GitLab

Summary: If we are not visualizing the training with visdom, then there are a couple of outputs of the coarse rendering step which are not small and are returned by the renderer but never used. We don't need to bother transferring them to the CPU.

Reviewed By: nikhilaravi

Differential Revision: D28939958

fbshipit-source-id: 7e0d6681d6524f7fb57b6b20164580006120de80

Summary:
All classes implicitly inherit from `object` since Python 3, so remove unnecessary explicit inheritance.

From the [official documentation](https://docs.python.org/3/library/functions.html#object):

> `object` is a base for all classes.

Reviewed By: nikhilaravi

Differential Revision: D28942595

fbshipit-source-id: 466c0d19d8a93a6263e7ad734c3e87160cfa6066

Summary:
Inside the implicit function, the color and density calculations are independent and time is saved by putting them on separate streams.

(In fact, colors is slower than densities, and the raymarcher does some calculation with the densities before the colors. So theoretically we could go further and not join the streams together until the colors are actually needed. The code would be more complicated. But the profile suggests that the raymarcher is quick and so this wouldn't be expected to make a big difference.)

In inference, this might increase memory usage, so it isn't an obvious win. That is why I have added a flag.

Reviewed By: nikhilaravi

Differential Revision: D28648549

fbshipit-source-id: c087de80d8ccfce1dad3a13e71df2f305a36952e

Summary: When harmonic embedding is used, we always cat its input onto its output before proceeding. Avoid an intermediate tensor by making the module do that for itself.

Reviewed By: davnov134

Differential Revision: D28185791

fbshipit-source-id: 98d92c94a918dd42e16cdadcaac71dabbc7de5c3

Summary:
Add custom layer to avoid repeating copied data for every ray position.

This should also save time in the backward pass because there are fewer multiplies with the weights.

Reviewed By: theschnitz

Differential Revision: D28382412

fbshipit-source-id: 1ba7356cd8520ebd598568ae503e47d31d3989eb

Summary: Add gitignore file to ignore data and checkpoints in the NeRF project.

Reviewed By: nikhilaravi

Differential Revision: D28382413

fbshipit-source-id: 747d69f4353a76a28acde8ba26a896cb2278f976

Summary: We don't use gradents of sample_pdf. Here we disable gradient calculation around calling it, instead of calling detach later. There's a theoretical speedup, but mainly this enables using sample_pdf implementations which don't support gradients.

Reviewed By: nikhilaravi

Differential Revision: D28057284

fbshipit-source-id: 8a9d5e73f18b34e1e4291028008e02973023638d

Summary: See title.

Reviewed By: nikhilaravi

Differential Revision: D27658290

fbshipit-source-id: 232550f04df4951f7f3d712047b39e510a2f4209

Summary: Collection of spelling things, mostly in docs / tutorials.

Reviewed By: gkioxari

Differential Revision: D26101323

fbshipit-source-id: 652f62bc9d71a4ff872efa21141225e43191353a

Summary:
Fixes mostly related to the "main" build on circleci.
-Avoid error to do with tuple copy from initializer_list which is `explicit` on old compiler.
-Add better reporting to copyright test.
-Move to PackedTensorAccessor64 from the deprecated PackedTensorAccessor
-Avoid some warnings about mismatched comparisons.

The "main" build is the only one that runs the test_build stuff. In that area
-Fix my bad copyright fix D26275931 (https://github.com/facebookresearch/pytorch3d/commit/3463f418b8a3e3c3e6b6a20007b38eb71938ec7f) / 965c9c
-Add test that all tutorials are valid json.

Reviewed By: nikhilaravi

Differential Revision: D26366466

fbshipit-source-id: c4ab8b7e6647987069f7cb7144aa6ab7c24bcdac

Summary: Fix missing copyright header in __init__.py file.

Reviewed By: davnov134

Differential Revision: D26275931

fbshipit-source-id: 965c9cf17383aa27d35d549754ebd99ae7c25f47

Summary: Fixes to Readme in NeRF

Reviewed By: nikhilaravi

Differential Revision: D26205882

fbshipit-source-id: 73e4d727f6e6c96fa7af7d2b917acdeaf990091c

Summary: Adds the readme file.

Reviewed By: nikhilaravi

Differential Revision: D25684459

fbshipit-source-id: f1aaa621a2a67c98d5fcfe33fe9bbfea8f95b537

Summary: Implements the test script of NeRF.

Reviewed By: nikhilaravi

Differential Revision: D25684450

fbshipit-source-id: 739169d9df706795814912bb9a15e2e65ac92df8

Summary: Implements methods for generating trajectories of test cameras.

Reviewed By: nikhilaravi

Differential Revision: D26100869

fbshipit-source-id: cf2b61a34d4c749cd8cba881e97f6c388e57d1f8

Summary: Implements the training script of NeRF.

Reviewed By: nikhilaravi

Differential Revision: D25684439

fbshipit-source-id: 8b19b6dc282eb6bf6e46ec4476bb0f13a84c90dd

Summary: Implements the `Stats` class that handles logging of the training statistics.

Reviewed By: nikhilaravi

Differential Revision: D25684430

fbshipit-source-id: 920a1c65917ab5d047988494d92173da60cfd64b

Summary: Implements the dataloader for NeRF.

Reviewed By: nikhilaravi

Differential Revision: D25684424

fbshipit-source-id: 4f7092ce23135bd418186833a087e243433babc7

Summary: Implements the main NeRF model class that controls the radiance field and its renderer

Reviewed By: nikhilaravi

Differential Revision: D25684419

fbshipit-source-id: fae45572daa6748c6234bd212f3e68110f778238

Summary: Implements the radiance field function of NeRF

Reviewed By: nikhilaravi

Differential Revision: D25684413

fbshipit-source-id: 4bf6dd5d22e6134a09f7b9f314536ec16670f737

Summary: Implements the positional embedding of NeRF

Reviewed By: nikhilaravi

Differential Revision: D25684406

fbshipit-source-id: 9f3b657babacff48bd6a0497d7a859607ffa5f89

Summary: Implements the NeRF raysampler.

Reviewed By: nikhilaravi

Differential Revision: D25684403

fbshipit-source-id: 616a60f047c79479f60a6a75d214f87cbfb06d28

Summary: An initial NeRF diff which sets up the folder structure and implements the raymarching algorithm of NeRF.

Reviewed By: nikhilaravi

Differential Revision: D25623990

fbshipit-source-id: ac6b05a9b866358bd4bbf44858f06859d8a6ebd1