GitLab

Summary:
Benchmarking. We only use num_faces=2 for splatter, because as far as I can see one would never need to use more. Pose optimization and mesh optimization experiments (see next two diffs) showed that Splatter with 2 faces beats Softmax with 50 and 100 faces in terms of accuracy.

Results: We're slower at 64px^2. At 128px and 256px, we're slower than Softmax+50faces, but faster than Softmax+100faces. We're also slower at 10 faces/pix, but expectation as well as results show that more then 2 faces shouldn't be necessary. See also more results in .https://fburl.com/gdoc/ttv7u7hp

Reviewed By: jcjohnson

Differential Revision: D36210575

fbshipit-source-id: c8de28c8a59ce5fe21a47263bd43d2757b15d123

Summary: Update all FB license strings to the new format.

Reviewed By: patricklabatut

Differential Revision: D33403538

fbshipit-source-id: 97a4596c5c888f3c54f44456dc07e718a387a02c

Summary: Move benchmarks to a separate directory as tests/ is getting big.

Reviewed By: nikhilaravi

Differential Revision: D32885462

fbshipit-source-id: a832662a494ee341ab77d95493c95b0af0a83f43

Summary: License lint codebase

Reviewed By: theschnitz

Differential Revision: D29001799

fbshipit-source-id: 5c59869911785b0181b1663bbf430bc8b7fb2909

Summary:
This diff integrates the pulsar renderer source code into PyTorch3D as an alternative backend for the PyTorch3D point renderer. This diff is the first of a series of three diffs to complete that migration and focuses on the packaging and integration of the source code.

For more information about the pulsar backend, see the release notes and the paper (https://arxiv.org/abs/2004.07484). For information on how to use the backend, see the point cloud rendering notebook and the examples in the folder `docs/examples`.

Tasks addressed in the following diffs:
* Add the PyTorch3D interface,
* Add notebook examples and documentation (or adapt the existing ones to feature both interfaces).

Reviewed By: nikhilaravi

Differential Revision: D23947736

fbshipit-source-id: a5e77b53e6750334db22aefa89b4c079cda1b443

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: Address black + isort fbsource linter warnings from D20558374 (previous diff)

Reviewed By: nikhilaravi

Differential Revision: D20558373

fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8

Summary: Ensure copyright header consistency and translation unit name uniqueness.

Reviewed By: nikhilaravi

Differential Revision: D20438802

fbshipit-source-id: 9820cfe4c6efab016a0a8589dfa24bb526692f83

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

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