GitLab

Summary: Fixing several unused imports and pyre/linter warnings.

Reviewed By: bottler

Differential Revision: D22592491

fbshipit-source-id: 463383b9b73a545949475044fb5c531712f8482c

Summary: Added link to the youtube video of the PyTorch hackathon tutorial to the README.

Reviewed By: bottler

Differential Revision: D22592655

fbshipit-source-id: 7b3791042a0d6f7e1d3b5602580f10b08a48fe43

Summary:
1. CircleCI tests fail because of different randomisation. I was able to reproduce it on devfair (with an older version of pytorch3d though), but with a new threshold, it works. Let’s push and see if it will work in CircleCI.
2. Fixing linter’s issue with `l` variable name.

Reviewed By: bottler

Differential Revision: D22573244

fbshipit-source-id: 32cebc8981883a3411ed971eb4a617469376964d

Summary:
Added support for barycentric clipping in the C++/CUDA rasterization kernels which can be switched on/off via a rasterization setting.

Added tests and a benchmark to compare with the current implementation in PyTorch - for some cases of large image size/faces per pixel the cuda version is 10x faster.

Reviewed By: gkioxari

Differential Revision: D21705503

fbshipit-source-id: e835c0f927f1e5088ca89020aef5ff27ac3a8769

Summary:
C++/CUDA implementation of forward and backward passes for the sigmoid alpha blending function.

This is slightly faster than the vectorized implementation in Python, but more importantly uses less memory due to fewer tensors being created.

Reviewed By: gkioxari

Differential Revision: D19980671

fbshipit-source-id: 0779055d2c68b1f20fb0870e60046077ef4613ff

Summary: R2N2 returns R2N2's own renderings of ShapeNetCore models.

Reviewed By: nikhilaravi

Differential Revision: D22266988

fbshipit-source-id: 36e67bd06c6459773e6e5f654259166b579be36a

Summary: Adding a render function for R2N2.

Reviewed By: nikhilaravi

Differential Revision: D22230228

fbshipit-source-id: a9f588ddcba15bb5d8be1401f68d730e810b4251

Summary: Skeleton of R2N2 that for now only returns verts and faces extracted from ShapeNetCore v1.

Reviewed By: nikhilaravi

Differential Revision: D22203656

fbshipit-source-id: 00db6ac76bfdb76fdbc77a2087c34a3f0ff01e6a

Summary: Adding collate_batched_meshes for datasets.utils: takes in a list of dictionaries and merge them into one dictionary (while adding a merged mesh to the dictionary).

Reviewed By: nikhilaravi

Differential Revision: D22180404

fbshipit-source-id: f811f9a140f09638f355ad5739bffa6ee415819f

Summary: Additional functionality for renderer in ShapeNetCore: users can select which objects to render by specifying their model_ids, or users could choose to render several random objects in some categories, or users could specify indices of the objects in the loaded dataset. (currently doesn't support changing lighting, still investigating why lighting is causing instability in renderings)

Reviewed By: nikhilaravi

Differential Revision: D22179594

fbshipit-source-id: 74c49094ffa3ea2eb71de9451f9e5da5053d356d

Summary: Adding a renderer to ShapeNetCore (Note that the lights are currently turned off for the test; will investigate why lighting causes instability in rendering)

Reviewed By: nikhilaravi

Differential Revision: D22102673

fbshipit-source-id: a704756a1e93b61d5a879f0e5ee14ebcb0df49d7

Differential Revision: D22519468

fbshipit-source-id: 6e39c2e50ef95f37df407dbc6d186cc97832fc7d

Summary: When rendering meshes with Phong shading, interpolate_face_attributes was taking up a nontrivial fraction of the overall shading time. This diff replaces our Python implementation of this function with a CUDA implementation.

Reviewed By: nikhilaravi

Differential Revision: D21610763

fbshipit-source-id: 2bb362a28f698541812aeab539047264b125ebb8

Summary: Make the `_open_file()` function return a context manager and remove the associated file closure

Reviewed By: nikhilaravi

Differential Revision: D20720506

fbshipit-source-id: 7d96ceb2fd64b6ee3985d0b0faf8d8bf791b1966

Summary: Finish extracting _open_file() to a separate utils module (started with D20754859 (https://github.com/facebookresearch/pytorch3d/commit/c9267ab7af0f72217a1ee1a0b37941a5c8fdb325) / previous version of this diff).

Reviewed By: nikhilaravi

Differential Revision: D20720344

fbshipit-source-id: 77ef201ff37a8f2a0cd19be162cb97ee99480158

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