GitLab

Summary: Simple method to add terms and privacy.

Reviewed By: nikhilaravi

Differential Revision: D22476671

fbshipit-source-id: 5b0503536f9a95961c46c93895c9e351c0401118

Summary:
This diff
* removes the unused compositing params
* adds a note describing cubify

Reviewed By: nikhilaravi

Differential Revision: D22426191

fbshipit-source-id: e8aa32040bb594e1dfd7d6d98e29264feefcec7c

Summary: Remove abbreviated installation instructions from the homepage because they confuse.

Reviewed By: gkioxari

Differential Revision: D22160787

fbshipit-source-id: 8eb81030727f71951f8785f71c0a332ef58e790c

Summary:
There is a bug in efficient PnP that incorrectly weights points. This fixes it.

The test does not pass for the previous version with the bug.

Reviewed By: shapovalov

Differential Revision: D22449357

fbshipit-source-id: f5a22081e91d25681a6a783cce2f5c6be429ca6a

Summary: Conversion to/from the 6D representation of rotation from the paper http://arxiv.org/abs/1812.07035 ; based on David’s implementation.

Reviewed By: davnov134

Differential Revision: D22234397

fbshipit-source-id: 9e25ee93da7e3a2f2068cbe362cb5edc88649ce0

Summary: Update the transform step in the pointcloud rasterizer to use the `update_padded` method on `Pointclouds`.  There was an inefficient step using `offset_points` which went via the packed represntation (and required unecessary additional memory). I think this was before the `update_padded` method was added to `Pointclouds`.

Reviewed By: gkioxari

Differential Revision: D22329166

fbshipit-source-id: 76db8a19654fb2f7807635d4f1c1729debdf3320

Summary:
The documentation of `Transform3d` highlights that the class handles points as well as normals. However, `transform_points` is applied to points and normals in the documentation instead of using `transform_normals` for normals, which I believe was intended.

This pull request fixes this typo in the documentation.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/233

Reviewed By: bottler

Differential Revision: D22287642

Pulled By: nikhilaravi

fbshipit-source-id: 0bc8754097b2e17a34fa3071319d00b78c3bc803

Summary:
Fix:
* Scaling of point clouds for scalars
* save_ply compatible cat

Reviewed By: nikhilaravi

Differential Revision: D22298609

fbshipit-source-id: abe94a5b64baf325587202d20adfc36912cc1478

Reviewed By: nikhilaravi

Differential Revision: D22357376

fbshipit-source-id: c103f9b0c798d4425d642781b5bfbb1a27310270

Summary: It's easier to understand code changes if we don't store the output in the notebooks. This is just a run of nbstripout on all the notebooks.

Reviewed By: nikhilaravi

Differential Revision: D22357375

fbshipit-source-id: bffdb426af2f676d448630d717658d609c224811

Summary:
Automatic run to suppress type errors.
 #pyreupgrade

Differential Revision: D22369027

fbshipit-source-id: 2beb1a43e429a0850944a8849d416bedefd516ed

Summary: Added `sorted` argument to the `knn_points` function. This came up during the benchmarking against Faiss - sorting added extra memory usage. Match the memory usage of Faiss by making sorting optional.

Reviewed By: bottler, gkioxari

Differential Revision: D22329070

fbshipit-source-id: 0828ff9b48eefce99ce1f60089389f6885d03139

Summary:
Fix default setting of `max_faces_per_bin` and update mesh rasterization benchmark tests.
The previous setting of `max_faces_per_bin` was wrong and for larger mesh sizes and batch sizes it was causing a significant slow down due to an unecessarily large intermediate tensor being created.

Reviewed By: gkioxari

Differential Revision: D22301819

fbshipit-source-id: d5e817f5b917fb5633c9c6a8634b6c8ff65e3508

Summary:
Fixes the default setting of `max_points_per_bin` in `rasterize_points.py`. For large batches with large size pointclouds this was a causing the rasterizer to be very slow.

Expanded the pointcloud rendering benchmarks to include larger size pointclouds and fixed cuda synchronization issue in benchmark.

Reviewed By: gkioxari

Differential Revision: D22301185

fbshipit-source-id: 5077c1ba2c43d73efc1c659f0ec75959ceddf893

Summary: Adding datasets.rst to modules and update index.rst.

Reviewed By: nikhilaravi

Differential Revision: D22187578

fbshipit-source-id: e70cf49fa276db8a106c67a2edab530b6dba2dee

Summary: Now pytorch 1.5.1 is released, pytorch 1.5 is ambiguous and causes problems. Now have specific builds for pytorch 1.5.0 and 1.5.1. Here we only change the conda builds.

Reviewed By: gkioxari

Differential Revision: D22196016

fbshipit-source-id: 478327e870f538f54d3480d5a268a1ece5c5c680

Summary: Adding support so that users can select which categories they would like to load with wordnet synset offsets or labels or a combination of both. ShapeNetCore now also supports loading v2.

Reviewed By: nikhilaravi

Differential Revision: D22039207

fbshipit-source-id: 1f0218acb790e5561e2ae373e99cebb9823eea1a

Summary: Skeleton of ShapeNetCore class that loads ShapeNet v1 from a given directory to a Dataset object. Overrides _init_, _len_, and _getitem_ from torch.utils.data.Dataset. Currently getitem returns verts, faces and id_str, where id_str is a concatenation of synset_id and obj_id. Planning on adding support for loading ShapeNet v2, retrieving textures and returning wordnet synsets (not just ids) in next diffs.

Reviewed By: nikhilaravi

Differential Revision: D21986222

fbshipit-source-id: c2c515303f1898b6c495b52cb53c74d691585326

Summary: Fix the new CPU implementation of point_mesh functionality to be compatible with older C++.

Reviewed By: nikhilaravi

Differential Revision: D22066785

fbshipit-source-id: a245849342019a93ff68e186a10985458b007436

Summary:
point_mesh functions were missing CPU implementations.
The indices returned are not always matching, possibly due to numerical instability.

Reviewed By: gkioxari

Differential Revision: D21594264

fbshipit-source-id: 3016930e2a9a0f3cd8b3ac4c94a92c9411c0989d

Summary:
Pytorch seems to be becoming stricter about integer tensors of shape `(1,)` on GPU and not allowing them to be used as `int`s. For example the following no longer works on pytorch master,
    foo = torch.tensor([3, 5, 3], device="cuda:0")
    torch.arange(10) + foo[0]
because this is the sum of tensors on different devices.

Here fix tests which recently broke because of this.

Reviewed By: nikhilaravi

Differential Revision: D21929745

fbshipit-source-id: 25374f70468d1c895372766f1a9dd61df0833957

Summary: [Folly] Cut the FOR_EACH_KV macro, which may be replaced by a combination of range-for and structured bindings.

Differential Revision: D21826182

fbshipit-source-id: ce4712afd3d0d7806eb1fca8c97009da117f982e

Summary: Adding a function in pytorch3d.structures.meshes to join multiple meshes into a Meshes object representing a single mesh. The function currently ignores all textures.

Reviewed By: nikhilaravi

Differential Revision: D21876908

fbshipit-source-id: 448602857e9d3d3f774d18bb4e93076f78329823

Summary:
To address the issue https://github.com/facebookresearch/pytorch3d/issues/219 of Invalid rotation matrix when number of camera position is equal to 3
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/220

Reviewed By: bottler

Differential Revision: D21877606

Pulled By: nikhilaravi

fbshipit-source-id: f95ae44497cae33f2f0cff1b1718d866cf79bda1

Summary: To avoid pytorch warnings and future behaviour changes, stop using torch.div and / with tensors of integers.

Reviewed By: gkioxari, mruberry

Differential Revision: D21857955

fbshipit-source-id: fb9f3000f3d953352cdc721d2a5f73d3a4bbf4b7

Summary: [Folly] Cut the `FOR_EACH_ENUMERATE` macro, which may be replaced by a combination of range-for, `ranges::view::enumerate`, and structured bindings.

Reviewed By: markisaa

Differential Revision: D21813019

fbshipit-source-id: fc9ac09a4e2f72f1433d0a518f03d5cd69a59c55

Summary: Adds support to hard_rgb_blend and hard blending shaders in shader.py (HardPhongShader, HardGouraudShader, and HardFlatShader) for changing the background color on which objects are rendered

Reviewed By: nikhilaravi

Differential Revision: D21746062

fbshipit-source-id: 08001200f4339d6a69c52405c6b8f4cac9f3f56e

Summary:
Update the transform method in the mesh rasterizer class to use the new `update_padded` method on the `Meshes` class to directly update the mesh vertices.

Also added a benchmark.

Reviewed By: gkioxari

Differential Revision: D21700352

fbshipit-source-id: c330e4040c681729eb2cc7bdfd92fb4a51a1a7d6

Summary:
Three changes to Meshes

1. `num_verts_per_mesh` and `num_faces_per_mesh` are assigned at construction time and are returned without the need for `compute_packed`
2. `update_padded` updates `verts_padded` and shallow copies faces list and faces_padded and existing attributes from construction.
3. `padded_to_packed_idx` does not need `compute_packed`

Reviewed By: nikhilaravi

Differential Revision: D21653674

fbshipit-source-id: dc6815a2e2a925fe4a834fe357919da2b2c14527

Summary:
This diff is auto-generated to upgrade the Pyre version and suppress errors in vision. The upgrade will affect Pyre local configurations in the following directories:
```
vision/ale/search
vision/fair/fvcore
vision/fair/pytorch3d
vision/ocr/rosetta_hash
vision/vogue/personalization
```

Differential Revision: D21688454

fbshipit-source-id: 1f3c3fee42b6da2e162fd0932742ab8c5c96aa45

Summary:
Fix division by zero when alpha is 1.0
In this case, the nominator is already 0 and we need to make sure division with 0 does not occur which would produce nans

Reviewed By: nikhilaravi

Differential Revision: D21650478

fbshipit-source-id: bc457105b3050fef1c8bd4e58e7d6d15c0c81ffd

Summary: Add ability to decode ply files which use types like int32.

Reviewed By: nikhilaravi

Differential Revision: D21639208

fbshipit-source-id: 0ede7d4aa353a6e940446680a18e7ac0c48fafee

Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/204

Reviewed By: gkioxari

Differential Revision: D21621695

Pulled By: nikhilaravi

fbshipit-source-id: 556f297bef4211c331dfde6471e10762a9956f98

Summary: I was trying to speed up the lighting computations, but my ideas didn't work. Even if that didn't work, we can at least commit the benchmarking script I wrote for diffuse and specular shading.

Reviewed By: nikhilaravi

Differential Revision: D21580171

fbshipit-source-id: 8b60c0284e91ecbe258b6aae839bd5c2bbe788aa

Summary:
Update the cuda kernels to:
- remove contiguous checks for the grad tensors and for cpu functions which use accessors
- for cuda implementations call `.contiguous()` on all tensors in the host function before invoking the kernel

Reviewed By: gkioxari

Differential Revision: D21598008

fbshipit-source-id: 9b97bda4582fd4269c8a00999874d4552a1aea2d

Summary: lg-zhang found the problem with the quadratic part of ePnP implementation: n262385 . It was caused by a coefficient returned from the linear equation solver being equal to exactly 0.0, which caused `sign()` to return 0, something I had not anticipated. I also made sure we avoid division by zero by clamping all relevant denominators.

Reviewed By: nikhilaravi, lg-zhang

Differential Revision: D21531200

fbshipit-source-id: 9eb2fa9d4f4f8f5f411d4cf1cffcc44b365b7e51

Summary:
Make flat shading differentiable again

Currently test fails with P130944403 which looks weird.

Reviewed By: nikhilaravi

Differential Revision: D21567106

fbshipit-source-id: 65995b64739e08397b3d021b65625e3c377cd1a5

Summary: pytorch is adding checks that mean integer tensors with requires_grad=True need to be avoided. Fix accidentally creating them.

Reviewed By: jcjohnson, gkioxari

Differential Revision: D21576712

fbshipit-source-id: 008218997986800a36d93caa1a032ee91f2bffcd

Summary: Use `self.__class__` when creating new instances, to slightly accommodate inheritance.

Reviewed By: nikhilaravi

Differential Revision: D21504476

fbshipit-source-id: b4600d15462fc1985da95a4cf761c7d794cfb0bb

Summary:
Fixes the case where the rotation angle is exactly 0/PI.
Added a test for `so3_log_map(identity_matrix)`.

Reviewed By: nikhilaravi

Differential Revision: D21477078

fbshipit-source-id: adff804da97f6f0d4f50aa1f6904a34832cb8bfe