Summary: In order to simplify the interface, we disallow passing None as vertex/face lists to textures.submeshes. This function would only ever get called from within meshes.submeshes where we can provide both arguments, even if they're not necessary for a specific submesh type.
Reviewed By: bottler
Differential Revision: D35581161
fbshipit-source-id: aeab99308a319b144e141ca85ca7515f855116da
Summary:
Copypasting the docstring:
```
Split a mesh into submeshes, defined by face indices of the original Meshes object.
Args:
face_indices:
Let the original mesh have verts_list() of length N.
Can be either
- List of length N. The n-th element is a list of length num_submeshes_n
(empty lists are allowed). Each element of the n-th sublist is a LongTensor
of length num_faces.
- List of length N. The n-th element is a possibly empty padded LongTensor of
shape (num_submeshes_n, max_num_faces).
Returns:
Meshes object with selected submeshes. The submesh tensors are cloned.
Currently submeshing only works with no textures or with the TexturesVertex texture.
Example:
Take a Meshes object `cubes` with 4 meshes, each a translated cube. Then:
* len(cubes) is 4, len(cubes.verts_list()) is 4, len(cubes.faces_list()) is 4,
* [cube_verts.size for cube_verts in cubes.verts_list()] is [8, 8, 8, 8],
* [cube_faces.size for cube_faces in cubes.faces_list()] if [6, 6, 6, 6],
Now let front_facet, top_and_bottom, all_facets be LongTensors of
sizes (2), (4), and (12), each picking up a number of facets of a cube by specifying
the appropriate triangular faces.
Then let `subcubes = cubes.submeshes([[front_facet, top_and_bottom], [], [all_facets], []])`.
* len(subcubes) is 3.
* subcubes[0] is the front facet of the cube contained in cubes[0].
* subcubes[1] is a mesh containing the (disconnected) top and bottom facets of cubes[0].
* subcubes[2] is a clone of cubes[2].
* There are no submeshes of cubes[1] and cubes[3] in subcubes.
* subcubes[0] and subcubes[1] are not watertight. subcubes[2] is.
```
Reviewed By: bottler
Differential Revision: D35440657
fbshipit-source-id: 8a6d2d300ce226b5b9eb440688528b5e795195a1
Summary:
Sort a mesh's vertices in alphabetical order, and resort the face coords accordingly. Textured meshes are not supported yet, but will be added down the stack.
This, togehter with mesh equality, can be used to compare two meshes in a way invariant to vertex permutations, as shown in the unit tests.
We do not want the submeshing mechanism to guarantee any particular vertex order, leaving that up to the implementation, so we need this function for testing.
Reviewed By: bottler
Differential Revision: D35440656
fbshipit-source-id: 5a4dd921fdb00625a33da08b5fea79e20ac6402c
Summary: Adding a mesh equality operator. Two Meshes objects m1, m2 are equal iff their vertex lists, face lists, and normals lists are equal. Textures meshes are not supported yet, but will be added for vertex textures down the stack.
Reviewed By: bottler, nikhilaravi
Differential Revision: D35440655
fbshipit-source-id: 69974a59c091416afdb2892896859a189f5ebf3a
Summary:
The default behavior of Meshes (with verts=None, faces=None) throws an exception:
```
meshes = Meshes()
> ValueError: Verts and Faces must be either a list or a tensor with shape (batch_size, N, 3) where N is either the maximum number of verts or faces respectively.
```
Instead, let's default to an empty mesh, following e.g. PyTorch:
```
empty_tensor = torch.FloatTensor()
> torch.tensor([])
```
this change is backwards-compatible (you can still init with verts=[], faces=[]).
Reviewed By: bottler, nikhilaravi
Differential Revision: D35443453
fbshipit-source-id: d638a8fef49a089bf0da6dd2201727b94ceb21ec
Summary:
Added L1 norm for KNN and chamfer op
* The norm is now specified with a variable `norm` which can only be 1 or 2
Reviewed By: bottler
Differential Revision: D35419637
fbshipit-source-id: 77813fec650b30c28342af90d5ed02c89133e136
Summary: A new type of auto-expanded member of a Configurable: something of type Optional[X] where X is a Configurable. This works like X but its construction is controlled by a boolean membername_enabled.
Reviewed By: davnov134
Differential Revision: D35368269
fbshipit-source-id: 7e0c8a3e8c4930b0aa942fa1b325ce65336ebd5f
Summary:
Try again to solve https://github.com/facebookresearch/pytorch3d/issues/1144 pickling problem.
D35258561 (24260130ce) didn't work.
When writing a function or vanilla class C which you want people to be able to call get_default_args on, you must add the line enable_get_default_args(C) to it. This causes autogeneration of a hidden dataclass in the module.
Reviewed By: davnov134
Differential Revision: D35364410
fbshipit-source-id: 53f6e6fff43e7142ae18ca3b06de7d0c849ef965
Summary:
Error Reproduction:
python=3.8.12
pytorch=1.9.1
pytorch3d=0.6.1
cudatoolkit=11.1.74
test.py:
```python
import torch
from pytorch3d.ops import cubify
voxels = torch.Tensor([[[[0,1], [0,0]], [[0,1], [0,0]]]]).float()
meshes = cubify(voxels, 0.5, device="cpu")
```
The error appears when `device="cpu"` and `pytorch=1.9.1` (works fine with pytorch=1.10.2)
Error message:
```console
/home/kyle/anaconda3/envs/adapt-net/lib/python3.8/site-packages/torch/_tensor.py:575: UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values.
To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at /opt/conda/conda-bld/pytorch_1631630839582/work/aten/src/ATen/native/BinaryOps.cpp:467.)
return torch.floor_divide(self, other)
Traceback (most recent call last):
File "test.py", line 5, in <module>
meshes = cubify(voxels, 0.5, device="cpu")
File "/home/kyle/anaconda3/envs/adapt-net/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "/home/kyle/Desktop/pytorch3d/pytorch3d/ops/cubify.py", line 227, in cubify
idleverts.scatter_(0, grid_faces.flatten(), 0)
RuntimeError: Expected index [60] to be smaller than self [27] apart from dimension 0 and to be smaller size than src [27]
```
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1067
Reviewed By: nikhilaravi
Differential Revision: D34893567
Pulled By: bottler
fbshipit-source-id: aa95980f7319302044141f7821ef48129cfa37a6
Summary: This is required to suppress a huge stdout full of warnings about overflown bins.
Reviewed By: bottler
Differential Revision: D35359824
fbshipit-source-id: 39214b1bdcb4a5d5debf8ed498b2ca81fa43d210
Summary: Aid reflection by adding the original declared types of replaced members of a configurable as values in _processed_members.
Reviewed By: davnov134
Differential Revision: D35358422
fbshipit-source-id: 80ef3266144c51c1c2105f349e0dd3464e230429
Summary: Use logging instead of printing in the internals of implicitron.
Reviewed By: davnov134
Differential Revision: D35247581
fbshipit-source-id: be5ddad5efe1409adbae0575d35ade6112b3be63
Summary: This might make the implicitron tests work better on RE.
Reviewed By: davnov134
Differential Revision: D35283131
fbshipit-source-id: 4dda9684f632ab6e9cebcbf1e6e4a8243ec00c85
Summary:
ListConfig and DictConfig members of get_default_args(X) when X is a callable will contain references to a temporary dataclass and therefore be unpicklable. Avoid this in a few cases.
Fixes https://github.com/facebookresearch/pytorch3d/issues/1144
Reviewed By: shapovalov
Differential Revision: D35258561
fbshipit-source-id: e52186825f52accee9a899e466967a4ff71b3d25
Summary:
Previously, dtypes were not propagated correctly in composed transforms, resulting in errors when different dtypes were mixed. Even specifying a dtype in the constructor does not fix this. Neither does specifying the dtype for each composition function invocation (e.g. as a `kwarg` in `rotate_axis_angle`).
With the change, I also had to modify the default dtype of `RotateAxisAngle`, which was `torch.float64`; it is now `torch.float32` like for all other transforms. This was required because the fix in propagation broke some tests due to dtype mismatches.
This change in default dtype in turn broke two tests due to precision changes (calculations that were previously done in `torch.float64` were now done in `torch.float32`), so I changed the precision tolerances to be less strict. I chose the lowest power of ten that passed the tests here.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1141
Reviewed By: patricklabatut
Differential Revision: D35192970
Pulled By: bottler
fbshipit-source-id: ba0293e8b3595dfc94b3cf8048e50b7a5e5ed7cf
Summary: Allow things like `renderer:Optional[BaseRenderer]` in configurables.
Reviewed By: davnov134
Differential Revision: D35118339
fbshipit-source-id: 1219321b2817ed4b26fe924c6d6f73887095c985
Summary: To ensure that tests outside implicitron/ don't use implicitron, split the test for recursive includes in to two. License header checking is not needed here any more.
Reviewed By: shapovalov
Differential Revision: D35077830
fbshipit-source-id: 2ebe7436a6dcc5d21a116434f6ddd08705dfab34
Summary:
Before the fix, running get_default_args(C: Callable) returns an unstructured DictConfig which causes Enums to be handled incorrectly. This is a fix.
WIP update: Currently tests still fail whenever a function signature contains an untyped argument: This needs to be somehow fixed.
Reviewed By: bottler
Differential Revision: D34932124
fbshipit-source-id: ecdc45c738633cfea5caa7480ba4f790ece931e8
Summary: bin_size should be 0 not -1 for naive rasterization. See https://github.com/facebookresearch/pytorch3d/issues/1129
Reviewed By: patricklabatut
Differential Revision: D35077115
fbshipit-source-id: b81ff74f47c78429977802f7dcadfd1b96676f8c
Summary: Attempt to reduce nvcc trouble on windows by (1) avoiding flag for c++14 and (2) avoiding `torch/extension.h`, which introduces pybind11, in `.cu` files.
Reviewed By: patricklabatut
Differential Revision: D34969868
fbshipit-source-id: f3878d6a2ba9d644e87ae7b6377cb5008b4b6ce3
Summary: Using the API from D35012121 everywhere.
Reviewed By: bottler
Differential Revision: D35045870
fbshipit-source-id: dab112b5e04160334859bbe8fa2366344b6e0f70
Summary: We often want to iterate over frames in the sequence in temporal order. This diff provides the API to do that. `seq_to_idx` should probably be considered to have `protected` visibility.
Reviewed By: davnov134
Differential Revision: D35012121
fbshipit-source-id: 41896672ec35cd62f3ed4be3aa119efd33adada1
Summary:
Fixes required for MC rasterisation to work.
1) Wrong number of channels for background was used (derived from points dimensions, not features dimensions;
2) split of the results on the wrong dimension was done;
3) CORE CHANGE: blending in alpha compositor was assuming RGBA input.
Reviewed By: davnov134
Differential Revision: D34933673
fbshipit-source-id: a5cc9f201ea21e114639ab9e291a10888d495206
Summary: Fix assumption that face indices are signed in the PLY file, as reported in #1104.
Reviewed By: nikhilaravi
Differential Revision: D34892598
fbshipit-source-id: a8b23bfac1357bdc11bbbf752098319142239804
Summary: As noticed in https://github.com/facebookresearch/pytorch3d/issues/1098 , it would be useful to make this more available.
Reviewed By: nikhilaravi
Differential Revision: D34752526
fbshipit-source-id: 5a127bd557a0cd626f36bf194f22bc0a0a6a2436
Summary: As reported in https://github.com/facebookresearch/pytorch3d/pull/1100, a rasterizer couldn't be moved if it was missing the optional cameras member. Fix that. This matters because the renderer.to calls rasterizer.to, so this to() could be called even by a user who never sets a cameras member.
Reviewed By: nikhilaravi
Differential Revision: D34643841
fbshipit-source-id: 7e26e32e8bc585eb1ee533052754a7b59bc7467a
Summary: As reported in https://github.com/facebookresearch/pytorch3d/pull/1100, _num_faces_per_mesh was changing in the source mesh in join_batch. This affects both TexturesUV and TexturesAtlas
Reviewed By: nikhilaravi
Differential Revision: D34643675
fbshipit-source-id: d67bdaca7278f18a76cfb15ba59d0ea85575bd36
Summary: A scalar background color is not meant to be allowed for the point renderer. It used to be ignored with a warning, but a recent code change made it an error. It was being used, at least in the black (value=0.0) case. Re-enable it.
Reviewed By: nikhilaravi
Differential Revision: D34519651
fbshipit-source-id: d37dcf145bb7b8999c9265cf8fc39b084059dd18
Summary:
1. changed IsInsideTriangle in geometry_utils to take in min_triangle_area parameter instead of hardcoded value
2. updated point_mesh_cpu.cpp and point_mesh_cuda.[h/cu] to adapt to changes in geometry_utils function signatures
3. updated point_mesh_distance.py and test_point_mesh_distance.py to modify _C. calls
Reviewed By: bottler
Differential Revision: D34459764
fbshipit-source-id: 0549e78713c6d68f03d85fb597a13dd88e09b686
