GitLab

Differential Revision: D28962863

fbshipit-source-id: 7acc8e2f08ea7a94294647431561ff2cfd52a97d

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:
One test hits problems with CUDA 11.1 and pytorch 1.8. This seems to be a known bug, so we just run that test on the cpu in the problematic cases.

Note - the full test run is much slower with cuda 11.1 than 10.2, but this is known.

Reviewed By: patricklabatut

Differential Revision: D28938933

fbshipit-source-id: cf8ed84cd10a0b52d8f4292edbef7bd4844fea65

Summary: Improve type annotations for textures and remove a few pyre fixmes

Reviewed By: nikhilaravi

Differential Revision: D28942630

fbshipit-source-id: 422f2bdf07b435869461ca103d71473aa0c2b814

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: Remove extra pyre fixmes

Reviewed By: bottler

Differential Revision: D28929468

fbshipit-source-id: 175b7986d49b56de7af063e97a9b0423570f9093

Summary: Restore assertNormsClose's printing of its message on failure which I broke in D26233419 (https://github.com/facebookresearch/pytorch3d/commit/cd9786e787386c185ef915b3983c5d2861a32907).

Reviewed By: nikhilaravi

Differential Revision: D28799743

fbshipit-source-id: e7a24b2558b68991c731bbd55fb3ca6c1df98f69

Summary: make assertClose print its failure information even if a message is supplied.

Reviewed By: nikhilaravi

Differential Revision: D28799745

fbshipit-source-id: 787c8c356342420cd8f40fdc0b2aba036142298e

Summary:
Caught a silly typo in the docs, figured I'd send in a PR. Thanks for sharing your work!

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/693

Reviewed By: bottler

Differential Revision: D28837851

Pulled By: patricklabatut

fbshipit-source-id: c326189007c3537429a8aa2a3b2850d60b74b16d

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

Differential Revision: D28766465

fbshipit-source-id: 9c5b123ac279e25965ebc8827d9a947bbb6f3ac5

Summary:
The multiplicative factors in function embeddings go from `2**0` to `2**(self.n_harmonic_functions-1)`, and not from `2**0` to `2**self.n_harmonic_functions`.

Pull Request resolved: https://github.com/fairinternal/pytorch3d/pull/13

Reviewed By: nikhilaravi

Differential Revision: D28637894

Pulled By: ignacio-rocco

fbshipit-source-id: da20f39eba9aaa09af5b24be1554a3bfd7556281

Summary: Experimental data loader for taking the default scene from a GLB file and converting it to a single mesh in PyTorch3D.

Reviewed By: nikhilaravi

Differential Revision: D25900167

fbshipit-source-id: bff22ac00298b83a0bd071ae5c8923561e1d81d7

Summary:
Specific object to represent light which is 100% everywhere. Sometimes lighting is irrelevant, for example when viewing a mesh which has lighting already baked in.

This is not primarily aiming for a performance win but I think the test which has changed might be a bit faster.

Reviewed By: theschnitz

Differential Revision: D26405151

fbshipit-source-id: 82eae55de0bee918548a3eaf031b002cb95e726c

Summary: Function to relatively rotate a camera position. Also document how to relatively translate a camera position.

Reviewed By: theschnitz

Differential Revision: D25900166

fbshipit-source-id: 2ddaf06ee7c5e2a2e973c04d7dee6ccb61c6ff84

Summary:
If you join several meshes which have TexturesUV textures using join_meshes_as_scene then we amalgamate all the texture images in to a single one. This now checks if some of the images are equal (i.e. the tensors are the same tensor, in the `is` sense; they have the same `id` in Python) and only uses one copy if they are.

I have an example of a massive scene made of several textured meshes with some shared, where this makes the difference between fitting the data on the GPU and not.

Reviewed By: theschnitz

Differential Revision: D25982364

fbshipit-source-id: a8228805f38475c796302e27328a340d9b56c8ef

Summary: Currently the Rotate transform does not consider the R's device at all, resulting in errors if you're expecting it to be on cuda but it gets the default casting to cpu. This updates the transform to respect R's device.

Reviewed By: nikhilaravi

Differential Revision: D27828118

fbshipit-source-id: ddd99f73eadbd990688eb22f3d1ffbacbe168c81

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

Reviewed By: nikhilaravi

Differential Revision: D28382413

fbshipit-source-id: 747d69f4353a76a28acde8ba26a896cb2278f976

Summary: Avoid test files explicitly importing TestCase objects from each other, because doing so causes the tests to be discovered twice by unittest discover. This means moving a few static functions out of their classes. I noticed this while trying to fix failures from yesterday.

Reviewed By: nikhilaravi

Differential Revision: D28194679

fbshipit-source-id: ac6e6585603bd4ef9c098cdd56891d94f8923ba6

Summary:
A couple of tests are failing in open source after my changes yesterday because of numerical issues calculating normals. In particular we have meshes with very few vertices and several faces, where the normals should be zero but end up non-negligible after F.normalize. I have no idea why the different environments produce different results, so that the tests are passing internally.

An example. Consider a mesh with the following faces:
```
tensor([[4, 0, 2],
        [4, 1, 2],
        [3, 1, 0],
        [1, 3, 1],
        [3, 0, 1],
        [4, 0, 0],
        [4, 0, 2]])
```
At vertex 3, there is one zero-area face and there are two other faces, which are back-to-back with each other. This vertex should have zero normal. The open source calculation produces a small but nonzero normal which varies unpredictably with changes in scale/offset, which can cause test failures.

In this diff, the main change is to increase the number of vertices to make this less likely to happen. Also a small change to init_mesh to make it not generate a batch of empty meshes.

Reviewed By: nikhilaravi

Differential Revision: D28220984

fbshipit-source-id: 79fdc62e5f5f8836de5a3a9980cfd6fe44590359

Summary:
Allow a line like `OFF10 10 10` as the start of an OFF file. Such things apparently occur in ModelNet40.

This resolves https://github.com/facebookresearch/pytorch3d/issues/663.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/665

Test Plan: New test

Reviewed By: nikhilaravi

Differential Revision: D28180006

Pulled By: bottler

fbshipit-source-id: 7f474c6a262e32da012217e09f76e8672a7f0278

Summary: 3 extend functions in textures.py updated to call `self.__class__` rather than create a new object of its type. As mentioned in https://github.com/facebookresearch/pytorch3d/issues/618 .

Reviewed By: bottler

Differential Revision: D28281218

fbshipit-source-id: b9c99ab87e46a3f28c37efa1ee2c2dceb560b491

Summary:
Several tutorials were importing skimage and not using it (and it is not an official dependency of PyTorch3D).

Also several had a bad call to plt.grid.

Reviewed By: nikhilaravi

Differential Revision: D28185822

fbshipit-source-id: adabfd0d4d339e1081c26b7b28f5e3953b492f2e

Summary: Add ability to load normals when they are present in a PLY file.

Reviewed By: nikhilaravi

Differential Revision: D26458971

fbshipit-source-id: 658270b611f7624eab4f5f62ff438038e1d25723

Summary: Save existing vertex normals when a mesh is saved to PLY, and existing normals when a point cloud is saved to PLY.

Reviewed By: theschnitz

Differential Revision: D27765257

fbshipit-source-id: fa0aae4c0f100f7e5eb742f48fc3dfc87435deba

Summary: Add ability to ask a Meshes if it already has normals. If it does, then requesting normals will not trigger a calculation. MeshesFormatInterpreters will therefore be able to decide whether to save normals.

Reviewed By: theschnitz, nikhilaravi

Differential Revision: D27765261

fbshipit-source-id: 7c87dbf999d5616d20f5eb2c01039ee5ff65a830

Summary: Add ability to set the vertex normals when creating a Meshes, so that the pluggable loaders can return them from a file.

Reviewed By: nikhilaravi

Differential Revision: D27765258

fbshipit-source-id: b5ddaa00de3707f636f94d9f74d1da12ecce0608

Summary: If offset_verts_ is used to move meshes with a single vector, the normals won't change so don't need to recalculate. I am planning to allow user-specified vertex normals. This change means that user-specified vertex normals won't get overwritten when they don't need to be.

Reviewed By: nikhilaravi

Differential Revision: D27765256

fbshipit-source-id: f6e4d308ac9ac023030325cb75a18d39b966cf88

Summary:
There is no need to recalculate normals when scaling a mesh by a constant. We omit doing this for vertex normals. This will make things less confusing when we allow user-specified vertex normals.

Face normals also don't need recalculating, but they are calculated at the same time as face areas which do, so it is easiest not to change their behavior here. That is convenient because we are not immediately planning to allow user-specified face normals.

Reviewed By: nikhilaravi

Differential Revision: D27793476

fbshipit-source-id: 827f1be4bc78bf0391ce3959cce48c4f3ee326fe

Summary: When a PLY file contains colors in byte format, these are now scaled from 0..255 to [0,1], as they should be

Reviewed By: gkioxari

Differential Revision: D27765254

fbshipit-source-id: 526b5f5149d5e8cbffd7412b411be52c935fa4ad

Summary:
Include TexturesVertex colors when loading and saving Meshes to PLY files.

A couple of other improvements to the internals of ply_io, including using `None` instead of empty tensors for some missing data.

Reviewed By: gkioxari

Differential Revision: D27765260

fbshipit-source-id: b9857dc777c244b9d7d6643b608596d31435ecda

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: As remarked in #655, we need to specify the fvcore channel before conda-forge, because there is now an fvcore on conda-forge which we don't aim to use. Compare D27589827

Reviewed By: nikhilaravi

Differential Revision: D27938996

fbshipit-source-id: 8abf7994a26e0ea9e6a19fb1e246aba7af091ddc

Summary: We can check the bounds without using extra memory. This produces a small speedup in NeRF training (like 0.5%).

Reviewed By: nikhilaravi

Differential Revision: D27859691

fbshipit-source-id: d566420c465f51231f4a57438084c98b73253046

Differential Revision: D27934268

fbshipit-source-id: 51185fa493451012a9b2fd37379897d60596f73b

Summary:
When a list of Meshes is `join_batched()`, the `num_verts_per_mesh` in the list would be unexpectedly modified.

Also some cleanup around `_num_verts_per_mesh`.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/623

Test Plan: A modification to an existing test checks this.

Reviewed By: nikhilaravi

Differential Revision: D27682104

Pulled By: bottler

fbshipit-source-id: 9d00913dfb4869bd6c7d3f5cc9156b7b6f1aecc9

Reviewed By: divchenko

Differential Revision: D27835360

fbshipit-source-id: cbb23793ee57382e43bd65bd40cfeb2820c6eec2

Summary: The renderer gets used for visualization only in places. Here we avoid creating an autograd graph during that, which is not needed and can fail because some of the graph which existed earlier might be needed and has not been retained after the optimizer step. See https://github.com/facebookresearch/pytorch3d/issues/624

Reviewed By: gkioxari

Differential Revision: D27593018

fbshipit-source-id: 62ae7a5a790111273aa4c566f172abd36c844bfb