pytorch3d.ops.sample_points_from_obj() 是一个新函数,允许用户使用新的自动采样功能从所有面上采样至少一个点,该功能确定要采样的点的数量。 尽管是一个新函数,sample_points_from_obj 重新封装了 pytorch3d.ops.sample_points_from_meshes() 中的现有 PyTorch3D 功能。 重要的是,sample_points_from_obj 中...
from pytorch3d.io import load_obj, save_obj from pytorch3d.structures import Meshes from pytorch3d.utils import ico_sphere from pytorch3d.ops import sample_points_from_meshes from pytorch3d.loss import ( chamfer_distance, mesh_edge_loss, mesh_normal_consistency, mesh_laplacian_smoothing ) import ...
Extendsample_points_from_meshesto support sampling textures |commit corresponding_cameras_alignmentfunction that estimates a similarity transformation between two sets of cameras |commit Support for variable size point radius in the pointcloud rasterizer |commit ...
2 # Sample points uniformly from the surface of the mesh. ---> 3 points = sample_points_from_meshes(mesh, 5000) 4 x, y, z = points.clone().detach().cpu().squeeze().unbind(1) 5 fig = plt.figure(figsize=(5, 5)) /.../pytorch3d/ops/sample_points_from_meshes.py in sample_p...
test_mesh = Meshes(verts=[verts], faces=[faces.verts_idx]) # 从网格表面采样点并计算 Chamfer 距离 sample_sphere = sample_points_from_meshes(sphere_mesh, 5000) sample_test = sample_points_from_meshes(test_mesh, 5000) loss_chamfer, _ = chamfer_distance(sample_sphere, sample_test) print("...
points = sample_points_from_meshes(mesh, 5000) x, y, z = points.clone().detach().cpu().squeeze().unbind(1) fig = plt.figure(figsize=(5, 5)) ax = Axes3D(fig) ax.scatter3D(x, z, -y) ax.set_xlabel('x') ax.set_ylabel('z') ax.set_zlabel('y') ax.set_title(title) ...
copying pytorch3d/ops/sample_points_from_meshes.py -> build/lib.linux-x86_64-3.6/pytorch3d/ops copying pytorch3d/ops/knn.py -> build/lib.linux-x86_64-3.6/pytorch3d/ops copying pytorch3d/ops/points_normals.py -> build/lib.linux-x86_64-3.6/pytorch3d/ops ...
sample_farthest_points.cu error: command 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\bin\nvcc.exe' failed with exit code 1 [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. ...
_losses=[]normal_losses=[]foriinrange(Niter):# Initialize optimizeroptimizer.zero_grad()# Deform the meshnew_src_mesh=src_mesh.offset_verts(deform_verts)# We sample 5k points from the surface of each meshsample_trg=sample_points_from_meshes(trg_mesh,5000)sample_src=sample_points_from...
from pytorch3d.io import load_obj File "C:\ProgramData\Anaconda3\envs\pytorch3d\lib\site-packages\pytorch3d\io_init_.py", line 8, in from .obj_io import load_obj, load_objs_as_meshes, save_obj File "C:\ProgramData\Anaconda3\envs\pytorch3d\lib\site-packages\pytorch3d\io\obj_io.py...