I'm computing a constrained delaunay triangulation of an input UV parameterization, and I want to exactly maintain all input edges, so I passed them all through the segments parameter. Currently though, I found that the output will have edges flipped as compared to the input mesh, and if I do not pass segments at all the output is identical as when I specify segments to preserve.
I'm not sure if my use is wrong, but any help would be appreciated.
import argparse
import math
import trimesh
import torch
import numpy as np
import triangle
def arguments():
a = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
a.add_argument("-i", "--input", required=True, help="Input mesh")
a.add_argument("--iters", type=int, default=10000, help="Optimization iterations")
a.add_argument("--device", default="cpu", help="device to use")
return a.parse_args()
def main():
args = arguments()
device = args.device
print("Loading mesh")
mesh = trimesh.load_mesh(args.input, process=False)
uv = mesh.visual.uv
faces = torch.tensor(mesh.faces, device=device)
uniq_edges = []
tri_m = trimesh.Trimesh(
vertices=np.concatenate([uv, np.zeros_like(uv[:, :1])], axis=-1),
faces=mesh.faces,
)
tri_m.export("tmp_in.obj")
og_vi = {}
for vi, p in enumerate(uv.tolist()):
assert(tuple(p) not in og_vi)
og_vi[tuple(p)] = vi
og_edges = set()
for vis in mesh.faces:
assert(len(vis) == 3)
for i, v in enumerate(vis):
assert(v >= 0)
n = vis[(i+1)%3]
assert(n >= 0)
og_edges.add(tuple(sorted([int(v),int(n)])))
corners = [[0,1],[0,0],[1,1],[1,0]]
t = triangle.triangulate({
"vertices": uv.tolist() + corners,
"segments": list(og_edges),
})
new_uv = t["vertices"]
new_t = t["triangles"]
is_valid_face = [0] * len(new_t)
se = lambda i,j: (min(i, j), max(i,j))
for ti, vis in enumerate(new_t):
is_valid = True
for i, v in enumerate(vis):
vi = og_vi.get(tuple(new_uv[v]))
ni = og_vi.get(tuple(new_uv[vis[(i+1) % 3]]))
is_valid = is_valid and (vi is not None) and (ni is not None) and (se(vi, ni) in og_edges)
is_valid_face[ti] = is_valid
#new_t = [t for ti, t in enumerate(new_t) if is_valid_face[ti]]
tri_m = trimesh.Trimesh(
vertices=np.concatenate([new_uv, np.zeros_like(new_uv[:, :1])], axis=-1),
faces=new_t,
)
tri_m.export("tmp.obj")
exit()
if __name__ == "__main__": main()
I'm computing a constrained delaunay triangulation of an input UV parameterization, and I want to exactly maintain all input edges, so I passed them all through the
segmentsparameter. Currently though, I found that the output will have edges flipped as compared to the input mesh, and if I do not passsegmentsat all the output is identical as when I specify segments to preserve.Here is code to load and output meshes, and the data I'm loading with it:
I'm not sure if my use is wrong, but any help would be appreciated.
dense_cube copy.obj.txt