407 Commits

Author SHA1 Message Date
David Novotny
e5b1d6d3a3 Umeyama
Summary:
Umeyama estimates a rigid motion between two sets of corresponding points.

Benchmark output for `bm_points_alignment`

```
Arguments key: [<allow_reflection>_<batch_size>_<dim>_<estimate_scale>_<n_points>_<use_pointclouds>]
Benchmark                                                        Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
CorrespodingPointsAlignment_True_1_3_True_100_False                   7382            9833             68
CorrespodingPointsAlignment_True_1_3_True_10000_False                 8183           10500             62
CorrespodingPointsAlignment_True_1_3_False_100_False                  7301            9263             69
CorrespodingPointsAlignment_True_1_3_False_10000_False                7945            9746             64
CorrespodingPointsAlignment_True_1_20_True_100_False                 13706           41623             37
CorrespodingPointsAlignment_True_1_20_True_10000_False               11044           33766             46
CorrespodingPointsAlignment_True_1_20_False_100_False                 9908           28791             51
CorrespodingPointsAlignment_True_1_20_False_10000_False               9523           18680             53
CorrespodingPointsAlignment_True_10_3_True_100_False                 29585           32026             17
CorrespodingPointsAlignment_True_10_3_True_10000_False               29626           36324             18
CorrespodingPointsAlignment_True_10_3_False_100_False                26013           29253             20
CorrespodingPointsAlignment_True_10_3_False_10000_False              25000           33820             20
CorrespodingPointsAlignment_True_10_20_True_100_False                40955           41592             13
CorrespodingPointsAlignment_True_10_20_True_10000_False              42087           42393             12
CorrespodingPointsAlignment_True_10_20_False_100_False               39863           40381             13
CorrespodingPointsAlignment_True_10_20_False_10000_False             40813           41699             13
CorrespodingPointsAlignment_True_100_3_True_100_False               183146          194745              3
CorrespodingPointsAlignment_True_100_3_True_10000_False             213789          231466              3
CorrespodingPointsAlignment_True_100_3_False_100_False              177805          180796              3
CorrespodingPointsAlignment_True_100_3_False_10000_False            184963          185695              3
CorrespodingPointsAlignment_True_100_20_True_100_False              347181          347325              2
CorrespodingPointsAlignment_True_100_20_True_10000_False            363259          363613              2
CorrespodingPointsAlignment_True_100_20_False_100_False             351769          352496              2
CorrespodingPointsAlignment_True_100_20_False_10000_False           375629          379818              2
CorrespodingPointsAlignment_False_1_3_True_100_False                 11155           13770             45
CorrespodingPointsAlignment_False_1_3_True_10000_False               10743           13938             47
CorrespodingPointsAlignment_False_1_3_False_100_False                 9578           11511             53
CorrespodingPointsAlignment_False_1_3_False_10000_False               9549           11984             53
CorrespodingPointsAlignment_False_1_20_True_100_False                13809           14183             37
CorrespodingPointsAlignment_False_1_20_True_10000_False              14084           15082             36
CorrespodingPointsAlignment_False_1_20_False_100_False               12765           14177             40
CorrespodingPointsAlignment_False_1_20_False_10000_False             12811           13096             40
CorrespodingPointsAlignment_False_10_3_True_100_False                28823           39384             18
CorrespodingPointsAlignment_False_10_3_True_10000_False              27135           27525             19
CorrespodingPointsAlignment_False_10_3_False_100_False               26236           28980             20
CorrespodingPointsAlignment_False_10_3_False_10000_False             42324           45123             12
CorrespodingPointsAlignment_False_10_20_True_100_False              723902          723902              1
CorrespodingPointsAlignment_False_10_20_True_10000_False            220007          252886              3
CorrespodingPointsAlignment_False_10_20_False_100_False              55593           71636              9
CorrespodingPointsAlignment_False_10_20_False_10000_False            44419           71861             12
CorrespodingPointsAlignment_False_100_3_True_100_False              184768          185199              3
CorrespodingPointsAlignment_False_100_3_True_10000_False            198657          213868              3
CorrespodingPointsAlignment_False_100_3_False_100_False             224598          309645              3
CorrespodingPointsAlignment_False_100_3_False_10000_False           197863          202002              3
CorrespodingPointsAlignment_False_100_20_True_100_False             293484          309459              2
CorrespodingPointsAlignment_False_100_20_True_10000_False           327253          366644              2
CorrespodingPointsAlignment_False_100_20_False_100_False            420793          422194              2
CorrespodingPointsAlignment_False_100_20_False_10000_False          462634          485542              2
CorrespodingPointsAlignment_True_1_3_True_100_True                    7664            9909             66
CorrespodingPointsAlignment_True_1_3_True_10000_True                  7190            8366             70
CorrespodingPointsAlignment_True_1_3_False_100_True                   6549            8316             77
CorrespodingPointsAlignment_True_1_3_False_10000_True                 6534            7710             77
CorrespodingPointsAlignment_True_10_3_True_100_True                  29052           32940             18
CorrespodingPointsAlignment_True_10_3_True_10000_True                30526           33453             17
CorrespodingPointsAlignment_True_10_3_False_100_True                 28708           32993             18
CorrespodingPointsAlignment_True_10_3_False_10000_True               30630           35973             17
CorrespodingPointsAlignment_True_100_3_True_100_True                264909          320820              3
CorrespodingPointsAlignment_True_100_3_True_10000_True              310902          322604              2
CorrespodingPointsAlignment_True_100_3_False_100_True               246832          250634              3
CorrespodingPointsAlignment_True_100_3_False_10000_True             276006          289061              2
CorrespodingPointsAlignment_False_1_3_True_100_True                  11421           13757             44
CorrespodingPointsAlignment_False_1_3_True_10000_True                11199           12532             45
CorrespodingPointsAlignment_False_1_3_False_100_True                 11474           15841             44
CorrespodingPointsAlignment_False_1_3_False_10000_True               10384           13188             49
CorrespodingPointsAlignment_False_10_3_True_100_True                 36599           47340             14
CorrespodingPointsAlignment_False_10_3_True_10000_True               40702           50754             13
CorrespodingPointsAlignment_False_10_3_False_100_True                41277           52149             13
CorrespodingPointsAlignment_False_10_3_False_10000_True              34286           37091             15
CorrespodingPointsAlignment_False_100_3_True_100_True               254991          258578              2
CorrespodingPointsAlignment_False_100_3_True_10000_True             257999          261285              2
CorrespodingPointsAlignment_False_100_3_False_100_True              247511          248693              3
CorrespodingPointsAlignment_False_100_3_False_10000_True            251807          263865              3
```

Reviewed By: gkioxari

Differential Revision: D19808389

fbshipit-source-id: 83305a58627d2fc5dcaf3c3015132d8148f28c29
2020-04-02 14:46:51 -07:00
Patrick Labatut
745aaf3915 No side effect with invalid inputs to save_obj / save_ply
Summary: Do not create output files with invalid inputs to `save_{obj,ply}()`.

Reviewed By: bottler

Differential Revision: D20720282

fbshipit-source-id: 3b611a10da6f6eecacab2a1900bf16f89e2000aa
2020-04-01 11:45:12 -07:00
Patrick Labatut
83feed56a0 Fix saving / loading empty PLY meshes
Summary:
Similar to D20392526, PLY files without vertices or faces should be allowed:
- a PLY with only vertices can represent a point cloud
- a PLY without any vertex or face is just empty
- a PLY with faces referencing inexistent vertices has invalid data

Reviewed By: gkioxari

Differential Revision: D20400330

fbshipit-source-id: 35a5f072603fd221f382c7faad5f37c3e0b49bb1
2020-04-01 04:51:20 -07:00
Jeremy Reizenstein
b64fe51360 join_meshes_as_batch
Summary: rename join_meshes to join_meshes_as_batch.

Reviewed By: nikhilaravi

Differential Revision: D20671293

fbshipit-source-id: e84d6a67d6c1ec28fb5e52d4607db8e92561a4cd
2020-03-30 11:27:41 -07:00
Jeremy Reizenstein
27eb791e2f fix recent lint
Summary: Flowing of compositing comments

Reviewed By: nikhilaravi

Differential Revision: D20556707

fbshipit-source-id: 4abdc85e4f65abd41c4a890b6895bc5e95b4576b
2020-03-30 06:17:27 -07:00
Patrick Labatut
d57daa6f85 Address black + isort fbsource linter warnings
Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff)

Reviewed By: nikhilaravi

Differential Revision: D20558373

fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
2020-03-29 14:51:02 -07:00
Jeremy Reizenstein
37c5c8e0b6 Linter, deprecated type()
Summary: Run linter after recent changes. Fix long comment in knn.h which clang-format has reflowed badly. Add crude test that code doesn't call deprecated `.type()` or `.data()`.

Reviewed By: nikhilaravi

Differential Revision: D20692935

fbshipit-source-id: 28ce0308adae79a870cb41a810b7cf8744f41ab8
2020-03-29 14:02:58 -07:00
Patrick Labatut
3061c5b663 Fix saving / loading empty OBJ files
Summary:
OBJ files without vertices or faces should be allowed:
- an OBJ with only vertices can represent a point cloud
- an OBJ without any vertex or face is just empty
- an OBJ with faces referencing inexistent vertices has invalid data

Reviewed By: gkioxari

Differential Revision: D20392526

fbshipit-source-id: e72c846ff1e5787fb11d527af3fefa261f9eb0ee
2020-03-28 08:14:00 -07:00
Justin Johnson
870290df34 Implement K-Nearest Neighbors
Summary:
Implements K-Nearest Neighbors with C++ and CUDA versions.

KNN in CUDA is highly nontrivial. I've implemented a few different versions of the kernel, and we heuristically dispatch to different kernels based on the problem size. Some of the kernels rely on template specialization on either D or K, so we use template metaprogramming to compile specialized versions for ranges of D and K.

These kernels are up to 3x faster than our existing 1-nearest-neighbor kernels, so we should also consider swapping out `nn_points_idx` to use these kernels in the backend.

I've been working mostly on the CUDA kernels, and haven't converged on the correct Python API.

I still want to benchmark against FAISS to see how far away we are from their performance.

Reviewed By: bottler

Differential Revision: D19729286

fbshipit-source-id: 608ffbb7030c21fe4008f330522f4890f0c3c21a
2020-03-26 13:40:26 -07:00
Jeremy Reizenstein
81a4aa18ad type() deprecated
Summary:
Replace `tensor.type().is_cuda()` with the preferred `tensor.is_cuda()`.
Replace `AT_DISPATCH_FLOATING_TYPES(tensor.type(), ...` with `AT_DISPATCH_FLOATING_TYPES(tensor.scalar_type(), ...`.
These avoid deprecation warnings in future pytorch.

Reviewed By: nikhilaravi

Differential Revision: D20646565

fbshipit-source-id: 1a0c15978c871af816b1dd7d4a7ea78242abd95e
2020-03-26 04:01:41 -07:00
Jeremy Reizenstein
e22d431e5b data() deprecated
Summary: replace `data()` with preferred `data_ptr()`, avoiding some deprecation warnings in future pytorch.

Reviewed By: nikhilaravi

Differential Revision: D20645738

fbshipit-source-id: 8f6e02d292729b804fa2a66f94dd0517bbaf7887
2020-03-26 03:21:48 -07:00
Jeremy Reizenstein
8fa7678614 fix CPU-only hiding of cuda calls
Summary: CPU-only builds should be fixed by this change

Reviewed By: nikhilaravi

Differential Revision: D20598014

fbshipit-source-id: df098ec4c6c93d38515172805fe57cac7463c506
2020-03-24 05:04:32 -07:00
Jeremy Reizenstein
595aca27ea use assertClose
Summary: use assertClose in some tests, which enforces shape equality. Fixes some small problems, including graph_conv on an empty graph.

Reviewed By: nikhilaravi

Differential Revision: D20556912

fbshipit-source-id: 60a61eafe3c03ce0f6c9c1a842685708fb10ac5b
2020-03-23 11:36:38 -07:00
Georgia Gkioxari
03f441e7ca run lint
Summary: Run `/dev/linter.sh` to fix linting

Reviewed By: nikhilaravi

Differential Revision: D20584037

fbshipit-source-id: 69e45b33d22e3d54b6d37c3c35580bb3e9dc50a5
2020-03-21 17:58:15 -07:00
Georgia Gkioxari
6c48ff6ad9 replace view with reshape, check for nans
Summary: Replace view with reshape, add check for nans before mesh sampling

Reviewed By: nikhilaravi

Differential Revision: D20548456

fbshipit-source-id: c4e1b88e033ecb8f0f3a8f3a33a04ce13a5b5043
2020-03-19 19:31:41 -07:00
Olivia
53599770dd Accumulate points (#4)
Summary:
Code for accumulating points in the z-buffer in three ways:
1. weighted sum
2. normalised weighted sum
3. alpha compositing

Pull Request resolved: https://github.com/fairinternal/pytorch3d/pull/4

Reviewed By: nikhilaravi

Differential Revision: D20522422

Pulled By: gkioxari

fbshipit-source-id: 5023baa05f15e338f3821ef08f5552c2dcbfc06c
2020-03-19 11:23:12 -07:00
Patrick Labatut
5218f45c2c Add pattern linter for project names
Summary: Add pattern linter for PyTorch3D and SlowFast, this will suggest typo fixes whenever the wrong case is accidentally used.

Reviewed By: wanyenlo

Differential Revision: D20498696

fbshipit-source-id: 1a3f4702bd0dbe06e81d0f301b3ea38ea62e7885
2020-03-18 11:39:31 -07:00
Nikhila Ravi
3d3b2fdc46 Re-sync with internal repository 2020-03-18 10:35:27 -07:00
Dave Greenwood
2480723adf create extrinsic from eye point (#65)
Summary:
Create extrinsic parameters from eye point.
Create the rotation and translation from an eye point, look-at point and up vector.
see:
https://www.khronos.org/registry/OpenGL-Refpages/gl2.1/xhtml/gluLookAt.xml

It is arguably easier to initialise a camera position as a point in the world rather than an angle.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/65

Reviewed By: bottler

Differential Revision: D20419652

Pulled By: nikhilaravi

fbshipit-source-id: 9caa1330860bb8bde1fb5c3864ed4cde836a5d19
2020-03-17 17:04:19 -07:00
Patrick Labatut
c9742d00b0 Enable spelling linter for Markdown, reStructuredText and IPython notebooks
Summary: Enable spelling linter for Markdown, reStructuredText and IPython notebooks under `fbcode/vision/fair`. Apply suggested fixes.

Reviewed By: ppwwyyxx

Differential Revision: D20495298

fbshipit-source-id: 95310c7b51f9fa68ba2aa34ecc39a874da36a75c
2020-03-17 16:33:20 -07:00
Patrick Labatut
25d2e2c8b7 Use a consistent case for PyTorch3D
Summary: Use a consistent case for PyTorch3D (matching the logo...): replace all occurrences of PyTorch3d with PyTorch3D across the codebase (including documentation and notebooks)

Reviewed By: wanyenlo, gkioxari

Differential Revision: D20427546

fbshipit-source-id: 8c7697f51434c51e99b7fe271935932c72a1d9b9
2020-03-17 12:48:43 -07:00
Nikhila Ravi
5d3cc3569a Rendering texturing fixes
Summary:
Fix errors raised by issue on GitHub - extending mesh textures + rendering with Gourad and Phong shaders.

https://github.com/facebookresearch/pytorch3d/issues/97

Reviewed By: gkioxari

Differential Revision: D20319610

fbshipit-source-id: d1c692ff0b9397a77a9b829c5c731790de70c09f
2020-03-17 08:58:40 -07:00
Jeremy Reizenstein
fa81953380 test_build
Summary: Ensure copyright header consistency and translation unit name uniqueness.

Reviewed By: nikhilaravi

Differential Revision: D20438802

fbshipit-source-id: 9820cfe4c6efab016a0a8589dfa24bb526692f83
2020-03-16 07:54:56 -07:00
Nikhila Ravi
20e457ca0e [pytorch3d[ padded to packed function in struct utils
Summary: Added a padded to packed utils function which takes either split sizes or a padding value to remove padded elements from a tensor.

Reviewed By: gkioxari

Differential Revision: D20454238

fbshipit-source-id: 180b807ff44c74c4ee9d5c1ac3b5c4a9b4be57c7
2020-03-15 09:35:58 -07:00
Jeremy Reizenstein
2361845548 squared distance in comments
Summary: Comments were describing squared distance as absolute distance in a few places.

Reviewed By: nikhilaravi

Differential Revision: D20426020

fbshipit-source-id: 009946867c4a98f61f5ce7158542d41e22bf8346
2020-03-13 04:35:25 -07:00
Patrick Labatut
327868b86e Add utility function to tesselate a torus
Summary: Add utility function to tesselate a torus, to be used in more complex mesh I/O benchmarks

Reviewed By: bottler

Differential Revision: D20390724

fbshipit-source-id: 882bbbe9cac81cf340a34495b9aa66e3c1ddeebc
2020-03-13 04:31:25 -07:00
Patrick Labatut
3c71ab64cc Remove shebang line when not strictly required
Summary: The shebang line `#!<path to interpreter>` is only required for Python scripts, so remove it on source files for class or function definitions. Additionally explicitly mark as executable the actual Python scripts in the codebase.

Reviewed By: nikhilaravi

Differential Revision: D20095778

fbshipit-source-id: d312599fba485e978a243292f88a180d71e1b55a
2020-03-12 10:39:44 -07:00
Nikhila Ravi
d01e722849 Fix coordinate system conventions in point cloud renderer
Summary:
Applying the changes added for mesh rasterization to ensure that +Y is up and +X is left so that the coordinate system is right handed.

Also updated the diagram in the docs to indicate that (0,0) is in the top left hand corner.

Reviewed By: gkioxari

Differential Revision: D20394849

fbshipit-source-id: cfb7c79090eb1f55ad38b92327a74a70a8dc541e
2020-03-12 07:48:29 -07:00
Nikhila Ravi
32ad869dea Update point cloud rasterizer to support heterogeneous point clouds
Summary:
Update the point cloud rasterizer to:
- use the pointcloud datastructure (rebased on top of D19791851.)
- support rasterization of heterogeneous point clouds in the same way as with Meshes.

The main changes to the API will be as follows:
- The input to `rasterize_points` will be a `Pointclouds` object instead of a tensor. This will be easy to update e.g.
```
points = torch.randn(N, P, 3)
idx2, zbuf2, dists2 = rasterize_points(points, image_size, radius, points_per_pixel)

points = torch.randn(N, P, 3)
pointclouds = Pointclouds(points=points)
idx2, zbuf2, dists2 = rasterize_points(pointclouds, image_size, radius, points_per_pixel)
```

- The indices output from rasterization will now refer to points in `poinclouds.points_packed()`.
This may require some changes to the functions which consume the outputs of rasterization if they were previously
assuming that the indices ranged from 0 to P where P is the number of points in each pointcloud.

Making this change now so that Olivia can update her PR accordingly.

Reviewed By: gkioxari

Differential Revision: D20088651

fbshipit-source-id: 833ed659909712bcbbb6a50e2ec0189839f0413a
2020-03-12 07:48:29 -07:00
Roman Shapovalov
cae325718e Old-style string formatting fails when passed a tuple.
Summary: When the error occurs, another exception is thrown when tensor shape is passed to the % formatting. I have found all entries for `msg %` and fixed potential failures

Reviewed By: nikhilaravi

Differential Revision: D20386511

fbshipit-source-id: c05413eb4867cab1ddc9615dffbd0ebd3adfcaf9
2020-03-11 11:17:58 -07:00
Jeremy Reizenstein
fb97ab104e getitem for textures
Summary: Make Meshes.__getitem__ carry texture information to the new mesh.

Reviewed By: gkioxari

Differential Revision: D20283976

fbshipit-source-id: d9ee0580c11ac5b4384df9d8158a07e6eb8d00fe
2020-03-11 07:45:44 -07:00
Jeremy Reizenstein
5a1d7143d8 post-release v0.1.1 updates.
Reviewed By: nikhilaravi

Differential Revision: D20218481

fbshipit-source-id: b153282cc30ad75de970c89ae64526b6be62ee95
2020-03-09 06:37:50 -07:00
Jeremy Reizenstein
cf8e667b61 version 0.1.1
Summary: Bumping the version number to 0.1.1 and thereby documenting all the places where the version number currently appears in the code.

Reviewed By: nikhilaravi

Differential Revision: D20067382

fbshipit-source-id: 76a25ed1d4036f51357e4ae3e0f07de32ad114ae
2020-03-07 12:42:43 -08:00
Nikhila Ravi
15c72be444 Fix coordinate system conventions in renderer
Summary:
## Updates

- Defined the world and camera coordinates according to this figure. The world coordinates are defined as having +Y up, +X left and +Z in.

{F230888499}

- Removed all flipping from blending functions.
- Updated the rasterizer to return images with +Y up and +X left.
- Updated all the mesh rasterizer tests
    - The expected values are now defined in terms of the default +Y up, +X left
    - Added tests where the triangles in the meshes are non symmetrical so that it is clear which direction +X and +Y are

## Questions:
- Should we have **scene settings** instead of raster settings?
    - To be more correct we should be [z clipping in the rasterizer based on the far/near clipping planes](https://github.com/ShichenLiu/SoftRas/blob/master/soft_renderer/cuda/soft_rasterize_cuda_kernel.cu#L400) - these values are also required in the blending functions so should we make these scene level parameters and have a scene settings tuple which is available to the rasterizer and shader?

Reviewed By: gkioxari

Differential Revision: D20208604

fbshipit-source-id: 55787301b1bffa0afa9618f0a0886cc681da51f3
2020-03-06 06:51:05 -08:00
Nikhila Ravi
ba11c0b59c Blending fixes and test updates
Summary:
Changed `torch.cumprod` to `torch.prod` in blending functions and added more tests and benchmark tests.

This should fix the issue raised on GitHub.

Reviewed By: gkioxari

Differential Revision: D20163073

fbshipit-source-id: 4569fd37be11aa4435a3ce8736b55622c00ec718
2020-02-29 17:52:05 -08:00
Nikhila Ravi
ff19c642cb Barycentric clipping in the renderer and flat shading
Summary:
Updates to the Renderer to enable barycentric clipping. This is important when there is blurring in the rasterization step.

Also added support for flat shading.

Reviewed By: jcjohnson

Differential Revision: D19934259

fbshipit-source-id: 036e48636cd80d28a04405d7a29fcc71a2982904
2020-02-28 21:30:33 -08:00
takiyu
f358b9b14d Fix squared distance for CPU impl. (#83)
Summary:
`PointLineDistanceForward()` should return squared distance. However, it seems that it returned non-squared distance when `v0` was near by `v1` in CPU implementation.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/83

Reviewed By: bottler

Differential Revision: D20097181

Pulled By: nikhilaravi

fbshipit-source-id: 7ea851c0837ab89364e42d283c999df21ff5ff02
2020-02-25 14:00:00 -08:00
Dave Greenwood
a0f3dc2d63 allow changes to background_color in BlendParams (#64)
Summary:
BlendParams background_color is immutable , type hint as a sequence allows setting new values in constructor.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/64

Reviewed By: bottler

Differential Revision: D20068911

Pulled By: nikhilaravi

fbshipit-source-id: c580a7654dca25629218513841aa16d9d1055588
2020-02-24 13:44:02 -08:00
Georgia Gkioxari
c2a0a3e3ba fix docstring of mesh edge loss
Summary: Fix docstring for mesh edge loss

Reviewed By: jcjohnson

Differential Revision: D20040560

fbshipit-source-id: 01a3ee9473c7d11583684bf4cd200caa1d3f0260
2020-02-21 15:55:37 -08:00
Jeremy Reizenstein
e491efb81f lint things
Summary:
Lint related fixes: Improve internal/OSS consistency. Fix the fight between black and certain pyre-ignore markers by moving them to the line before.
Use clang-format-8 automatically if present. Small number of pyre fixes.

arc doesn't run pyre at the moment, so I put back the explicit call to pyre. I don't know if there's an option somewhere to change this.

Reviewed By: nikhilaravi

Differential Revision: D19780518

fbshipit-source-id: ef1c243392322fa074130f6cff2dd8a6f7738a7f
2020-02-21 05:05:06 -08:00
merayxu
9e21659fc5 Fixed windows MSVC build compatibility (#9)
Summary:
Fixed a few MSVC compiler (visual studio 2019, MSVC 19.16.27034) compatibility issues
1. Replaced long with int64_t. aten::data_ptr\<long\> is not supported in MSVC
2. pytorch3d/csrc/rasterize_points/rasterize_points_cpu.cpp, inline function is not correctly recognized by MSVC.
3. pytorch3d/csrc/rasterize_meshes/geometry_utils.cuh
const auto kEpsilon = 1e-30;
MSVC does not compile this const into both host and device, change to a MACRO.
4. pytorch3d/csrc/rasterize_meshes/geometry_utils.cuh,
const float area2 = pow(area, 2.0);
2.0 is considered as double by MSVC and raised an error
5. pytorch3d/csrc/rasterize_points/rasterize_points_cpu.cpp
std::tuple<torch::Tensor, torch::Tensor> RasterizePointsCoarseCpu() return type does not match the declaration in rasterize_points_cpu.h.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/9

Reviewed By: nikhilaravi

Differential Revision: D19986567

Pulled By: yuanluxu

fbshipit-source-id: f4d98525d088c99c513b85193db6f0fc69c7f017
2020-02-20 18:43:19 -08:00
Georgia Gkioxari
a3baa367e3 face areas backward
Summary:
Added backward for mesh face areas & normals. Exposed it as a layer. Replaced the computation with the new op in Meshes and in Sample Points.

Current issue: Circular imports. I moved the import of the op in meshes inside the function scope.

Reviewed By: jcjohnson

Differential Revision: D19920082

fbshipit-source-id: d213226d5e1d19a0c8452f4d32771d07e8b91c0a
2020-02-20 11:11:33 -08:00
Patrick Labatut
9ca5489107 Fix spelling of "Gouraud"
Summary: Fix spelling of *Gouraud* in [Gouraud shading](https://en.wikipedia.org/wiki/Gouraud_shading).

Reviewed By: nikhilaravi

Differential Revision: D19943547

fbshipit-source-id: 5c016b7b051a7b33a7b68ed5303b642d9e834bbd
2020-02-20 01:11:56 -08:00
Nikhila Ravi
f0dc65110a Shader API more consistent naming
Summary:
Renamed shaders to be prefixed with Hard/Soft depending on if they use a probabalistic blending (Soft) or use the closest face (Hard).

There is some code duplication but I thought it would be cleaner to have separate shaders for each task rather than:
- inheritance (which we discussed previously that we want to avoid)
- boolean (hard/soft) or a string (hard/soft) - new blending functions other than the ones provided would need if statements in the current shaders which might get messy.

Also added a `flat_shading` function and a `FlatShader` - I could make this into a tutorial as it was really easy to add a new shader and it might be a nice showcase.

NOTE: There are a few more places where the naming will need to change (e.g the tutorials) but I wanted to reach a consensus on this before changing it everywhere.

Reviewed By: jcjohnson

Differential Revision: D19761036

fbshipit-source-id: f972f6530c7f66dc5550b0284c191abc4a7f6fc4
2020-02-19 23:16:50 -08:00
Georgia Gkioxari
60f3c4e7d2 cpp support for packed to padded
Summary:
Cpu implementation for packed to padded and added gradients
```
Benchmark                                     Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
PACKED_TO_PADDED_2_100_300_1_cpu                    138             221           3625
PACKED_TO_PADDED_2_100_300_1_cuda:0                 184             261           2716
PACKED_TO_PADDED_2_100_300_16_cpu                   555             726            901
PACKED_TO_PADDED_2_100_300_16_cuda:0                179             260           2794
PACKED_TO_PADDED_2_100_3000_1_cpu                   396             519           1262
PACKED_TO_PADDED_2_100_3000_1_cuda:0                181             274           2764
PACKED_TO_PADDED_2_100_3000_16_cpu                 4517            5003            111
PACKED_TO_PADDED_2_100_3000_16_cuda:0               224             397           2235
PACKED_TO_PADDED_2_1000_300_1_cpu                   138             212           3616
PACKED_TO_PADDED_2_1000_300_1_cuda:0                180             282           2775
PACKED_TO_PADDED_2_1000_300_16_cpu                  565             711            885
PACKED_TO_PADDED_2_1000_300_16_cuda:0               179             264           2797
PACKED_TO_PADDED_2_1000_3000_1_cpu                  389             494           1287
PACKED_TO_PADDED_2_1000_3000_1_cuda:0               180             271           2777
PACKED_TO_PADDED_2_1000_3000_16_cpu                4522            5170            111
PACKED_TO_PADDED_2_1000_3000_16_cuda:0              216             286           2313
PACKED_TO_PADDED_10_100_300_1_cpu                   251             345           1995
PACKED_TO_PADDED_10_100_300_1_cuda:0                178             262           2806
PACKED_TO_PADDED_10_100_300_16_cpu                 2354            2750            213
PACKED_TO_PADDED_10_100_300_16_cuda:0               178             291           2814
PACKED_TO_PADDED_10_100_3000_1_cpu                 1519            1786            330
PACKED_TO_PADDED_10_100_3000_1_cuda:0               179             237           2791
PACKED_TO_PADDED_10_100_3000_16_cpu               24705           25879             21
PACKED_TO_PADDED_10_100_3000_16_cuda:0              228             316           2191
PACKED_TO_PADDED_10_1000_300_1_cpu                  261             432           1919
PACKED_TO_PADDED_10_1000_300_1_cuda:0               181             261           2756
PACKED_TO_PADDED_10_1000_300_16_cpu                2349            2770            213
PACKED_TO_PADDED_10_1000_300_16_cuda:0              180             256           2782
PACKED_TO_PADDED_10_1000_3000_1_cpu                1613            1929            310
PACKED_TO_PADDED_10_1000_3000_1_cuda:0              183             253           2739
PACKED_TO_PADDED_10_1000_3000_16_cpu              22041           23653             23
PACKED_TO_PADDED_10_1000_3000_16_cuda:0             220             343           2270
PACKED_TO_PADDED_32_100_300_1_cpu                   555             750            901
PACKED_TO_PADDED_32_100_300_1_cuda:0                188             282           2661
PACKED_TO_PADDED_32_100_300_16_cpu                 7550            8131             67
PACKED_TO_PADDED_32_100_300_16_cuda:0               181             272           2770
PACKED_TO_PADDED_32_100_3000_1_cpu                 4574            6327            110
PACKED_TO_PADDED_32_100_3000_1_cuda:0               173             254           2884
PACKED_TO_PADDED_32_100_3000_16_cpu               70366           72563              8
PACKED_TO_PADDED_32_100_3000_16_cuda:0              349             654           1433
PACKED_TO_PADDED_32_1000_300_1_cpu                  612             728            818
PACKED_TO_PADDED_32_1000_300_1_cuda:0               189             295           2647
PACKED_TO_PADDED_32_1000_300_16_cpu                7699            8254             65
PACKED_TO_PADDED_32_1000_300_16_cuda:0              189             311           2646
PACKED_TO_PADDED_32_1000_3000_1_cpu                5105            5261             98
PACKED_TO_PADDED_32_1000_3000_1_cuda:0              191             260           2625
PACKED_TO_PADDED_32_1000_3000_16_cpu              87073           92708              6
PACKED_TO_PADDED_32_1000_3000_16_cuda:0             344             425           1455
--------------------------------------------------------------------------------

Benchmark                                           Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
PACKED_TO_PADDED_TORCH_2_100_300_1_cpu                    492             627           1016
PACKED_TO_PADDED_TORCH_2_100_300_1_cuda:0                 768             975            652
PACKED_TO_PADDED_TORCH_2_100_300_16_cpu                   659             804            760
PACKED_TO_PADDED_TORCH_2_100_300_16_cuda:0                781             918            641
PACKED_TO_PADDED_TORCH_2_100_3000_1_cpu                   624             734            802
PACKED_TO_PADDED_TORCH_2_100_3000_1_cuda:0                778             929            643
PACKED_TO_PADDED_TORCH_2_100_3000_16_cpu                 2609            2850            192
PACKED_TO_PADDED_TORCH_2_100_3000_16_cuda:0               758             901            660
PACKED_TO_PADDED_TORCH_2_1000_300_1_cpu                   467             612           1072
PACKED_TO_PADDED_TORCH_2_1000_300_1_cuda:0                772             905            648
PACKED_TO_PADDED_TORCH_2_1000_300_16_cpu                  689             839            726
PACKED_TO_PADDED_TORCH_2_1000_300_16_cuda:0               789            1143            635
PACKED_TO_PADDED_TORCH_2_1000_3000_1_cpu                  629             735            795
PACKED_TO_PADDED_TORCH_2_1000_3000_1_cuda:0               812             916            616
PACKED_TO_PADDED_TORCH_2_1000_3000_16_cpu                2716            3117            185
PACKED_TO_PADDED_TORCH_2_1000_3000_16_cuda:0              844            1288            593
PACKED_TO_PADDED_TORCH_10_100_300_1_cpu                  2387            2557            210
PACKED_TO_PADDED_TORCH_10_100_300_1_cuda:0               4112            4993            122
PACKED_TO_PADDED_TORCH_10_100_300_16_cpu                 3385            4254            148
PACKED_TO_PADDED_TORCH_10_100_300_16_cuda:0              3959            4902            127
PACKED_TO_PADDED_TORCH_10_100_3000_1_cpu                 2918            3105            172
PACKED_TO_PADDED_TORCH_10_100_3000_1_cuda:0              4054            4450            124
PACKED_TO_PADDED_TORCH_10_100_3000_16_cpu               12748           13623             40
PACKED_TO_PADDED_TORCH_10_100_3000_16_cuda:0             4023            4395            125
PACKED_TO_PADDED_TORCH_10_1000_300_1_cpu                 2258            2492            222
PACKED_TO_PADDED_TORCH_10_1000_300_1_cuda:0              3997            4312            126
PACKED_TO_PADDED_TORCH_10_1000_300_16_cpu                3404            3597            147
PACKED_TO_PADDED_TORCH_10_1000_300_16_cuda:0             3877            4227            129
PACKED_TO_PADDED_TORCH_10_1000_3000_1_cpu                2789            3054            180
PACKED_TO_PADDED_TORCH_10_1000_3000_1_cuda:0             3821            4402            131
PACKED_TO_PADDED_TORCH_10_1000_3000_16_cpu              11967           12963             42
PACKED_TO_PADDED_TORCH_10_1000_3000_16_cuda:0            3729            4290            135
PACKED_TO_PADDED_TORCH_32_100_300_1_cpu                  6933            8152             73
PACKED_TO_PADDED_TORCH_32_100_300_1_cuda:0              11856           12287             43
PACKED_TO_PADDED_TORCH_32_100_300_16_cpu                 9895           11205             51
PACKED_TO_PADDED_TORCH_32_100_300_16_cuda:0             12354           13596             41
PACKED_TO_PADDED_TORCH_32_100_3000_1_cpu                 9516           10128             53
PACKED_TO_PADDED_TORCH_32_100_3000_1_cuda:0             12917           13597             39
PACKED_TO_PADDED_TORCH_32_100_3000_16_cpu               41209           43783             13
PACKED_TO_PADDED_TORCH_32_100_3000_16_cuda:0            12210           13288             41
PACKED_TO_PADDED_TORCH_32_1000_300_1_cpu                 7179            7689             70
PACKED_TO_PADDED_TORCH_32_1000_300_1_cuda:0             11896           12381             43
PACKED_TO_PADDED_TORCH_32_1000_300_16_cpu               10127           15494             50
PACKED_TO_PADDED_TORCH_32_1000_300_16_cuda:0            12034           12817             42
PACKED_TO_PADDED_TORCH_32_1000_3000_1_cpu                8743           10251             58
PACKED_TO_PADDED_TORCH_32_1000_3000_1_cuda:0            12023           12908             42
PACKED_TO_PADDED_TORCH_32_1000_3000_16_cpu              39071           41777             13
PACKED_TO_PADDED_TORCH_32_1000_3000_16_cuda:0           11999           13690             42
--------------------------------------------------------------------------------
```

Reviewed By: bottler, nikhilaravi, jcjohnson

Differential Revision: D19870575

fbshipit-source-id: 23a2477b73373c411899633386c87ab034c3702a
2020-02-19 10:48:54 -08:00
Nikhila Ravi
8301163d24 transforms 3d convention fix
Summary: Fixed the rotation matrices generated by the RotateAxisAngle class and updated the tests. Added documentation for Transforms3d to clarify the conventions.

Reviewed By: gkioxari

Differential Revision: D19912903

fbshipit-source-id: c64926ce4e1381b145811557c32b73663d6d92d1
2020-02-19 10:32:44 -08:00
Jeremy Reizenstein
bdc2bb578c MACOSX_DEPLOYMENT_TARGET=10.14
Summary:
pybind now seems to need C++17 on a mac, so advise people to use it. (Also delete an unused variable to silence a warning I got on a mac build.)

Reported in github issue #68.

Reviewed By: nikhilaravi

Differential Revision: D19970512

fbshipit-source-id: f9be20c8ed425bd6ba8d009a7d62dad658dccdb1
2020-02-19 08:43:50 -08:00
Chr1k0
234658901a Update obj_io.py: Make PyTorch3D work with ShapeNetCore.v2 (#49)
Summary:
Making PyTorch3D work with ShapeNetCore.v2 models from http://shapenet.cs.stanford.edu/shapenet/obj-zip/ShapeNetCore.v2/
The face identifier of the ShapeNetCore.v2 models is followed by two not one blank - example:
"f  1/1/1 2/2/2 3/3/3" instead of
"f 1/1/1 2/2/2 3/3/3"
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/49

Differential Revision: D19951828

Pulled By: gkioxari

fbshipit-source-id: 5695df0fca2059e75eeb73edf4cfe9d9f008e841
2020-02-18 11:11:58 -08:00
Nikhila Ravi
97acf16de2 lint fixes
Summary: Ran `dev/linter.sh`.

Reviewed By: bottler

Differential Revision: D19761062

fbshipit-source-id: 1a49abe4a5f2bc7641b2b46e254aa77e6a48aa7d
2020-02-13 20:50:48 -08:00
Georgia Gkioxari
29cd181a83 CPU implem for face areas normals
Summary:
Added cpu implementation for face areas normals. Moved test and bm to separate functions.

```
Benchmark                                   Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
FACE_AREAS_NORMALS_2_100_300_False                196             268           2550
FACE_AREAS_NORMALS_2_100_300_True                 106             179           4733
FACE_AREAS_NORMALS_2_100_3000_False              1447            1630            346
FACE_AREAS_NORMALS_2_100_3000_True                107             178           4674
FACE_AREAS_NORMALS_2_1000_300_False               201             309           2486
FACE_AREAS_NORMALS_2_1000_300_True                107             186           4673
FACE_AREAS_NORMALS_2_1000_3000_False             1451            1636            345
FACE_AREAS_NORMALS_2_1000_3000_True               107             186           4655
FACE_AREAS_NORMALS_10_100_300_False               767             918            653
FACE_AREAS_NORMALS_10_100_300_True                106             167           4712
FACE_AREAS_NORMALS_10_100_3000_False             7036            7754             72
FACE_AREAS_NORMALS_10_100_3000_True               113             164           4445
FACE_AREAS_NORMALS_10_1000_300_False              748             947            669
FACE_AREAS_NORMALS_10_1000_300_True               108             169           4638
FACE_AREAS_NORMALS_10_1000_3000_False            7069            7783             71
FACE_AREAS_NORMALS_10_1000_3000_True              108             172           4646
FACE_AREAS_NORMALS_32_100_300_False              2286            2496            219
FACE_AREAS_NORMALS_32_100_300_True                108             180           4631
FACE_AREAS_NORMALS_32_100_3000_False            23184           24369             22
FACE_AREAS_NORMALS_32_100_3000_True               159             213           3147
FACE_AREAS_NORMALS_32_1000_300_False             2414            2645            208
FACE_AREAS_NORMALS_32_1000_300_True               112             197           4480
FACE_AREAS_NORMALS_32_1000_3000_False           21687           22964             24
FACE_AREAS_NORMALS_32_1000_3000_True              141             211           3540
--------------------------------------------------------------------------------

Benchmark                                         Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
FACE_AREAS_NORMALS_TORCH_2_100_300_False               5465            5782             92
FACE_AREAS_NORMALS_TORCH_2_100_300_True                1198            1351            418
FACE_AREAS_NORMALS_TORCH_2_100_3000_False             48228           48869             11
FACE_AREAS_NORMALS_TORCH_2_100_3000_True               1186            1304            422
FACE_AREAS_NORMALS_TORCH_2_1000_300_False              5556            6097             90
FACE_AREAS_NORMALS_TORCH_2_1000_300_True               1200            1328            417
FACE_AREAS_NORMALS_TORCH_2_1000_3000_False            48683           50016             11
FACE_AREAS_NORMALS_TORCH_2_1000_3000_True              1185            1306            422
FACE_AREAS_NORMALS_TORCH_10_100_300_False             24215           25097             21
FACE_AREAS_NORMALS_TORCH_10_100_300_True               1150            1314            435
FACE_AREAS_NORMALS_TORCH_10_100_3000_False           232605          234952              3
FACE_AREAS_NORMALS_TORCH_10_100_3000_True              1193            1314            420
FACE_AREAS_NORMALS_TORCH_10_1000_300_False            24912           25343             21
FACE_AREAS_NORMALS_TORCH_10_1000_300_True              1216            1330            412
FACE_AREAS_NORMALS_TORCH_10_1000_3000_False          239907          241253              3
FACE_AREAS_NORMALS_TORCH_10_1000_3000_True             1226            1333            408
FACE_AREAS_NORMALS_TORCH_32_100_300_False             73991           75776              7
FACE_AREAS_NORMALS_TORCH_32_100_300_True               1193            1339            420
FACE_AREAS_NORMALS_TORCH_32_100_3000_False           728932          728932              1
FACE_AREAS_NORMALS_TORCH_32_100_3000_True              1186            1359            422
FACE_AREAS_NORMALS_TORCH_32_1000_300_False            76385           79129              7
FACE_AREAS_NORMALS_TORCH_32_1000_300_True              1165            1310            430
FACE_AREAS_NORMALS_TORCH_32_1000_3000_False          753276          753276              1
FACE_AREAS_NORMALS_TORCH_32_1000_3000_True             1205            1340            415
--------------------------------------------------------------------------------
```

Reviewed By: bottler, jcjohnson

Differential Revision: D19864385

fbshipit-source-id: 3a87ae41a8e3ab5560febcb94961798f2e09dfb8
2020-02-13 11:42:48 -08:00