def Decimate_mesh(meshvtk,name_vtkmesh,nvertices=2000):
print 'test'
stlWriter = vtk.vtkSTLWriter()
stlWriter.SetFileName('meshdecimated.stl')
stlWriter.SetInputData(meshvtk)
stlWriter.Write()
mesh_om = om.PolyMesh()
Result=om.read_mesh(mesh_om, "meshdecimated.stl")
print Result
deci_om=om.PolyMeshDecimater(mesh_om)
mh=om.PolyMeshModQuadricHandle()
deci_om.add(mh)
deci_om.initialize()
deci_om.decimate_to(nvertices)
mesh_om.garbage_collection()
assert mesh_om.n_vertices()==nvertices, 'vertices goal not acomplished; nvertices={0:d}'.format(mesh_om.n_vertices())
print "Decimation to {0} vertices Sucessful".format(nvertices)
om.write_mesh(mesh_om,'meshdecimated.stl')
stlReader = vtk.vtkSTLReader()
stlReader.SetFileName('meshdecimated.stl')
stlReader.Update()
vtkwrite=vtk.vtkPolyDataWriter()
vtkwrite.SetInputData(stlReader.GetOutput())
vtkwrite.SetFileName(name_vtkmesh)
vtkwrite.Write()
print "enters"
def test_write_triangle(self):
filename = "triangle-minimal.om";
# Generate data
v1 = self.mesh.add_vertex(openmesh.Vec3d(1.0, 0.0, 0.0))
v2 = self.mesh.add_vertex(openmesh.Vec3d(0.0, 1.0, 0.0))
v3 = self.mesh.add_vertex(openmesh.Vec3d(0.0, 0.0, 1.0))
self.mesh.add_face(v1, v2, v3)
# Save
ok = openmesh.write_mesh(self.mesh, filename)
self.assertTrue(ok)
# Reset
self.mesh.clear()
# Load
ok = openmesh.read_mesh(self.mesh, filename)
self.assertTrue(ok)
# Compare
self.assertEqual(self.mesh.n_vertices(), 3)
self.assertEqual(self.mesh.n_edges(), 3)
self.assertEqual(self.mesh.n_faces(), 1)
self.assertEqual(self.mesh.point(v1), openmesh.Vec3d(1.0, 0.0, 0.0))
self.assertEqual(self.mesh.point(v2), openmesh.Vec3d(0.0, 1.0, 0.0))
self.assertEqual(self.mesh.point(v3), openmesh.Vec3d(0.0, 0.0, 1.0))
# Cleanup
os.remove(filename)
def test_write_and_read_vertex_colors_to_and_from_off_file(self):
self.mesh.request_vertex_colors()
self.mesh.add_vertex(openmesh.Vec3d(0, 0, 1))
self.mesh.add_vertex(openmesh.Vec3d(0, 1, 0))
self.mesh.add_vertex(openmesh.Vec3d(0, 1, 1))
self.mesh.add_vertex(openmesh.Vec3d(1, 0, 1))
# Using the default openmesh Python color type
testColor = openmesh.Vec4f(1.0, 0.5, 0.25, 1.0)
# Setting colors (different from black)
for v in self.mesh.vertices():
self.mesh.set_color(v, testColor)
# Check if the colors are correctly set
count = 0
for v in self.mesh.vertices():
color = self.mesh.color(v)
if color[0] != testColor[0] or color[1] != testColor[1] or color[2] != testColor[2]:
count += 1
self.assertEqual(count, 0)
options = openmesh.Options()
options += openmesh.Options.VertexColor
options += openmesh.Options.ColorFloat
openmesh.write_mesh(self.mesh, "temp.off", options)
openmesh.read_mesh(self.mesh, "temp.off", options)
# Check if vertices still have the same color
count = 0
for v in self.mesh.vertices():
color = self.mesh.color(v)
if color[0] != testColor[0] or color[1] != testColor[1] or color[2] != testColor[2]:
count += 1
self.assertEqual(count, 0)
self.mesh.release_vertex_colors()
def test_write_and_read_binary_float_vertex_colors_to_and_from_off_file(self):
self.mesh.request_vertex_colors()
options = openmesh.Options(openmesh.Options.VertexColor)
ok = openmesh.read_mesh(self.mesh, "meshlab.ply", options)
self.assertTrue(ok)
options.clear()
options += openmesh.Options.VertexColor
options += openmesh.Options.Binary
options += openmesh.Options.ColorFloat
# Write the mesh
ok = openmesh.write_mesh(self.mesh, "cube_floating_binary.off", options)
self.assertTrue(ok)
self.mesh.clear()
options.clear()
options += openmesh.Options.VertexColor
options += openmesh.Options.Binary
options += openmesh.Options.ColorFloat
ok = openmesh.read_mesh(self.mesh, "cube_floating_binary.off", options)
self.assertTrue(ok)
self.assertEqual(self.mesh.n_vertices(), 8)
self.assertEqual(self.mesh.n_edges(), 18)
self.assertEqual(self.mesh.n_faces(), 12)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(0))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(0))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(0))[2], 1.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(3))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(3))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(3))[2], 1.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(4))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(4))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(4))[2], 1.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(7))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(7))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(7))[2], 1.0)
self.assertFalse(options.vertex_has_normal())
self.assertFalse(options.vertex_has_texcoord())
self.assertFalse(options.face_has_color())
self.assertTrue(options.vertex_has_color())
self.assertTrue(options.color_is_float())
self.assertTrue(options.is_binary())
self.mesh.release_vertex_colors()
def test_write_and_read_binary_ply_with_float_vertex_colors(self):
self.mesh.request_vertex_colors()
options = openmesh.Options()
options += openmesh.Options.VertexColor
ok = openmesh.read_mesh(self.mesh, "meshlab.ply", options)
self.assertTrue(ok)
options += openmesh.Options.ColorFloat
options += openmesh.Options.Binary
ok = openmesh.write_mesh(self.mesh, "meshlab_binary_float.ply", options)
self.assertTrue(ok)
self.mesh.clear
ok = openmesh.read_mesh(self.mesh, "meshlab_binary_float.ply", options)
self.assertTrue(ok)
self.assertEqual(self.mesh.n_vertices(), 8)
self.assertEqual(self.mesh.n_edges(), 18)
self.assertEqual(self.mesh.n_faces(), 12)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(0))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(0))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(0))[2], 1.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(3))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(3))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(3))[2], 1.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(4))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(4))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(4))[2], 1.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(7))[0], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(7))[1], 0.0)
self.assertEqual(self.mesh.color(self.mesh.vertex_handle(7))[2], 1.0)
self.assertFalse(options.vertex_has_normal())
self.assertFalse(options.vertex_has_texcoord())
self.assertTrue(options.vertex_has_color())
self.assertTrue(options.color_is_float())
self.assertTrue(options.is_binary())
self.mesh.release_vertex_colors()
def test(net=None, save_subdir="test"):
opt.phase = "test"
dataset = build_dataset(opt)
if opt.dim == 3:
init_cage_V, init_cage_Fs = loadInitCage([opt.template])
cage_V_t = init_cage_V.transpose(1, 2).detach().cuda()
else:
init_cage_V = generatePolygon(0, 0, 1.5, 0, 0, 0, opt.cage_deg)
init_cage_V = torch.tensor([(x, y) for x, y in init_cage_V],
dtype=torch.float).unsqueeze(0)
cage_V_t = init_cage_V.transpose(1, 2).detach().cuda()
init_cage_Fs = [
torch.arange(opt.cage_deg, dtype=torch.int64).view(1, 1,
-1).cuda()
]
if net is None:
# network
net = networks.NetworkFull(
opt,
dim=opt.dim,
bottleneck_size=opt.bottleneck_size,
template_vertices=cage_V_t,
template_faces=init_cage_Fs[-1],
).cuda()
net.eval()
load_network(net, opt.ckpt)
else:
net.eval()
print(net)
dataloader = torch.utils.data.DataLoader(
dataset,
batch_size=1,
shuffle=False,
drop_last=False,
collate_fn=tolerating_collate,
num_workers=0,
worker_init_fn=lambda id: np.random.seed(np.random.get_state()[1][0] +
id))
test_output_dir = os.path.join(opt.log_dir, save_subdir)
os.makedirs(test_output_dir, exist_ok=True)
with open(os.path.join(test_output_dir, "eval.txt"), "w") as f:
with torch.no_grad():
for i, data in enumerate(dataloader):
data = dataset.uncollate(data)
############# blending ############
# sample 4 different alpha
if opt.blend_style:
num_alpha = 4
blend_alpha = torch.linspace(
0, 1, steps=num_alpha,
dtype=torch.float32).cuda().reshape(num_alpha, 1)
data["source_shape"] = data["source_shape"].expand(
num_alpha, -1, -1).contiguous()
data["target_shape"] = data["target_shape"].expand(
num_alpha, -1, -1).contiguous()
else:
blend_alpha = 1.0
data["alpha"] = blend_alpha
###################################
source_shape_t = data["source_shape"].transpose(
1, 2).contiguous().detach()
target_shape_t = data["target_shape"].transpose(
1, 2).contiguous().detach()
outputs = net(source_shape_t, target_shape_t, blend_alpha)
deformed = outputs["deformed"]
####################### evaluation ########################
s_filename = os.path.splitext(data["source_file"][0])[0]
t_filename = os.path.splitext(data["target_file"][0])[0]
log_str = "{}/{} {}-{} ".format(i, len(dataloader), s_filename,
t_filename)
print(log_str)
f.write(log_str + "\n")
###################### outputs ############################
for b in range(deformed.shape[0]):
if "source_mesh" in data and data[
"source_mesh"] is not None:
if isinstance(data["source_mesh"][0], str):
source_mesh = om.read_polymesh(
data["source_mesh"][0]).points().copy()
source_mesh = dataset.normalize(
source_mesh, opt.isV2)
source_mesh = torch.from_numpy(
source_mesh.astype(
np.float32)).unsqueeze(0).cuda()
deformed = deform_with_MVC(
outputs["cage"][b:b + 1],
outputs["new_cage"][b:b + 1],
outputs["cage_face"], source_mesh)
else:
deformed = deform_with_MVC(
outputs["cage"][b:b + 1],
outputs["new_cage"][b:b + 1],
outputs["cage_face"], data["source_mesh"])
deformed[b] = center_bounding_box(deformed[b])[0]
if data["source_face"] is not None and data[
"source_mesh"] is not None:
source_mesh = data["source_mesh"][0].detach().cpu()
source_mesh = center_bounding_box(source_mesh)[0]
source_face = data["source_face"][0].detach().cpu()
tosave = pymesh.form_mesh(vertices=source_mesh,
faces=source_face)
pymesh.save_mesh(os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sa.obj".format(s_filename, t_filename)),
tosave,
use_float=True)
tosave = pymesh.form_mesh(
vertices=deformed[0].detach().cpu(),
faces=source_face)
pymesh.save_mesh(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sab-{}.obj".format(
s_filename, t_filename, b)),
tosave,
use_float=True,
)
elif data["source_face"] is None and isinstance(
data["source_mesh"][0], str):
orig_file_path = data["source_mesh"][0]
mesh = om.read_polymesh(orig_file_path)
points_arr = mesh.points()
points_arr[:] = source_mesh[0].detach().cpu().numpy()
om.write_mesh(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sa.obj".format(s_filename, t_filename)),
mesh)
points_arr[:] = deformed[0].detach().cpu().numpy()
om.write_mesh(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sab-{}.obj".format(
s_filename, t_filename, b)), mesh)
else:
# save to "pts" for rendering
save_pts(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sa.pts".format(s_filename, t_filename)),
data["source_shape"][b].detach().cpu())
save_pts(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sab-{}.pts".format(
s_filename, t_filename, b)),
deformed[0].detach().cpu())
if data["target_face"] is not None and data[
"target_mesh"] is not None:
data["target_mesh"][0] = center_bounding_box(
data["target_mesh"][0])[0]
tosave = pymesh.form_mesh(
vertices=data["target_mesh"][0].detach().cpu(),
faces=data["target_face"][0].detach().cpu())
pymesh.save_mesh(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sb.obj".format(s_filename, t_filename)),
tosave,
use_float=True,
)
elif data["target_face"] is None and isinstance(
data["target_mesh"][0], str):
orig_file_path = data["target_mesh"][0]
mesh = om.read_polymesh(orig_file_path)
points_arr = mesh.points()
points_arr[:] = dataset.normalize(
points_arr.copy(), opt.isV2)
om.write_mesh(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sb.obj".format(s_filename, t_filename)),
mesh)
else:
save_pts(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-Sb.pts".format(s_filename, t_filename)),
data["target_shape"][0].detach().cpu())
outputs["cage"][b] = center_bounding_box(
outputs["cage"][b])[0]
outputs["new_cage"][b] = center_bounding_box(
outputs["new_cage"][b])[0]
pymesh.save_mesh_raw(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-cage1-{}.ply".format(
s_filename, t_filename, b)),
outputs["cage"][b].detach().cpu(),
outputs["cage_face"][0].detach().cpu(),
binary=True)
pymesh.save_mesh_raw(
os.path.join(
opt.log_dir, save_subdir,
"{}-{}-cage2-{}.ply".format(
s_filename, t_filename, b)),
outputs["new_cage"][b].detach().cpu(),
outputs["cage_face"][0].detach().cpu(),
binary=True)
dataset.render_result(test_output_dir)
if not os.path.exists(opt.outf):
os.makedirs(opt.outf)
PIL.Image.fromarray(sr_proj_img).save(opt.outf + "%04d_ours_s.png" % test_num)
if opt.step:
PIL.Image.fromarray(src_img).save(opt.outf + "%04d_src.png" % test_num)
PIL.Image.fromarray(ja_proj_img).save(opt.outf +
"%04d_ours_j.png" % test_num)
PIL.Image.fromarray(sa_proj_img).save(opt.outf +
"%04d_ours_a.png" % test_num)
PIL.Image.fromarray(ori_proj_img).save(opt.outf +
"%04d_hmr.png" % test_num)
if opt.mesh:
ja_mesh = make_trimesh(ja_verts, faces_smpl)
om.write_mesh(opt.outf + "%04d_mesh_j.obj" % test_num, ja_mesh)
sa_mesh = make_trimesh(sa_verts, faces_smpl)
om.write_mesh(opt.outf + "%04d_mesh_a.obj" % test_num, sa_mesh)
om.write_mesh(opt.outf + "%04d_mesh_v.obj" % test_num, deformed_mesh)
print("mesh saved to [%s]" + opt.outf + "%04d_mesh.obj" % test_num)
if opt.gif:
gb_src_img = src_img.copy() # green bounding source image
gb_src_img[:, :3] = gb_src_img[:, :3] / 2 + np.array([0, 128, 0])
gb_src_img[:3, :] = gb_src_img[:3, :] / 2 + np.array([0, 128, 0])
gb_src_img[-3:, :] = gb_src_img[-3:, :] / 2 + np.array([0, 128, 0])
gb_src_img[:, -3:] = gb_src_img[:, -3:] / 2 + np.array([0, 128, 0])
PIL.Image.fromarray(gb_src_img).save(opt.outf +
"%04d_src_gb.png" % test_num)
gif_name = opt.outf + "%04d.gif" % test_num
from vector import *
import openmesh as om
import numpy as np
# create mesh for bottom part
d1 = np.sqrt(0.5)
mesh = om.TriMesh()
# trigger part
make_block_triangle_mesh(mesh, [10 + d1, 5 * d1 + 6, 1], [5 - 2 * d1, 0, 0],
[0, -5 + 2 * d1, 0], [0, 0, 1])
make_block_mesh(mesh, [10 + d1, 15, 1], [0, -15 + 5 * d1 + 6, 0],
[5 - 2 * d1, 0, 0], [0, 0, 1])
make_block_mesh(mesh, [10 + d1, 5 * d1 + 6, 1], [-5, 0, 0], [0, -1.5, 0],
[0, 0, 1])
om.write_mesh("rubber_gun_trigger_part2.obj", mesh)
d2 = 0.5
for i in range(5):
mesh = om.TriMesh()
make_block_triangle_mesh(mesh, [10 + d1, 5 * d1 + 6 - i * d2, 1],
[5 - 2 * d1, 0, 0], [0, -5 + 2 * d1, 0],
[0, 0, 1])
make_block_mesh(mesh, [10 + d1, 15 - i * d2, 1], [0, -15 + 5 * d1 + 6, 0],
[5 - 2 * d1, 0, 0], [0, 0, 1])
make_block_mesh(mesh, [10 + d1, 5 * d1 + 6 - i * d2, 1], [-5, 0, 0],
[0, -1.5, 0], [0, 0, 1])
om.write_mesh("rubber_gun_trigger_part2_{0}.obj".format(i), mesh)
def test_all(opt, new_cage_shape):
opt.phase = "test"
opt.target_model = None
print(opt.model)
if opt.is_poly:
source_mesh = om.read_polymesh(opt.model)
else:
source_mesh = om.read_trimesh(opt.model)
dataset = build_dataset(opt)
dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False, drop_last=False,
collate_fn=tolerating_collate,
num_workers=0, worker_init_fn=lambda id: np.random.seed(np.random.get_state()[1][0] + id))
states = torch.load(opt.ckpt)
if "states" in states:
states = states["states"]
# states["template_vertices"] = new_cage_shape.transpose(1, 2)
# states["source_vertices"] = new_source.transpose(1,2)
# states["source_faces"] = new_source_face
# new_source_face = states["source_faces"]
om.write_mesh(os.path.join(opt.log_dir, opt.subdir,
"template-Sa.ply"), source_mesh)
net = networks.FixedSourceDeformer(opt, 3, opt.num_point, bottleneck_size=opt.bottleneck_size,
template_vertices=states["template_vertices"], template_faces=states["template_faces"].cuda(),
source_vertices=states["source_vertices"], source_faces=states["source_faces"]).cuda()
load_network(net, states)
source_points = torch.from_numpy(
source_mesh.points().copy()).float().cuda().unsqueeze(0)
with torch.no_grad():
# source_face = net.source_faces.detach()
for i, data in enumerate(dataloader):
data = dataset.uncollate(data)
target_shape, target_filename = data["target_shape"], data["target_file"]
logger.info("", data["target_file"][0])
sample_idx = None
if "sample_idx" in data:
sample_idx = data["sample_idx"]
outputs = net(target_shape.transpose(1, 2), cage_only=True)
if opt.d_residual:
cage_offset = outputs["new_cage"]-outputs["cage"]
outputs["cage"] = new_cage_shape
outputs["new_cage"] = new_cage_shape+cage_offset
deformed = deform_with_MVC(outputs["cage"], outputs["new_cage"], outputs["cage_face"].expand(
outputs["cage"].shape[0], -1, -1), source_points)
for b in range(deformed.shape[0]):
t_filename = os.path.splitext(target_filename[b])[0]
source_mesh_arr = source_mesh.points()
source_mesh_arr[:] = deformed[0].cpu().detach().numpy()
om.write_mesh(os.path.join(
opt.log_dir, opt.subdir, "template-{}-Sab.obj".format(t_filename)), source_mesh)
# if data["target_face"] is not None and data["target_mesh"] is not None:
# pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-{}-Sa.ply".format(t_filename)),
# source_mesh[0].detach().cpu(), source_face[b].detach().cpu())
pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-{}-Sb.ply".format(t_filename)),
data["target_mesh"][b].detach().cpu(), data["target_face"][b].detach().cpu())
# pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-{}-Sab.ply".format(t_filename)),
# deformed[b].detach().cpu(), source_face[b].detach().cpu())
# else:
# save_ply(source_mesh[0].detach().cpu(), os.path.join(opt.log_dir, opt.subdir,"template-{}-Sa.ply".format(t_filename)))
# save_ply(target_shape[b].detach().cpu(), os.path.join(opt.log_dir, opt.subdir,"template-{}-Sb.ply".format(t_filename)),
# normals=data["target_normals"][b].detach().cpu())
# save_ply(deformed[b].detach().cpu(), os.path.join(opt.log_dir, opt.subdir,"template-{}-Sab.ply".format(t_filename)),
# normals=data["target_normals"][b].detach().cpu())
pymesh.save_mesh_raw(
os.path.join(opt.log_dir, opt.subdir, "template-{}-cage1.ply".format(t_filename)),
outputs["cage"][b].detach().cpu(), outputs["cage_face"][b].detach().cpu(),
)
pymesh.save_mesh_raw(
os.path.join(opt.log_dir, opt.subdir, "template-{}-cage2.ply".format(t_filename)),
outputs["new_cage"][b].detach().cpu(), outputs["cage_face"][b].detach().cpu(),
)
# if opt.opt_lap and deformed.shape[1] == source_mesh.shape[1]:
# deformed = optimize_lap(opt, source_mesh, deformed, source_face)
# for b in range(deformed.shape[0]):
# pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-{}-Sab-optlap.ply".format(t_filename)),
# deformed[b].detach().cpu(), source_face[b].detach().cpu())
if i % 20 == 0:
logger.success("[{}/{}] Done".format(i, len(dataloader)))
dataset.render_result(os.path.join(opt.log_dir, opt.subdir))
assert opt.set in ["recon", "syn"], \
"set must be one of [recon, syn]"
data_num = int(opt.num)
output_dir = "./eval_data/%s_set/pred_save/" % opt.set
if not os.path.exists(output_dir):
os.makedirs(output_dir)
hmr_pred = hmr_predictor()
faces = np.load("../predef/smpl_faces.npy")
tr = trange(data_num, desc='Bar desc', leave=True)
for i in tr:
src_img = np.array(PIL.Image.open("./eval_data/%s_set/input_masked/%03d_img.png" % \
(opt.set, i)))[:,:,:3]
verts, cam, proc_para, std_img = hmr_pred.predict(src_img)
with open(output_dir + "pre_%03d.pkl" % i, 'wb') as fp:
pickle.dump(
{
"verts": verts,
"cam": cam,
"proc_para": proc_para,
"std_img": std_img,
}, fp)
mesh = make_trimesh(verts, faces)
om.write_mesh("./eval_data/%s_set/pred_save/hmr_%03d.obj" % (opt.set, i),
mesh)
def test_read_write_read(self):
mesh1 = openmesh.read_trimesh("TestFiles/cube-minimal.stl")
openmesh.write_mesh('OutFiles/test_read_write_read.stl', mesh1)
mesh2 = openmesh.read_trimesh('OutFiles/test_read_write_read.stl')
self.assertTrue(np.allclose(mesh1.points(), mesh2.points()))
self.assertTrue(np.array_equal(mesh1.face_vertex_indices(), mesh2.face_vertex_indices()))
import openmesh as om
import numpy as np
import cv2.cv2 as cv
mesh = om.TriMesh()
rgbImg = cv.imread('rgb.png')
dImg = cv.imread('d.png')
imgWidth = rgbImg.shape[0]
imgHeight = rgbImg.shape[1]
for i in range(0, imgWidth):
for j in range(0, imgHeight):
if dImg[i, j][0] > 0:
x = j
y = -i
z = dImg[i, j][0] * 2.3
vh = mesh.add_vertex([x, y, z])
g = rgbImg[i, j][0] / 255
b = rgbImg[i, j][1] / 255
r = rgbImg[i, j][2] / 255
mesh.set_color(vh, [r, g, b, 0])
om.write_mesh('PointCloud.ply', mesh, vertex_color=True)
faces = np.array([[0, 1, 2], [0, 2, 3], [0, 3, 4], [0, 4, 5], [0, 5, 6],
[0, 6, 1], [1, 2, 7], [2, 3, 7], [3, 4, 7], [4, 5, 7],
[5, 6, 7], [6, 1, 7]])
mesh = om.TriMesh()
vlist = []
for i in coords:
vlist.append(mesh.add_vertex(i))
flist = []
for i in faces:
flist.append(mesh.add_face(vlist[i[0]], vlist[i[1]], vlist[i[2]]))
om.write_mesh('../data/irreg.off', mesh)
def load():
return coords, faces
one_stride_s = mesh_traversal.traverse_mesh(coords, faces, 0, is_sparse=True)
two_stride_s = mesh_traversal.traverse_mesh(coords,
faces,
0,
2,
is_sparse=True)
three_stride_s = mesh_traversal.traverse_mesh(coords,
faces,
0,
n = [0, 0, 0, 0]
mesh.set_normal(vh0, n)
mesh.set_normal(vh1, n)
mesh.set_normal(vh2, n)
mesh.set_normal(vh3, n)
mesh.set_normal(vh4, n)
# add another face to the mesh, this time using a list
vh_list = [vh2, vh1, vh4]
fh3 = mesh.add_face(vh_list)
# 0 ==== 2
# |\ 0 /|
# | \ / |
# |2 1 3|
# | / \ |
# |/ 1 \|
# 3 ==== 4
# get the point with vertex handle vh0
point = mesh.point(vh0)
# get all points of the mesh
point_array = mesh.points()
# translate the mesh along the x-axis
# point_array += np.array([1, 0, 0])
# write and read meshes
om.write_mesh('cone.ply', mesh, vertex_normal=True, vertex_color=True)
from vector import *
import openmesh as om
import numpy as np
# create mesh for top part
d1 = np.sqrt(0.5)
mesh = om.TriMesh()
#make_block_mesh(mesh, [0, 0, 2], [5, 0, 0], [0, 5, 0], [0, 0, 1])
make_block_mesh(mesh, [5, 0, 2], [5, 0, 0], [0, 5, 0], [0, 0, 1])
make_block_mesh(mesh, [10, 0, 2], [5, 0, 0], [0, 20, 0], [0, 0, 1])
#make_block_mesh(mesh, [10, 20, 2], [5, 0, 0], [0, 5, 0], [0, 0, 1])
make_block_mesh(mesh, [14.5, 25, 2], [0.5, 0, 0], [0, 0.5, 0], [0, 0, 1])
make_block_mesh(mesh, [10, 25, 2], [4, 0, 0], [0, 0.5, 0], [0, 0, 1])
make_block_mesh(mesh, [15 - d1, 0, 2], [0.5 * d1, -0.5 * d1, 0],
[0.5 * d1, 0.5 * d1, 0], [0, 0, 1])
make_block_mesh(mesh, [15 - d1, 0, 2], [-0.5 * d1, 0.5 * d1, 0],
[-0.5 * d1, -0.5 * d1, 0], [0, 0, 1])
# make hole part
make_pipe_mesh(mesh, [2.5, 2.5, 2], [2.5, 2.5, 3],
p2=[1, 1, 0.0],
r1=d1,
r2=5 * d1,
n=4)
make_pipe_mesh(mesh, [12.5, 22.5, 2], [12.5, 22.5, 3],
p2=[22.5, 12.5, 0.0],
r1=d1,
r2=5 * d1,
n=4)
om.write_mesh("rubber_gun_top.obj", mesh)
from trianglulation import *
from vector import *
import numpy as np
import math
import openmesh as om
mesh = om.TriMesh()
make_funnel_mesh(mesh, [0, 0, 0], [0, 0, 3.8],
p2=[1.0, 0.0, 0.0],
z0=-0.5,
c1=1.0,
r1=15.0,
r2=0.1,
n=100,
m=50)
om.write_mesh("funnel_test1.obj", mesh)
file_gii = os.path.join(file_gii)
img = nib.load(file_gii)
img.print_summary()
# these are the spatial coordinates
data0 = img.darrays[0].data
# these are the mesh connections
data1 = img.darrays[1].data
mesh = om.TriMesh()
verts = []
for i in data0:
verts.append(mesh.add_vertex(i))
v = []
faces = []
for i in data1:
v.append(i[0])
v.append(i[1])
v.append(i[2])
faces.append(mesh.add_face(verts[i[0]], verts[i[1]], verts[i[2]]))
v = set(v)
print(len(verts))
pickle.dump(v, open("verts.pickle", "wb"))
om.write_mesh('example_mesh.off', mesh)
if not os.path.exists(opt.outf):
os.makedirs(opt.outf)
PIL.Image.fromarray(sr_proj_img).save(opt.outf + "%04d_ours_s.png" % test_num)
if opt.step:
PIL.Image.fromarray(src_img).save(opt.outf + "%04d_src.png" % test_num)
PIL.Image.fromarray(ja_proj_img).save(opt.outf +
"%04d_ours_j.png" % test_num)
PIL.Image.fromarray(sa_proj_img).save(opt.outf +
"%04d_ours_a.png" % test_num)
PIL.Image.fromarray(ori_proj_img).save(opt.outf +
"%04d_hmr.png" % test_num)
if opt.mesh:
import openmesh as om
om.write_mesh(opt.outf + "%04d_mesh.obj" % test_num, deformed_mesh)
print("mesh saved to [%s]" + opt.outf + "%04d_mesh.obj" % test_num)
if opt.gif:
gb_src_img = src_img.copy() # green bounding source image
gb_src_img[:, :3] = gb_src_img[:, :3] / 2 + np.array([0, 128, 0])
gb_src_img[:3, :] = gb_src_img[:3, :] / 2 + np.array([0, 128, 0])
gb_src_img[-3:, :] = gb_src_img[-3:, :] / 2 + np.array([0, 128, 0])
gb_src_img[:, -3:] = gb_src_img[:, -3:] / 2 + np.array([0, 128, 0])
PIL.Image.fromarray(gb_src_img).save(opt.outf +
"%04d_src_gb.png" % test_num)
gif_name = opt.outf + "%04d.gif" % test_num
file_list = [
opt.outf + "%04d_src_gb.png" % test_num,
opt.outf + "%04d_hmr.png" % test_num,
curve_mesh = EmbeddedCurveMesh(host_mesh)
for h in host_mesh.halfedges():
vf, vt = host_mesh.from_vertex_handle(h), host_mesh.to_vertex_handle(h)
vtt = host_mesh.to_vertex_handle(host_mesh.next_halfedge_handle(h))
if VL[vf.idx()] != VL[vt.idx()] != VL[vtt.idx()]:
curve_mesh.add_embedd_edge(h, 0.5,
host_mesh.next_halfedge_handle(h),
0.5).idx()
color_map = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1], [0.5, 0.5, 0]])
curve_mesh.request_vertex_colors()
curve_mesh.request_face_colors()
for i in range(len(V)):
curve_mesh.set_color(curve_mesh.vertex_handle(i),
np.append(color_map[VL[i], :], 1))
for f in curve_mesh.vf(curve_mesh.vertex_handle(i)):
curve_mesh.set_color(f, np.append(color_map[VL[i], :], 1))
for i in range(len(V), curve_mesh.n_vertices()):
curve_mesh.set_color(curve_mesh.vertex_handle(i), (1, 1, 1, 1))
om.write_mesh("1.off", curve_mesh, vertex_color=True, face_color=True)
for curve in curve_mesh.extract_em_curves():
curve_length_minimize(curve_mesh, curve, 0.35)
curvature_variation_minimize(curve_mesh, curve)
break
om.write_mesh("smoothed.off",
curve_mesh,
vertex_color=True,
face_color=True)
if opt.crop_y != -1:
if len(opt.crop_y) != 2:
print("ERROR: crop_y must be a list with 2 elements")
crop_img = crop_img[opt.crop_y[0]:-opt.crop_y[1], :]
if opt.pad>0:
crop_img = pad_arr(crop_img, 50)
std_img, proc_para = preproc_img(crop_img, img_size = 224,
margin = 30, normalize = True)
# initialize
hmr_pred = hmr_predictor()
renderer = SMPLRenderer()
faces = np.load("../predef/smpl_faces.npy")
# hmr predict
verts, cam, proc_para, std_img = hmr_pred.predict(std_img, normalize=False)
# build output folder if not exist
if not os.path.exists(opt.outf):
os.makedirs(opt.outf)
# write results
result_mesh = make_trimesh(verts, faces)
om.write_mesh(opt.outf + "hmr_mesh.obj", result_mesh)
final_img = ((std_img.copy()+1)*127).astype(np.uint8)
PIL.Image.fromarray(final_img).save(opt.outf + "std_img.jpg")
print("%s - finished, results are saved to [%s]" % (opt.img, opt.outf))
print("hmr done")
def optimize(opt):
"""
weights are the same with the original source mesh
target=net(old_source)
"""
# load new target
if opt.is_poly:
target_mesh = om.read_polymesh(opt.model)
else:
target_mesh = om.read_trimesh(opt.model)
target_shape_arr = target_mesh.points()
target_shape = target_shape_arr.copy()
target_shape = torch.from_numpy(
target_shape[:, :3].astype(np.float32)).cuda()
target_shape.unsqueeze_(0)
states = torch.load(opt.ckpt)
if "states" in states:
states = states["states"]
cage_v = states["template_vertices"].transpose(1, 2).cuda()
cage_f = states["template_faces"].cuda()
shape_v = states["source_vertices"].transpose(1, 2).cuda()
shape_f = states["source_faces"].cuda()
if os.path.isfile(opt.model.replace(os.path.splitext(opt.model)[1], ".picked")) and os.path.isfile(opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked")):
new_label_path = opt.model.replace(os.path.splitext(opt.model)[1], ".picked")
orig_label_path = opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked")
logger.info("Loading picked labels {} and {}".format(orig_label_path, new_label_path))
import pandas as pd
new_label = pd.read_csv(new_label_path, delimiter=" ",skiprows=1, header=None)
orig_label = pd.read_csv(orig_label_path, delimiter=" ",skiprows=1, header=None)
orig_label_name = orig_label.iloc[:,5]
new_label_name = new_label.iloc[:,5].tolist()
new_to_orig_idx = []
for i, name in enumerate(new_label_name):
matched_idx = orig_label_name[orig_label_name==name].index
if matched_idx.size == 1:
new_to_orig_idx.append((i, matched_idx[0]))
new_to_orig_idx = np.array(new_to_orig_idx)
if new_label.shape[1] == 10:
new_vidx = new_label.iloc[:,9].to_numpy()[new_to_orig_idx[:,0]]
target_points = target_shape[:, new_vidx, :]
else:
new_label_points = torch.from_numpy(new_label.iloc[:,6:9].to_numpy().astype(np.float32))
target_points = new_label_points.unsqueeze(0).cuda()
target_points, new_vidx, _ = faiss_knn(1, target_points, target_shape, NCHW=False)
target_points = target_points.squeeze(2) # B,N,3
new_label[9] = new_vidx.squeeze(0).squeeze(-1).cpu().numpy()
new_label.to_csv(new_label_path, sep=" ", header=[str(new_label.shape[0])]+[""]*(new_label.shape[1]-1), index=False)
target_points = target_points[:, new_to_orig_idx[:,0], :]
target_points = target_points.cuda()
source_shape, _ = read_trimesh(opt.source_model)
source_shape = torch.from_numpy(source_shape[None, :,:3]).float()
if orig_label.shape[1] == 10:
orig_vidx = orig_label.iloc[:,9].to_numpy()[new_to_orig_idx[:,1]]
source_points = source_shape[:, orig_vidx, :]
else:
orig_label_points = torch.from_numpy(orig_label.iloc[:,6:9].to_numpy().astype(np.float32))
source_points = orig_label_points.unsqueeze(0)
# find the closest point on the original meshes
source_points, new_vidx, _ = faiss_knn(1, source_points, source_shape, NCHW=False)
source_points = source_points.squeeze(2) # B,N,3
orig_label[9] = new_vidx.squeeze(0).squeeze(-1).cpu().numpy()
orig_label.to_csv(orig_label_path, sep=" ", header=[str(orig_label.shape[0])]+[""]*(orig_label.shape[1]-1), index=False)
source_points = source_points[:,new_to_orig_idx[:,1],:]
_, source_center, _ = center_bounding_box(source_shape[0])
source_points -= source_center
source_points = source_points.cuda()
# # shift target so that the belly match
# try:
# orig_bellyUp_idx = orig_label_name[orig_label_name=="bellUp"].index[0]
# orig_bellyUp = orig_label_points[orig_bellyUp_idx, :]
# new_bellyUp_idx = [i for i, i2 in new_to_orig_idx if i2==orig_bellyUp_idx][0]
# new_bellyUp = new_label_points[new_bellyUp_idx,:]
# target_points += (orig_bellyUp - new_bellyUp)
# except Exception as e:
# logger.warn("Couldn\'t match belly to belly")
# traceback.print_exc(file=sys.stdout)
# source_points[0] = center_bounding_box(source_points[0])[0]
elif not os.path.isfile(opt.model.replace(os.path.splitext(opt.model)[1], ".picked")) and os.path.isfile(opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked")):
logger.info("Assuming Faust model")
orig_label_path = opt.source_model.replace(os.path.splitext(opt.source_model)[1], ".picked")
logger.info("Loading picked labels {}".format(orig_label_path))
import pandas as pd
orig_label = pd.read_csv(orig_label_path, delimiter=" ",skiprows=1, header=None)
orig_label_name = orig_label.iloc[:,5]
source_shape, _ = read_trimesh(opt.source_model)
source_shape = torch.from_numpy(source_shape[None, :,:3]).cuda().float()
if orig_label.shape[1] == 10:
idx = torch.from_numpy(orig_label.iloc[:,9].to_numpy()).long()
source_points = source_shape[:,idx,:]
target_points = target_shape[:,idx,:]
else:
source_points = torch.from_numpy(orig_label.iloc[:,6:9].to_numpy().astype(np.float32))
source_points = source_points.unsqueeze(0).cuda()
# find the closest point on the original meshes
source_points, idx, _ = faiss_knn(1, source_points, source_shape, NCHW=False)
source_points = source_points.squeeze(2) # B,N,3
idx = idx.squeeze(-1)
target_points = target_shape[:,idx,:]
_, source_center, _ = center_bounding_box(source_shape[0])
source_points -= source_center
elif opt.corres_idx is None and target_shape.shape[1] == shape_v.shape[1]:
logger.info("No correspondence provided, assuming registered Faust models")
# corresp_idx = torch.randint(0, shape_f.shape[1], (100,)).cuda()
corresp_v = torch.unique(torch.randint(0, shape_v.shape[1], (4800,))).cuda()
target_points = torch.index_select(target_shape, 1, corresp_v)
source_points = torch.index_select(shape_v, 1, corresp_v)
target_shape[0], target_center, target_scale = center_bounding_box(target_shape[0])
_, _, source_scale = center_bounding_box(shape_v[0])
target_scale_factor = (source_scale/target_scale)[1]
target_shape *= target_scale_factor
target_points -= target_center
target_points = (target_points*target_scale_factor).detach()
# make sure test use the normalized
target_shape_arr[:] = target_shape[0].cpu().numpy()
om.write_mesh(os.path.join(opt.log_dir, opt.subdir, os.path.splitext(
os.path.basename(opt.model))[0]+"_normalized.obj"), target_mesh)
opt.model = os.path.join(opt.log_dir, opt.subdir, os.path.splitext(
os.path.basename(opt.model))[0]+"_normalized.obj")
pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "template-initial.obj"),
shape_v[0].cpu().numpy(), shape_f[0].cpu().numpy())
pymesh.save_mesh_raw(os.path.join(opt.log_dir, opt.subdir, "cage-initial.obj"),
cage_v[0].cpu().numpy(), cage_f[0].cpu().numpy())
save_ply(target_points[0].cpu().numpy(), os.path.join(
opt.log_dir, opt.subdir, "target_points.ply"))
save_ply(source_points[0].cpu().numpy(), os.path.join(
opt.log_dir, opt.subdir, "source_points.ply"))
logger.info("Optimizing for {} corresponding vertices".format(
target_points.shape[1]))
cage_init = cage_v.clone().detach()
lap_loss = MeshLaplacianLoss(torch.nn.MSELoss(reduction="none"), use_cot=True,
use_norm=True, consistent_topology=True, precompute_L=True)
mvc_reg_loss = MVCRegularizer(threshold=50, beta=1.0, alpha=0.0)
cage_v.requires_grad_(True)
optimizer = torch.optim.Adam([cage_v], lr=opt.lr, betas=(0.5, 0.9))
scheduler = torch.optim.lr_scheduler.StepLR(optimizer, int(opt.nepochs*0.4), gamma=0.5, last_epoch=-1)
if opt.dim == 3:
weights_ref = mean_value_coordinates_3D(
source_points, cage_init, cage_f, verbose=False)
else:
raise NotImplementedError
for t in range(opt.nepochs):
optimizer.zero_grad()
weights = mean_value_coordinates_3D(
target_points, cage_v, cage_f, verbose=False)
loss_mvc = torch.mean((weights-weights_ref)**2)
# reg = torch.sum((cage_init-cage_v)**2, dim=-1)*1e-4
reg = 0
if opt.clap_weight > 0:
reg = lap_loss(cage_init, cage_v, face=cage_f)*opt.clap_weight
reg = reg.mean()
if opt.mvc_weight > 0:
reg += mvc_reg_loss(weights)*opt.mvc_weight
# weight regularizer with the shape difference
# dist = torch.sum((source_points - target_points)**2, dim=-1)
# weights = torch.exp(-dist)
# reg = reg*weights*0.1
loss = loss_mvc + reg
if (t+1) % 50 == 0:
print("t {}/{} mvc_loss: {} reg: {}".format(t,
opt.nepochs, loss_mvc.item(), reg.item()))
if loss_mvc.item() < 5e-6:
break
loss.backward()
optimizer.step()
scheduler.step()
return cage_v, cage_f
fh57 = mesh.add_face(vh43, vh31, vh2)
fh58 = mesh.add_face(vh31, vh38, vh2)
fh59 = mesh.add_face(vh38, vh15, vh2)
fh60 = mesh.add_face(vh38, vh37, vh15)
fh61 = mesh.add_face(vh15, vh37, vh14)
fh62 = mesh.add_face(vh37, vh36, vh14)
fh63 = mesh.add_face(vh36, vh13, vh14)
fh64 = mesh.add_face(vh36, vh32, vh13)
fh65 = mesh.add_face(vh32, vh3, vh13)
# get all points of the mesh
point_array = mesh.points()
# write and read meshes
om.write_mesh('test.off', mesh)
mesh_2 = om.read_trimesh('test.off')
###### CALCULO DE CENTROIDES Y AREAS DE LAS CELDAS ######
#Recorrer todas las interfaces
contador = 0
for eh in mesh.edges():
eIdx = eh.idx() # devuelve el indice global del elemento
contador = contador + 1
print(contador)
# arreglo de baricentros
aCenterx = []
aCentery = []
# arreglo de Area
#===============================================================================
#
# This part should be in a function but it crashes duw to openmesh :/
#===============================================================================
mesh_om = om.PolyMesh()
Result=om.read_mesh(mesh_om, "meshdecimated.stl")
assert Result, "Open mesh could not read file"
deci_om=om.PolyMeshDecimater(mesh_om)
mh=om.PolyMeshModQuadricHandle()
deci_om.add(mh)
deci_om.initialize()
deci_om.decimate_to(nvertices)
mesh_om.garbage_collection()
assert mesh_om.n_vertices()==nvertices, 'vertices goal not acomplished; nvertices={0:d}'.format(mesh_om.n_vertices())
print "Decimation to {0} vertices Sucessful".format(nvertices)
om.write_mesh(mesh_om,'meshdecimated.stl')
################################################################################
meshvtktmp=LoadSTLMesh('meshdecimated.stl')
WriteVTKMesh(meshvtktmp,"mymesh.vtk")
meshvtk_dec=LoadVTKMesh('mymesh.vtk')
compute_info_mesh(meshvtk_dec)
norms=Compute_Normals(meshvtk_dec)
glyph = MakeGlyphs(norms)
Display_Normal_Mesh(meshvtk_dec,glyph,"arrows")
ax = np.int(np.round(achr_posi[j][0]))
if cim[ay, ax] == 0:
active_index[j] = 0
# anchor deform
fd_sa = fast_deform_dsa(weight=1.0)
sa_verts = fd_sa.deform(
np.asarray(ja_verts),
new_av,
active_index=active_index,
)
# visualize
if False:
ori_proj_img = renderer(verts=verts, img=src_img)
joint_move_img = draw_vert_move(ori_jv, new_jv, src_img)
achr_move_img = draw_vert_move(ori_av, new_av, src_img)
ja_proj_img = renderer(verts=ja_verts, img=src_img)
sa_proj_img = renderer(verts=sa_verts, img=src_img)
final_prv_img = np.concatenate(
(ori_proj_img, joint_move_img, ja_proj_img, achr_move_img,
sa_proj_img),
axis=1)
show_img_arr(final_prv_img.astype(np.uint8))
mesh_j = make_trimesh(ja_verts, faces)
om.write_mesh("./eval_data/%s_set/pred_save/j_%03d.obj" % \
(opt.set, test_ind), mesh_j)
mesh_a = make_trimesh(sa_verts, faces)
om.write_mesh("./eval_data/%s_set/pred_save/a_%03d.obj" % \
(opt.set, test_ind), mesh_a)
visi_vert_inds.append(fv[0])
visi_vert_inds.append(fv[1])
visi_vert_inds.append(fv[2])
visi_vert_inds = set(visi_vert_inds)
# filter out exempt version
visi_vert_inds = list(set(visi_vert_inds).difference(exempt_vert_list))
visi_vert_inds_m = []
for i in visi_vert_inds:
xy = cam_para.project(verts[i])
x = int(round(xy[1]))
y = int(round(xy[0]))
if x < 0 or y < 0 or x >= 448 or y >= 448:
continue
if np.absolute(proj_depth[x, y] - verts[i, 2]) < 0.01:
visi_vert_inds_m.append(i)
for i in visi_vert_inds_m:
xy = cam_para.project(verts[i])
x = int(round(xy[1]))
y = int(round(xy[0]))
depth = proj_depth[x, y] + pred_depth[x, y]
#print(depth, verts[i])
if depth > 8.:
continue
verts[i][2] = depth
deformed_mesh = make_trimesh(verts, faces)
om.write_mesh("./eval_data/%s_set/pred_save/s_%03d.obj" % \
(opt.set, test_num), deformed_mesh)
def write(self, fname):
openmesh.write_mesh(fname, self.mesh)
print("Wrote Mesh to", fname)
if p0[2] < box[4] and p1[2] < box[4]:
continue
if p0[0] > box[1] and p1[0] > box[1]:
continue
if p0[1] > box[3] and p1[1] > box[3]:
continue
if p0[2] > box[5] and p1[2] > box[5]:
continue
# both inside
if p0[0] > box[0] and p0[0] < box[1] and p0[1] > box[2] and p0[1] < box[3] and p0[2] > box[4] and p0[2] < box[5]:
if p1[0] > box[0] and p1[0] < box[1] and p1[1] > box[2] and p1[1] < box[3] and p1[2] > box[4] and p1[2] < box[5]:
make_mesh(mesh, p0, p1, p2=[1.0, 0.1, 1.0], r=frame_r*0.5, n=6)
continue
if False:
p0[0] = box[0] if p0[0] < box[0] else p0[0]
p0[0] = box[1] if p0[0] > box[1] else p0[0]
p0[1] = box[2] if p0[1] < box[2] else p0[1]
p0[1] = box[3] if p0[1] > box[3] else p0[1]
p0[2] = box[4] if p0[2] < box[4] else p0[2]
p0[2] = box[5] if p0[2] > box[5] else p0[2]
p1[0] = box[0] if p1[0] < box[0] else p1[0]
p1[0] = box[1] if p1[0] > box[1] else p1[0]
p1[1] = box[2] if p1[1] < box[2] else p1[1]
p1[1] = box[3] if p1[1] > box[3] else p1[1]
p1[2] = box[4] if p1[2] < box[4] else p1[2]
p1[2] = box[5] if p1[2] > box[5] else p1[2]
make_mesh(mesh, p0, p1, p2=[1.0, 0.1, 1.0], r=frame_r*0.5, n=6)
# output final buble box
om.write_mesh("bubble_cut3.obj", mesh)
def test_teapot():
# load teapot and sphere
reference = read_and_process_mesh(
"example_data/pointclouds/teapot_mesh.obj",
trans=ch.array([0, 0, 0]),
rotation=ch.array([np.pi, 0, 0]))
target = read_and_process_mesh(
"example_data/pointclouds/sphere_normal_2K_mesh.obj",
trans=ch.array([0, 0, 0]),
rotation=ch.array([0, 0, 0]))
# reference
V_ref = ch.array(reference.v)
vc_ref = ch.array(reference.vc)
A_ref = LambertianPointLight(v=V_ref, f=reference.f, num_verts=len(
V_ref), light_pos=ch.array([-1000, -1000, -1000]), vc=vc_ref,
light_color=ch.array([0.9, 0, 0])) +\
LambertianPointLight(v=V_ref, f=reference.f, num_verts=len(
V_ref), light_pos=ch.array([1000, -1000, -1000]), vc=vc_ref,
light_color=ch.array([0.0, 0.9, 0])) +\
LambertianPointLight(v=V_ref, f=reference.f, num_verts=len(
V_ref), light_pos=ch.array([-1000, 1000, -1000]), vc=vc_ref,
light_color=ch.array([0.0, 0.0, 0.9]))
U_ref = ProjectPoints(v=V_ref,
f=[w, w],
c=[w / 2., h / 2.],
k=ch.zeros(5),
t=ch.zeros(3),
rt=ch.zeros(3))
f_ref = ColoredRenderer(vc=A_ref,
camera=U_ref,
f=reference.f,
bgcolor=[1.0, 1.0, 1.0],
frustum={
'width': w,
'height': h,
'near': 1,
'far': 20
})
# target
V_tgt = ch.array(target.v)
vc_tgt = ch.array(target.vc)
A_tgt = LambertianPointLight(v=V_tgt, f=target.f, num_verts=len(
V_tgt), light_pos=ch.array([-1000, -1000, -1000]), vc=vc_tgt,
light_color=ch.array([0.9, 0, 0])) +\
LambertianPointLight(v=V_tgt, f=target.f, num_verts=len(
V_tgt), light_pos=ch.array([1000, -1000, -1000]), vc=vc_tgt,
light_color=ch.array([0.0, 0.9, 0])) +\
LambertianPointLight(v=V_tgt, f=target.f, num_verts=len(
V_tgt), light_pos=ch.array([-1000, 1000, -1000]), vc=vc_tgt,
light_color=ch.array([0.0, 0.0, 0.9]))
U_tgt = ProjectPoints(v=V_tgt,
f=[w, w],
c=[w / 2., h / 2.],
k=ch.zeros(5),
t=ch.zeros(3),
rt=ch.zeros(3))
f_tgt = ColoredRenderer(vc=A_tgt,
camera=U_tgt,
f=target.f,
bgcolor=[1.0, 1.0, 1.0],
frustum={
'width': w,
'height': h,
'near': 1,
'far': 20
})
# offset = ch.zeros(V_tgt.shape)
translation, rotation = ch.array([0, 0, 6]), ch.zeros(3)
f_tgt.v = translation + V_tgt.dot(Rodrigues(rotation))
f_ref.v = translation + V_ref.dot(Rodrigues(rotation))
op_mesh_target = om.read_trimesh(
"example_data/pointclouds/sphere_normal_2K_mesh.obj")
n_rotations = 144
# camera positions
for index in range(n_rotations):
rotation[:] = np.random.rand(3) * np.pi * 2
np.save(os.path.join(save_dir, "rot_v{:03d}".format(index)), rotation)
img_ref = f_ref.r
Image.fromarray((img_ref * 255).astype(np.uint8)).save(
os.path.join(save_dir, "reference_v{:03d}.png".format(index)))
img_tgt = f_tgt.r
Image.fromarray((img_tgt * 255).astype(np.uint8)).save(
os.path.join(save_dir, "target_v{:03d}.png".format(index)))
E_raw = f_tgt - img_ref
# E_pyr = gaussian_pyramid(E_raw, n_levels=6, normalization='size')
free_variables = [V_tgt]
# dogleg
# Newton-CG
# SLSQP
# BFGS
# trust-ncg
method = "trust-ncg"
maxiter = 30
ch.minimize({'pyr': E_raw},
x0=free_variables,
method=method,
options=dict(maxiter=30),
callback=create_callback(f_tgt, step=index * maxiter))
ch.minimize({'pyr': E_raw},
x0=free_variables,
method=method,
options=dict(maxiter=30),
callback=create_callback(f_tgt, step=index * maxiter))
# is not the same?
target.v = f_tgt.v.r.copy()
# save mesh
# mesh = pymesh.form_mesh(f_tgt.v.r, f_tgt.f)
# pymesh.save_mesh(os.path.join(
# save_dir, "target_v{:03d}.obj".format(index)), mesh)
point_array = op_mesh_target.points()
point_array[:] = target.v
np.copyto(op_mesh_target.points(), f_tgt.v.r)
om.write_mesh(
os.path.join(save_dir, "target_v{:03d}.obj".format(index)),
op_mesh_target)
def test_write_triangle_vertex_integer_color(self):
self.mesh.request_vertex_colors()
options = openmesh.Options()
options += openmesh.Options.VertexColor
options += openmesh.Options.ColorFloat
filename = "triangle-minimal-ColorsPerVertex.om"
# Generate data
v1 = self.mesh.add_vertex(openmesh.Vec3d(1.0, 0.0, 0.0))
v2 = self.mesh.add_vertex(openmesh.Vec3d(0.0, 1.0, 0.0))
v3 = self.mesh.add_vertex(openmesh.Vec3d(0.0, 0.0, 1.0))
self.mesh.add_face(v1, v2, v3)
c1 = openmesh.Vec4f(0.00, 0.00, 0.50, 1.00)
c2 = openmesh.Vec4f(0.25, 0.00, 0.00, 1.00)
c3 = openmesh.Vec4f(0.00, 0.75, 0.00, 1.00)
self.mesh.set_color(v1, c1)
self.mesh.set_color(v2, c2)
self.mesh.set_color(v3, c3)
# Save
ok = openmesh.write_mesh(self.mesh, filename, options)
self.assertTrue(ok)
self.mesh.release_vertex_colors()
# Load
cmpMesh = openmesh.TriMesh()
cmpMesh.request_vertex_colors()
ok = openmesh.read_mesh(cmpMesh, filename, options)
self.assertTrue(ok)
self.assertTrue(cmpMesh.has_vertex_colors())
# Compare
self.assertEqual(self.mesh.n_vertices(), 3)
self.assertEqual(self.mesh.n_edges(), 3)
self.assertEqual(self.mesh.n_faces(), 1)
self.assertEqual(cmpMesh.point(v1), openmesh.Vec3d(1.0, 0.0, 0.0))
self.assertEqual(cmpMesh.point(v2), openmesh.Vec3d(0.0, 1.0, 0.0))
self.assertEqual(cmpMesh.point(v3), openmesh.Vec3d(0.0, 0.0, 1.0))
self.assertAlmostEqual(cmpMesh.color(v1)[0], c1[0], 2)
self.assertAlmostEqual(cmpMesh.color(v1)[1], c1[1], 2)
self.assertAlmostEqual(cmpMesh.color(v1)[2], c1[2], 2)
self.assertAlmostEqual(cmpMesh.color(v1)[3], c1[3], 2)
self.assertAlmostEqual(cmpMesh.color(v2)[0], c2[0], 2)
self.assertAlmostEqual(cmpMesh.color(v2)[1], c2[1], 2)
self.assertAlmostEqual(cmpMesh.color(v2)[2], c2[2], 2)
self.assertAlmostEqual(cmpMesh.color(v2)[3], c2[3], 2)
self.assertAlmostEqual(cmpMesh.color(v3)[0], c3[0], 2)
self.assertAlmostEqual(cmpMesh.color(v3)[1], c3[1], 2)
self.assertAlmostEqual(cmpMesh.color(v3)[2], c3[2], 2)
self.assertAlmostEqual(cmpMesh.color(v3)[3], c3[3], 2)
# Clean up
cmpMesh.release_vertex_colors()
os.remove(filename)
def load(subdiv=2):
"""
generates an sphere mesh representing a smaller brain mesh, and embeds random patterns
drawn from a distribution, creating data for a basic discrimination task.
:param subdiv: # subdivisions for the recursive generation of mesh. More subdivisions lead to a more complex mesh.
:return: vertices, faces and adjacency matrix for the mesh.
"""
# -----------------------------------------------------------------------------
# Settings
scale = 1
# -----------------------------------------------------------------------------
# Functions
middle_point_cache = {}
def vertex(x, y, z):
""" Return vertex coordinates fixed to the unit sphere """
length = sqrt(x**2 + y**2 + z**2)
return [(i * scale) / length for i in (x, y, z)]
def middle_point(point_1, point_2):
""" Find a middle point and project to the unit sphere """
# We check if we have already cut this edge first
# to avoid duplicated verts
smaller_index = min(point_1, point_2)
greater_index = max(point_1, point_2)
key = '{0}-{1}'.format(smaller_index, greater_index)
if key in middle_point_cache:
return middle_point_cache[key]
# If it's not in cache, then we can cut it
vert_1 = verts[point_1]
vert_2 = verts[point_2]
middle = [sum(i) / 2 for i in zip(vert_1, vert_2)]
verts.append(vertex(*middle))
index = len(verts) - 1
middle_point_cache[key] = index
return index
# -----------------------------------------------------------------------------
# Make the base icosahedron
# Golden ratio
PHI = (1 + sqrt(5)) / 2
verts = [
vertex(-1, PHI, 0),
vertex(1, PHI, 0),
vertex(-1, -PHI, 0),
vertex(1, -PHI, 0),
vertex(0, -1, PHI),
vertex(0, 1, PHI),
vertex(0, -1, -PHI),
vertex(0, 1, -PHI),
vertex(PHI, 0, -1),
vertex(PHI, 0, 1),
vertex(-PHI, 0, -1),
vertex(-PHI, 0, 1),
]
faces = [
# 5 faces around point 0
[0, 11, 5],
[0, 5, 1],
[0, 1, 7],
[0, 7, 10],
[0, 10, 11],
# Adjacent faces
[1, 5, 9],
[5, 11, 4],
[11, 10, 2],
[10, 7, 6],
[7, 1, 8],
# 5 faces around 3
[3, 9, 4],
[3, 4, 2],
[3, 2, 6],
[3, 6, 8],
[3, 8, 9],
# Adjacent faces
[4, 9, 5],
[2, 4, 11],
[6, 2, 10],
[8, 6, 7],
[9, 8, 1],
]
# -----------------------------------------------------------------------------
# Subdivisions
for i in range(subdiv):
faces_subdiv = []
for tri in faces:
v1 = middle_point(tri[0], tri[1])
v2 = middle_point(tri[1], tri[2])
v3 = middle_point(tri[2], tri[0])
faces_subdiv.append([tri[0], v1, v3])
faces_subdiv.append([tri[1], v2, v1])
faces_subdiv.append([tri[2], v3, v2])
faces_subdiv.append([v1, v2, v3])
faces = faces_subdiv
mesh = om.TriMesh()
vlist = []
for i in verts:
vlist.append(mesh.add_vertex(i))
flist = []
for i in faces:
flist.append(mesh.add_face(vlist[i[0]], vlist[i[1]], vlist[i[2]]))
om.write_mesh('../data/small_sphere.off', mesh)
adj_mtx, _, _ = mesh_traversal.create_adj_mtx(np.array(verts),
np.array(faces),
is_sparse=True)
return verts, faces, adj_mtx
def write_off(self, mesh, path):
return openmesh.write_mesh(mesh, path)
def save_mesh(self, fp, x):
x = x * self.std + self.mean
om.write_mesh(fp, om.TriMesh(x.numpy(), self.template_face))
