7 Commits

Author SHA1 Message Date
Jeremy Reizenstein
34f648ede0 move targets
Summary: Move testing targets from pytorch3d/tests/TARGETS to pytorch3d/TARGETS.

Reviewed By: shapovalov

Differential Revision: D36186940

fbshipit-source-id: a4c52c4d99351f885e2b0bf870532d530324039b
2022-05-25 06:16:03 -07:00
Jeremy Reizenstein
9eeb456e82 Update license for company name
Summary: Update all FB license strings to the new format.

Reviewed By: patricklabatut

Differential Revision: D33403538

fbshipit-source-id: 97a4596c5c888f3c54f44456dc07e718a387a02c
2022-01-04 11:43:38 -08:00
Patrick Labatut
af93f34834 License lint codebase
Summary: License lint codebase

Reviewed By: theschnitz

Differential Revision: D29001799

fbshipit-source-id: 5c59869911785b0181b1663bbf430bc8b7fb2909
2021-06-22 03:45:27 -07:00
Roman Shapovalov
cdaac5f9c5 Bumping the threshold to allow leeway for CI testing randomness.
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
2020-07-16 10:19:43 -07:00
David Novotny
daf9eac801 Efficient PnP weighting bug fix
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
2020-07-09 06:40:38 -07:00
Roman Shapovalov
a8377f1f06 Numerical stability of ePnP.
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
2020-05-15 01:36:21 -07:00
Roman Shapovalov
04d8bf6a43 Efficient PnP.
Summary:
Efficient PnP algorithm to fit 2D to 3D correspondences under perspective assumption.

Benchmarked both variants of nullspace and pick one; SVD takes 7 times longer in the 100K points case.

Reviewed By: davnov134, gkioxari

Differential Revision: D20095754

fbshipit-source-id: 2b4519729630e6373820880272f674829eaed073
2020-04-17 07:44:16 -07:00