0][-1], times[1][-1], times[2][-1]
print(f"tri: {dt1}s, tet_tri: {dt2}s, tet_tet: {dt3}s")
print(times)
print("Total time using tri:", sum(times[0]))
print("Total time using tet_tri:", sum(times[1]))
print("Total time using tet_tet:", sum(times[2]))
return times
path_to_model = "../data/Wikihuman_project/obj/Corrected_Emily_2_1_closed_color.obj"
path_to_vertex_keypoints = "data/vertex_keypoints_emily.txt"
path_to_triangulated_keypoints = "data/triangulated_keypoints_emily.txt"
"""""""""""""""""""""""""""""""""
" Creating new obj file "
"""""""""""""""""""""""""""""""""
_, anchors_id = recover_keypoints(path_to_vertex_keypoints,
have_indices=True)
mean_landmarks_dlib = recover_keypoints(path_to_triangulated_keypoints,
have_indices=False)
"""
# Using the laplacian_meshes module
mesh = LaplacianMesh.PolyMesh()
mesh.loadFile(path_to_model)
mesh = LaplacianMesh.solveLaplacianMesh(mesh, mean_landmarks_dlib,
np.array(anchors_id),
cotangent=True)
mesh.saveFile("laplacian_edition.obj")
"""
# Using laplacian8editing.py from this project
v, f = laplacian_editing.laplacian_editing(path_to_model,
mean_landmarks_dlib,
anchors_id)
laplacian_editing.save_mesh("data/meshes/test.obj", v, f)
print("New .obj file created")
def exp5(W, path_kpt_Emily, path_kpt_BEE10, pathes):
"""
We try to close the eyes. To do so we use the BEE10 database since the
person has here eyes closed
----
input:
path_kpt_Emily: str -> path to the txt file where Emily's keypoints
are stored
path_kpt_BEE10: str -> path to the txt file where BEE10's keypoints
are stored
pathes: 3-tuple -> path to the surfacic mesh, the volumetric .obj and
the volunetric .mesh, in this order
----
output:
times: float array of shape (3, N) -> computation time for each mesh
and for each weight
"""
times = [[], [], []]
kpt_Emily = recover_keypoints(path_kpt_Emily, have_indices=False)
kpt_BEE10 = recover_keypoints(path_kpt_BEE10, have_indices=False)
_, BEE10_fit, _ = procrustes(kpt_Emily, kpt_BEE10)
*_, anchors_id, _ = tfm.find_closest_vertices(kpt_Emily, pathes[0])
anchors = BEE10_fit[36:48] # Eyes
anchors_id = anchors_id[36:48]
for w in W:
print("Experience 5, w = {}".format(w))
w_list = [w] * len(anchors)
t1 = time()
v, f = lp_ed.laplacian_editing(pathes[0],
anchors,
anchors_id,
tetra=False,
custom_weight=w_list)
lp_ed.save_mesh("exp5_tri_w={}.obj".format(w), v, f)
t2 = time()
v, f = lp_ed.laplacian_editing(pathes[1],
anchors,
anchors_id,
tetra=False,
custom_weight=w_list)
lp_ed.save_mesh("exp5_tet_tri_w={}.obj".format(w), v, f)
t3 = time()
v, f = lp_ed.laplacian_editing(pathes[2],
anchors,
anchors_id,
tetra=True,
custom_weight=w_list)
lp_ed.save_mesh("exp5_tet_tet_w={}.obj".format(w), v, f)
t4 = time()
times[0].append(t2 - t1)
times[1].append(t3 - t2)
times[2].append(t4 - t3)
dt1, dt2, dt3 = times[0][-1], times[1][-1], times[2][-1]
print(f"tri: {dt1}s, tet_tri: {dt2}s, tet_tet: {dt3}s")
print(times)
print("Total time using tri:", sum(times[0]))
print("Total time using tet_tri:", sum(times[1]))
print("Total time using tet_tet:", sum(times[2]))
return times
def exp4(W, pt_index, radius, anchor_index, mvt, pathes):
"""
Moving every vertex around one by the same amount
----
input:
W: float list of length N -> the different weights
pt_index: int -> the index of the central vertex we want to move
radius: float -> each vertex whose distance to the center is less than
radius will have to move
mvt: float list of length 3 -> the shift we want to apply to the vertex
pathes: 3-tuple -> path to the surfacic mesh, the volumetric .obj and
the volunetric .mesh, in this order
----
output:
times: float array of shape (3, N) -> computation time for each mesh
and for each weight
"""
times = [[], [], []]
v, f = igl.read_triangle_mesh(pathes[0])
center = v[pt_index]
indices = np.array(
[i for i in range(len(v)) if np.linalg.norm(v[i] - center) < radius] +
[anchor_index],
dtype=np.int)
anchors = v[indices] + mvt
anchors[-1] = v[anchor_index]
for w1 in W:
for w2 in W:
print("Experience 4, w1 = {}, w2 = {}".format(w1, w2))
w_list = [w1] * (len(anchors) - 1) + [w2]
t1 = time()
v, f = lp_ed.laplacian_editing(pathes[0],
anchors,
indices,
tetra=False,
custom_weight=w_list)
lp_ed.save_mesh("exp4_tri_w1={}_w2={}.obj".format(w1, w2), v, f)
t2 = time()
v, f = lp_ed.laplacian_editing(pathes[1],
anchors,
indices,
tetra=False,
custom_weight=w_list)
lp_ed.save_mesh("exp4_tet_tri_w1={}_w2={}.obj".format(w1, w2), v,
f)
t3 = time()
v, f = lp_ed.laplacian_editing(pathes[2],
anchors,
indices,
tetra=True,
custom_weight=w_list)
lp_ed.save_mesh("exp4_tet_tet_w1={}_w2={}.obj".format(w1, w2), v,
f)
t4 = time()
times[0].append(t2 - t1)
times[1].append(t3 - t2)
times[2].append(t4 - t3)
dt1, dt2, dt3 = times[0][-1], times[1][-1], times[2][-1]
print(f"tri: {dt1}s, tet_tri: {dt2}s, tet_tet: {dt3}s")
print(times)
print("Total time using tri:", sum(times[0]))
print("Total time using tet_tri:", sum(times[1]))
print("Total time using tet_tet:", sum(times[2]))
return times