- 04 Jan, 2022 1 commit
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Jeremy Reizenstein authored
Summary: Update all FB license strings to the new format. Reviewed By: patricklabatut Differential Revision: D33403538 fbshipit-source-id: 97a4596c5c888f3c54f44456dc07e718a387a02c
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- 15 Sep, 2021 1 commit
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Nikhila Ravi authored
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
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- 22 Jun, 2021 1 commit
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Patrick Labatut authored
Summary: License lint codebase Reviewed By: theschnitz Differential Revision: D29001799 fbshipit-source-id: 5c59869911785b0181b1663bbf430bc8b7fb2909
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- 06 Apr, 2020 1 commit
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Jeremy Reizenstein authored
Summary: lint clean again Reviewed By: patricklabatut Differential Revision: D20868775 fbshipit-source-id: ade4301c1012c5c6943186432465215701d635a9
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- 03 Apr, 2020 1 commit
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Roman Shapovalov authored
Summary: 1. Introduced weights to Umeyama implementation. This will be needed for weighted ePnP but is useful on its own. 2. Refactored to use the same code for the Pointclouds mask and passed weights. 3. Added test cases with random weights. 4. Fixed a bug in tests that calls the function with 0 points (fails randomly in Pytorch 1.3, will be fixed in the next release: https://github.com/pytorch/pytorch/issues/31421 ). Reviewed By: gkioxari Differential Revision: D20070293 fbshipit-source-id: e9f549507ef6dcaa0688a0f17342e6d7a9a4336c
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