def compute_uvs(vertices, indices, print_progress = True):
"""
Args: vertices -- N x 3 float tensor
indices -- M x 3 int tensor
Return: uvs & uvs_indices
"""
vertices = vertices.cpu()
indices = indices.cpu()
uv_trimesh = redner.UVTriMesh(redner.float_ptr(vertices.data_ptr()),
redner.int_ptr(indices.data_ptr()),
redner.float_ptr(0),
redner.int_ptr(0),
int(vertices.shape[0]),
0,
int(indices.shape[0]))
atlas = redner.TextureAtlas()
num_uv_vertices = redner.automatic_uv_map([uv_trimesh], atlas, print_progress)[0]
uvs = torch.zeros(num_uv_vertices, 2, dtype=torch.float32)
uv_indices = torch.zeros_like(indices)
uv_trimesh.uvs = redner.float_ptr(uvs.data_ptr())
uv_trimesh.uv_indices = redner.int_ptr(uv_indices.data_ptr())
uv_trimesh.num_uv_vertices = num_uv_vertices
redner.copy_texture_atlas(atlas, [uv_trimesh])
if pyredner.get_use_gpu():
vertices = vertices.cuda(device = pyredner.get_device())
indices = indices.cuda(device = pyredner.get_device())
uvs = uvs.cuda(device = pyredner.get_device())
uv_indices = uv_indices.cuda(device = pyredner.get_device())
return uvs, uv_indices
def compute_uvs(vertices, indices, print_progress = True):
"""
Compute UV coordinates of a given mesh using a charting algorithm
with least square conformal mapping. This calls the `xatlas <https://github.com/jpcy/xatlas>`_ library.
Args
====
vertices: tf.Tensor
3D position of vertices
float32 tensor with size num_vertices x 3
indices: tf.Tensor
vertex indices of triangle faces.
int32 tensor with size num_triangles x 3
Returns
=======
tf.Tensor
uv vertices pool, float32 Tensor with size num_uv_vertices x 3
tf.Tensor
uv indices, int32 Tensor with size num_triangles x 3
"""
with tf.device('/device:cpu:' + str(pyredner.get_cpu_device_id())):
vertices = tf.identity(vertices)
indices = tf.identity(indices)
uv_trimesh = redner.UVTriMesh(redner.float_ptr(pyredner.data_ptr(vertices)),
redner.int_ptr(pyredner.data_ptr(indices)),
redner.float_ptr(0),
redner.int_ptr(0),
int(vertices.shape[0]),
0,
int(indices.shape[0]))
atlas = redner.TextureAtlas()
num_uv_vertices = redner.automatic_uv_map([uv_trimesh], atlas, print_progress)[0]
uvs = tf.zeros([num_uv_vertices, 2], dtype=tf.float32)
uv_indices = tf.zeros_like(indices)
uv_trimesh.uvs = redner.float_ptr(pyredner.data_ptr(uvs))
uv_trimesh.uv_indices = redner.int_ptr(pyredner.data_ptr(uv_indices))
uv_trimesh.num_uv_vertices = num_uv_vertices
redner.copy_texture_atlas(atlas, [uv_trimesh])
with tf.device(pyredner.get_device_name()):
vertices = tf.identity(vertices)
indices = tf.identity(indices)
uvs = tf.identity(uvs)
uv_indices = tf.identity(uv_indices)
return uvs, uv_indices
def compute_uvs(vertices, indices, print_progress=True):
"""
Compute UV coordinates of a given mesh using a charting algorithm
with least square conformal mapping. This calls the `xatlas <https://github.com/jpcy/xatlas>`_ library.
Args
====
vertices: torch.Tensor
3D position of vertices
float32 tensor with size num_vertices x 3
indices: torch.Tensor
vertex indices of triangle faces.
int32 tensor with size num_triangles x 3
Returns
=======
torch.Tensor
uv vertices pool, float32 Tensor with size num_uv_vertices x 3
torch.Tensor
uv indices, int32 Tensor with size num_triangles x 3
"""
device = vertices.device
vertices = vertices.cpu()
indices = indices.cpu()
uv_trimesh = redner.UVTriMesh(redner.float_ptr(vertices.data_ptr()),
redner.int_ptr(indices.data_ptr()),
redner.float_ptr(0), redner.int_ptr(0),
int(vertices.shape[0]), 0,
int(indices.shape[0]))
atlas = redner.TextureAtlas()
num_uv_vertices = redner.automatic_uv_map([uv_trimesh], atlas,
print_progress)[0]
uvs = torch.zeros(num_uv_vertices, 2, dtype=torch.float32)
uv_indices = torch.zeros_like(indices)
uv_trimesh.uvs = redner.float_ptr(uvs.data_ptr())
uv_trimesh.uv_indices = redner.int_ptr(uv_indices.data_ptr())
uv_trimesh.num_uv_vertices = num_uv_vertices
redner.copy_texture_atlas(atlas, [uv_trimesh])
vertices = vertices.to(device)
indices = indices.to(device)
uvs = uvs.to(device)
uv_indices = uv_indices.to(device)
return uvs, uv_indices
