Summary:
Applies new import merging and sorting from µsort v1.0.
When merging imports, µsort will make a best-effort to move associated
comments to match merged elements, but there are known limitations due to
the diynamic nature of Python and developer tooling. These changes should
not produce any dangerous runtime changes, but may require touch-ups to
satisfy linters and other tooling.
Note that µsort uses case-insensitive, lexicographical sorting, which
results in a different ordering compared to isort. This provides a more
consistent sorting order, matching the case-insensitive order used when
sorting import statements by module name, and ensures that "frog", "FROG",
and "Frog" always sort next to each other.
For details on µsort's sorting and merging semantics, see the user guide:
https://usort.readthedocs.io/en/stable/guide.html#sorting
Reviewed By: lisroach
Differential Revision: D36402260
fbshipit-source-id: 7cb52f09b740ccc580e61e6d1787d27381a8ce00
Summary:
Applies the black-fbsource codemod with the new build of pyfmt.
paintitblack
Reviewed By: lisroach
Differential Revision: D36324783
fbshipit-source-id: 280c09e88257e5e569ab729691165d8dedd767bc
Summary:
Applies new import merging and sorting from µsort v1.0.
When merging imports, µsort will make a best-effort to move associated
comments to match merged elements, but there are known limitations due to
the diynamic nature of Python and developer tooling. These changes should
not produce any dangerous runtime changes, but may require touch-ups to
satisfy linters and other tooling.
Note that µsort uses case-insensitive, lexicographical sorting, which
results in a different ordering compared to isort. This provides a more
consistent sorting order, matching the case-insensitive order used when
sorting import statements by module name, and ensures that "frog", "FROG",
and "Frog" always sort next to each other.
For details on µsort's sorting and merging semantics, see the user guide:
https://usort.readthedocs.io/en/stable/guide.html#sorting
Reviewed By: bottler
Differential Revision: D35553814
fbshipit-source-id: be49bdb6a4c25264ff8d4db3a601f18736d17be1
Summary: D35513897 (4b94649f7b) was a pyre infer job which got some things wrong. Correct by adding the correct types, so these things shouldn't need worrying about again.
Reviewed By: patricklabatut
Differential Revision: D35546144
fbshipit-source-id: 89f6ea2b67be27aa0b0b14afff4347cccf23feb7
Summary: Add option to not rescale the features, giving more control. https://github.com/facebookresearch/pytorch3d/issues/1137
Reviewed By: nikhilaravi
Differential Revision: D35219577
fbshipit-source-id: cbbb643b91b71bc908cedc6dac0f63f6d1355c85
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:
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: Use the newer eigh to avoid deprecation warnings in newer pytorch.
Reviewed By: patricklabatut
Differential Revision: D34375784
fbshipit-source-id: 40efe0d33fdfa071fba80fc97ed008cbfd2ef249
Summary: D33970393 (e9fb6c27e3) ran an inference to add some typing. Remove some where it was a bit too confident. (Also fix some pyre errors in plotly_vis caused by new mismatch.)
Reviewed By: patricklabatut
Differential Revision: D34004689
fbshipit-source-id: 430182b0ff0b91be542a3120da6d6b1d2b247c59
Summary: Update all FB license strings to the new format.
Reviewed By: patricklabatut
Differential Revision: D33403538
fbshipit-source-id: 97a4596c5c888f3c54f44456dc07e718a387a02c
Summary:
A small numerical fix for IoU for 3D boxes, fixes GH #992
* Adds a check for boxes with zero side areas (invalid boxes)
* Fixes numerical issue when two boxes have coplanar sides
Reviewed By: nikhilaravi
Differential Revision: D33195691
fbshipit-source-id: 8a34b4d1f1e5ec2edb6d54143930da44bdde0906
Summary: Fix#873, that grid_sizes defaults to the wrong dtype in points2volumes code, and mask doesn't have a proper default.
Reviewed By: nikhilaravi
Differential Revision: D31503545
fbshipit-source-id: fa32a1a6074fc7ac7bdb362edfb5e5839866a472
Summary: Make eps=1e-4 by default for coplanar check and also enable it to be set by the user in call to `box3d_overlap`.
Reviewed By: gkioxari
Differential Revision: D31596836
fbshipit-source-id: b57fe603fd136cfa58fddf836922706d44fe894e
Summary: Single C++ function for the core of points2vols, not used anywhere yet. Added ability to control align_corners and the weight of each point, which may be useful later.
Reviewed By: nikhilaravi
Differential Revision: D29548607
fbshipit-source-id: a5cda7ec2c14836624e7dfe744c4bbb3f3d3dfe2
Summary: C++ Implementation of algorithm to compute 3D bounding boxes for batches of bboxes of shape (N, 8, 3) and (M, 8, 3).
Reviewed By: gkioxari
Differential Revision: D30905190
fbshipit-source-id: 02e2cf025cd4fa3ff706ce5cf9b82c0fb5443f96
Summary:
I have implemented an exact solution for 3D IoU of oriented 3D boxes.
This file includes:
* box3d_overlap: which computes the exact IoU of box1 and box2
* box3d_overlap_sampling: which computes an approximate IoU of box1 and box2 by sampling points within the boxes
Note that both implementations currently do not support batching.
Our exact IoU implementation is based on the fact that the intersecting shape of the two 3D boxes will be formed by segments of the surface of the boxes. Our algorithm computes these segments by reasoning whether triangles of one box are within the second box and vice versa. We deal with intersecting triangles by clipping them.
Reviewed By: gkioxari
Differential Revision: D30667497
fbshipit-source-id: 2f747f410f90b7f854eeaf3036794bc3ac982917
Summary:
CUDA implementation of farthest point sampling algorithm.
## Visual comparison
Compared to random sampling, farthest point sampling gives better coverage of the shape.
{F658631262}
## Reduction
Parallelized block reduction to find the max value at each iteration happens as follows:
1. First split the points into two equal sized parts (e.g. for a list with 8 values):
`[20, 27, 6, 8 | 11, 10, 2, 33]`
2. Use half of the thread (4 threads) to compare pairs of elements from each half (e.g elements [0, 4], [1, 5] etc) and store the result in the first half of the list:
`[20, 27, 6, 33 | 11, 10, 2, 33]`
Now we no longer care about the second part but again divide the first part into two
`[20, 27 | 6, 33| -, -, -, -]`
Now we can use 2 threads to compare the 4 elements
4. Finally we have gotten down to a single pair
`[20 | 33 | -, - | -, -, -, -]`
Use 1 thread to compare the remaining two elements
5. The max will now be at thread id = 0
`[33 | - | -, - | -, -, -, -]`
The reduction will give the farthest point for the selected batch index at this iteration.
Reviewed By: bottler, jcjohnson
Differential Revision: D30401803
fbshipit-source-id: 525bd5ae27c4b13b501812cfe62306bb003827d2
Summary:
This is a naive python implementation of the iterative farthest point sampling algorithm along with associated simple tests. The C++/CUDA implementations will follow in subsequent diffs.
The algorithm is used to subsample a pointcloud with better coverage of the space of the pointcloud.
The function has not been added to `__init__.py`. I will add this after the full C++/CUDA implementations.
Reviewed By: jcjohnson
Differential Revision: D30285716
fbshipit-source-id: 33f4181041fc652776406bcfd67800a6f0c3dd58
Summary: New test that each subpackage of pytorch3d imports cleanly.
Reviewed By: patricklabatut
Differential Revision: D30001632
fbshipit-source-id: ca8dcac94491fc22f33602b3bbef481cba927094
Summary: Small fix for omitting this argument.
Reviewed By: nikhilaravi
Differential Revision: D29548610
fbshipit-source-id: f25032fab3faa2f09006f5fcf8628138555f2f20
Summary: Fixes to a couple of comments on points to volumes, make the mask work in round_points_to_volumes, and remove a duplicate rand calculation
Reviewed By: nikhilaravi
Differential Revision: D29522845
fbshipit-source-id: 86770ba37ef3942b909baf63fd73eed1399635b6
Summary:
Implementation of ball query from PointNet++. This function is similar to KNN (find the neighbors in p2 for all points in p1). These are the key differences:
- It will return the **first** K neighbors within a specified radius as opposed to the **closest** K neighbors.
- As all the points in p2 do not need to be considered to find the closest K, the algorithm is much faster than KNN when p2 has a large number of points.
- The neighbors are not sorted
- Due to the radius threshold it is not guaranteed that there will be K neighbors even if there are more than K points in p2.
- The padding value for `idx` is -1 instead of 0.
# Note:
- Some of the code is very similar to KNN so it could be possible to modify the KNN forward kernels to support ball query.
- Some users might want to use kNN with ball query - for this we could provide a wrapper function around the current `knn_points` which enables applying the radius threshold afterwards as an alternative. This could be called `ball_query_knn`.
Reviewed By: jcjohnson
Differential Revision: D30261362
fbshipit-source-id: 66b6a7e0114beff7164daf7eba21546ff41ec450
Summary: Annotate the (return type of the) following dunder functions across the codebase: `__init__()`, `__len__()`, `__getitem__()`
Reviewed By: nikhilaravi
Differential Revision: D29001801
fbshipit-source-id: 928d9e1c417ffe01ab8c0445311287786e997c7c
Summary:
Refactor of all functions to compute laplacian matrices in one file.
Support for:
* Standard Laplacian
* Cotangent Laplacian
* Norm Laplacian
Reviewed By: nikhilaravi
Differential Revision: D29297466
fbshipit-source-id: b96b88915ce8ef0c2f5693ec9b179fd27b70abf9
Summary:
Get rid of pyre fixmes related to importing a native module:
- add stub file for the `_C` native extension to the internal typeshed
- add initial annotations to the new stub file
- remove the now unnecessary pyre ignores
Reviewed By: nikhilaravi
Differential Revision: D28929467
fbshipit-source-id: 6525e15c8f27215a3ff6f78392925fd0ed6ec2ac
Summary: Increase code coverage of subdivide_meshes and re-include it in code coverage test
Reviewed By: bottler
Differential Revision: D29097476
fbshipit-source-id: 3403ae38a90c4b53f24188eed11faae202a235b5
Summary: Omit specific code from code coverage computation. This is done to make code coverage test pass again. Test coverage for shader.py and subdivide_meshes.py will be increased in later diffs to re-include them.
Reviewed By: bottler
Differential Revision: D29061105
fbshipit-source-id: addac35a216c96de9f559e2d8fe42496adc85791
