GitLab

Summary:
1) Update rasterizer/point rasterizer to accommodate fisheyecamera. Specifically, transform_points is in placement of explicit transform compositions.

2) In rasterizer unittests, update corresponding tests for rasterizer and point_rasterizer. Address comments to test fisheye against perspective camera when distortions are turned off.

3) Address comments to add end2end test for fisheyecameras. In test_render_meshes, fisheyecameras are added to camera enuerations whenever possible.

4) Test renderings with fisheyecameras of different params on cow mesh.

5) Use compositions for linear cameras whenever possible.

Reviewed By: kjchalup

Differential Revision: D38932736

fbshipit-source-id: 5b7074fc001f2390f4cf43c7267a8b37fd987547

Summary:
Amend FisheyeCamera by adding tests for all
combination of params and for different batch_sizes.

Reviewed By: kjchalup

Differential Revision: D39176747

fbshipit-source-id: 830d30da24beeb2f0df52db0b17a4303ed53b59c

Summary: Remove the compat functions eigh, solve, lstsq, and qr. Migrate callers to use torch.linalg directly.

Reviewed By: bottler

Differential Revision: D39172949

fbshipit-source-id: 484230a553237808f06ee5cdfde64651cba91c4c

Summary: A dummy value in test_opengl_utils seems to be able to break tests in test_mesh_renderer_opengl{,_to}.

Reviewed By: kjchalup

Differential Revision: D39173275

fbshipit-source-id: 83b15159f70135ea575d5085c7b6b37badd6e49e

Summary: Address comments to add benchmarkings for cameras and the new fisheye cameras. The dependency functions in test_cameras have been updated in Diff 1. The following two snapshots show benchmarking results.

Reviewed By: kjchalup

Differential Revision: D38991914

fbshipit-source-id: 51fe9bb7237543e4ee112c9f5068a4cf12a9d482

Summary:
1. A Fisheye camera model that generalizes pinhole camera by considering distortions (i.e. radial, tangential and thin-prism distortions).

2. Added tests against perspective cameras when distortions are off and Aria data points when distortions are on.

3. Address comments to test unhandled shapes between points and transforms. Added tests for __FIELDS, shape broadcasts, cuda etc.

4. Address earlier comments for code efficiency (e.g., adopted torch.norm; torch.solve for matrix inverse; removed inplace operations; unnecessary clone; expand in place of repeat etc).

Reviewed By: jcjohnson

Differential Revision: D38407094

fbshipit-source-id: a3ab48c85c496ac87af692d5d461bb3fc2a2db13

Summary: Added replacable decoding functions which will be applied after the voxel grid to get color and density

Reviewed By: bottler

Differential Revision: D38829763

fbshipit-source-id: f21ce206c1c19548206ea2ce97d7ebea3de30a23

Summary: Simple wrapper around voxel grids to make them a module

Reviewed By: bottler

Differential Revision: D38829762

fbshipit-source-id: dfee85088fa3c65e396cc7d3bf7ebaaffaadb646

Summary: Added voxel grid classes from TensoRF, both in their factorized (CP and VM) and full form.

Reviewed By: bottler

Differential Revision: D38465419

fbshipit-source-id: 8b306338af58dc50ef47a682616022a0512c0047

Summary: Fix EPS issue that causes numerical instabilities when boxes are very close

Reviewed By: kjchalup

Differential Revision: D38661465

fbshipit-source-id: d2b6753cba9dc2f0072ace5289c9aa815a1a29f6

Summary: Split Volumes class to data and location part so that location part can be reused in planned VoxelGrid classes.

Reviewed By: bottler

Differential Revision: D38782015

fbshipit-source-id: 489da09c5c236f3b81961ce9b09edbd97afaa7c8

Summary:
generic_model_args no longer exists. Update some references to it, mostly in doc.

This fixes the testing of all the yaml files in test_forward pass.

Reviewed By: shapovalov

Differential Revision: D38789202

fbshipit-source-id: f11417efe772d7f86368b3598aa66c52b1309dbf

Reviewed By: shapovalov

Differential Revision: D38794764

fbshipit-source-id: 140c8a935d760bab8569d903cc52ac3dd73cd553

Summary: Reasonable to expect bool indexing.

Reviewed By: bottler, kjchalup

Differential Revision: D38741446

fbshipit-source-id: 22b607bf13110043c5624196c66ca1484fdbce6c

Summary: Previously, "psnr" was evaluated between the masked g.t. image and the render. To avoid confusion, "psnr" is now renamed to "psnr_masked".

Reviewed By: bottler

Differential Revision: D38707511

fbshipit-source-id: 8ee881ab1a05453d6692dde9782333a47d8c1234

Summary: Adds additional source views to the eval batches for evaluating many-view models on CO3D Challenge

Reviewed By: bottler

Differential Revision: D38705904

fbshipit-source-id: cf7d00dc7db926fbd1656dd97a729674e9ff5adb

Summary: Reports also the PSNR between the unmasked G.T. image and the render.

Reviewed By: bottler

Differential Revision: D38655943

fbshipit-source-id: 1603a2d02116ea1ce037e5530abe1afc65a2ba93

Summary:
LLFF (and most/all non-synth datasets) will have no background/foreground distinction. Add support for data with no fg mask.

Also, we had a bug in stats loading, like this:
  * Load stats
  * One of the stats has a history of length 0
  * That's fine, e.g. maybe it's fg_error but the dataset has no notion of fg/bg. So leave it as len 0
  * Check whether all the stats have the same history length as an arbitrarily chosen "reference-stat"
  * Ooops the reference-stat happened to be the stat with length 0
  * assert (legit_stat_len == reference_stat_len (=0)) ---> failed assert

Also some minor fixes (from Jeremy's other diff) to support LLFF

Reviewed By: davnov134

Differential Revision: D38475272

fbshipit-source-id: 5b35ac86d1d5239759f537621f41a3aa4eb3bd68

Summary: remove n_instances==0 special case, standardise args for GlobalEncoderBase's forward.

Reviewed By: shapovalov

Differential Revision: D37817340

fbshipit-source-id: 0aac5fbc7c336d09be9d412cffff5712bda27290

Summary: continued - avoid duplicate inputs

Reviewed By: davnov134

Differential Revision: D38248827

fbshipit-source-id: 91ed398e304496a936f66e7a70ab3d189eeb5c70

Summary: Don't copy from one part of config to another, rather do the copy within GenericModel.

Reviewed By: davnov134

Differential Revision: D38248828

fbshipit-source-id: ff8af985c37ea1f7df9e0aa0a45a58df34c3f893

Summary: Made the config system call open_dict when it calls the tweak function.

Reviewed By: shapovalov

Differential Revision: D38315334

fbshipit-source-id: 5924a92d8d0bf399bbf3788247f81fc990e265e7

Summary:
Stats are logically connected to the training loop, not to the model. Hence, moving to the training loop.

Also removing resume_epoch from OptimizerFactory in favor of a single place - ModelFactory. This removes the need for config consistency checks etc.

Reviewed By: kjchalup

Differential Revision: D38313475

fbshipit-source-id: a1d188a63e28459df381ff98ad8acdcdb14887b7

Summary: Simple DataLoaderMapProvider instance

Reviewed By: davnov134

Differential Revision: D38326719

fbshipit-source-id: 58556833e76fae5790d25a59bea0aac4ce046bf1

Summary:
Added _NEED_CONTROL
 to JsonIndexDatasetMapProviderV2 and made dataset_tweak_args use it.

Reviewed By: bottler

Differential Revision: D38313914

fbshipit-source-id: 529847571065dfba995b609a66737bd91e002cfe

Summary: Only import it if you ask for it.

Reviewed By: kjchalup

Differential Revision: D38327167

fbshipit-source-id: 3f05231f26eda582a63afc71b669996342b0c6f9

Summary: Make a dummy single-scene dataset using the code from generate_cow_renders (used in existing NeRF tutorials)

Reviewed By: kjchalup

Differential Revision: D38116910

fbshipit-source-id: 8db6df7098aa221c81d392e5cd21b0e67f65bd70

Summary:
This is an internal change in the config systen. It allows redefining a pluggable implementation with new default values. This is useful in notebooks / interactive use. For example, this now works.

        class A(ReplaceableBase):
            pass

        registry.register
        class B(A):
            i: int = 4

        class C(Configurable):
            a: A
            a_class_type: str = "B"

            def __post_init__(self):
                run_auto_creation(self)

        expand_args_fields(C)

        registry.register
        class B(A):
            i: int = 5

        c = C()

        assert c.a.i == 5

Reviewed By: shapovalov

Differential Revision: D38219371

fbshipit-source-id: 72911a9bd3426d3359cf8802cc016fc7f6d7713b

Summary:
Adding MeshRasterizerOpenGL, a faster alternative to MeshRasterizer. The new rasterizer follows the ideas from "Differentiable Surface Rendering via non-Differentiable Sampling".

The new rasterizer 20x faster on a 2M face mesh (try pose optimization on Nefertiti from https://www.cs.cmu.edu/~kmcrane/Projects/ModelRepository/!). The larger the mesh, the larger the speedup.

There are two main disadvantages:
* The new rasterizer works with an OpenGL backend, so requires pycuda.gl and pyopengl installed (though we avoided writing any C++ code, everything is in Python!)
* The new rasterizer is non-differentiable. However, you can still differentiate the rendering function if you use if with the new SplatterPhongShader which we recently added to PyTorch3D (see the original paper cited above).

Reviewed By: patricklabatut, jcjohnson

Differential Revision: D37698816

fbshipit-source-id: 54d120639d3cb001f096237807e54aced0acda25

Summary: Needed to properly change devices during OpenGL rasterization.

Reviewed By: jcjohnson

Differential Revision: D37698568

fbshipit-source-id: 38968149d577322e662d3b5d04880204b0a7be29

Summary:
EGLContext is a utility to render with OpenGL without an attached display (that is, without a monitor).

DeviceContextManager allows us to avoid unnecessary context creations and releases. See docstrings for more info.

Reviewed By: jcjohnson

Differential Revision: D36562551

fbshipit-source-id: eb0d2a2f85555ee110e203d435a44ad243281d2c

Summary: Avoid calculating all_train_cameras before it is needed, because it is slow in some datasets.

Reviewed By: shapovalov

Differential Revision: D38037157

fbshipit-source-id: 95461226655cde2626b680661951ab17ebb0ec75

Summary:
X-link: https://github.com/fairinternal/pytorch3d/pull/39

Blender and LLFF cameras were sending screen space focal length and principal point to a camera init function expecting NDC

Reviewed By: shapovalov

Differential Revision: D37788686

fbshipit-source-id: 2ddf7436248bc0d174eceb04c288b93858138582

Summary:
EPnP fails the test when the number of points is below 6. As suggested, quadratic option is in theory to deal with as few as 4 points (so num_pts_thresh=3 is set). And when num_pts > num_pts_thresh=4, skip_q is False.

To avoid bumping num_pts_thresh while passing all the original tests, check_output is set to False when num_pts < 6, similar to the logic in Line 123-127.  It makes sure that the algo doesn't crash.

Reviewed By: shapovalov

Differential Revision: D37804438

fbshipit-source-id: 74576d63a9553e25e3ec344677edb6912b5f9354

Summary: Fixing comments on D37592429 (https://github.com/facebookresearch/pytorch3d/commit/0dce883241ae638b9fa824f34fca9590d5f0782c)

Reviewed By: shapovalov

Differential Revision: D37752367

fbshipit-source-id: 40aa7ee4dc0c5b8b7a84a09d13a3933a9e3afedd

Summary:
This fixes a indexing bug in HardDepthShader and adds proper unit tests for both of the DepthShaders. This bug was introduced when updating the shader sizes and discovered when I switched my local model onto pytorch3d trunk instead of the patched copy.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1252

Test Plan:
Unit test + custom model code

```
pytest tests/test_shader.py
```

![image](https://user-images.githubusercontent.com/909104/178397456-f478d0e0-9f6c-467a-a85b-adb4c47adfee.png)

Reviewed By: bottler

Differential Revision: D37775767

Pulled By: d4l3k

fbshipit-source-id: 5f001903985976d7067d1fa0a3102d602790e3e8

renderer: add support for rendering high dimensional textures for classification/segmentation use cases (#1248)

Summary:
For 3D segmentation problems it's really useful to be able to train the models from multiple viewpoints using Pytorch3D as the renderer. Currently due to hardcoded assumptions in a few spots the mesh renderer only supports rendering RGB (3 dimensional) data. You can encode the classification information as 3 channel data but if you have more than 3 classes you're out of luck.

This relaxes the assumptions to make rendering semantic classes work with `HardFlatShader` and `AmbientLights` with no diffusion/specular. The other shaders/lights don't make any sense for classification since they mutate the texture values in some way.

This only requires changes in `Materials` and `AmbientLights`. The bulk of the code is the unit test.

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1248

Test Plan: Added unit test that renders a 5 dimensional texture and compare dimensions 2-5 to a stored picture.

Reviewed By: bottler

Differential Revision: D37764610

Pulled By: d4l3k

fbshipit-source-id: 031895724d9318a6f6bab5b31055bb3f438176a5

Summary: remove erroneous RandomDataLoaderMapProvider

Reviewed By: davnov134

Differential Revision: D37751116

fbshipit-source-id: cf3b555dc1e6304425914d1522b4f70407b498bf

Summary: A new version of json index dataset provider supporting CO3Dv2

Reviewed By: shapovalov

Differential Revision: D37690918

fbshipit-source-id: bf2d5fc9d0f1220259e08661dafc69cdbe6b7f94

Summary:
Implements several changes needed for the CO3Dv2 release:
- FrameData contains crop_bbox_xywh which defines the outline of the image crop corresponding to the image-shaped tensors in FrameData
- revised the definition of a bounding box inside JsonDatasetIndex: bbox_xyxy is [xmin, ymin, xmax, ymax], where xmax, ymax are not inclusive; bbox_xywh = [xmin, ymain, xmax-xmin, ymax-ymin]
- is_filtered for detecting whether the entries of the dataset were somehow filtered
- seq_frame_index_to_dataset_index allows to skip entries that are not present in the dataset

Reviewed By: shapovalov

Differential Revision: D37687547

fbshipit-source-id: 7842756b0517878cc0964fc0935d3c0769454d78