Summary:
Introduce methods to approximate the radii of conical frustums along rays as described in [MipNerf](https://arxiv.org/abs/2103.13415):
- Two new attributes are added to ImplicitronRayBundle: bins and radii. Bins is of size n_pts_per_ray + 1. It allows us to manipulate easily and n_pts_per_ray intervals. For example we need the intervals coordinates in the radii computation for \(t_{\mu}, t_{\delta}\). Radii are used to store the radii of the conical frustums.
- Add 3 new methods to compute the radii:
- approximate_conical_frustum_as_gaussians: It computes the mean along the ray direction, the variance of the
conical frustum with respect to t and variance of the conical frustum with respect to its radius. This
implementation follows the stable computation defined in the paper.
- compute_3d_diagonal_covariance_gaussian: Will leverage the two previously computed variances to find the
diagonal covariance of the Gaussian.
- conical_frustum_to_gaussian: Mix everything together to compute the means and the diagonal covariances along
the ray of the Gaussians.
- In AbstractMaskRaySampler, introduces the attribute `cast_ray_bundle_as_cone`. If False it won't change the previous behaviour of the RaySampler. However if True, the samplers will sample `n_pts_per_ray +1` instead of `n_pts_per_ray`. This points are then used to set the bins attribute of ImplicitronRayBundle. The support of HeterogeneousRayBundle has not been added since the current code does not allow it. A safeguard has been added to avoid a silent bug in the future.
Reviewed By: shapovalov
Differential Revision: D45269190
fbshipit-source-id: bf22fad12d71d55392f054e3f680013aa0d59b78
Summary: Making it easier for the clients to use these datasets.
Reviewed By: bottler
Differential Revision: D46727179
fbshipit-source-id: cf619aee4c4c0222a74b30ea590cf37f08f014cc
Summary:
Moving SQL dataset to PyTorch3D. It has been extensively tested in pixar_replay.
It requires SQLAlchemy 2.0, which is not supported in fbcode. So I exclude the sources and tests that depend on it from buck TARGETS.
Reviewed By: bottler
Differential Revision: D45086611
fbshipit-source-id: 0285f03e5824c0478c70ad13731525bb5ec7deef
Summary:
Allows loading of multiple categories.
Multiple categories are provided in a comma-separated list of category names.
Reviewed By: bottler, shapovalov
Differential Revision: D40803297
fbshipit-source-id: 863938be3aa6ffefe9e563aede4a2e9e66aeeaa8
Summary:
Changed ray_sampler and metrics to be able to use mixed frame raysampling.
Ray_sampler now has a new member which it passes to the pytorch3d raysampler.
If the raybundle is heterogeneous metrics now samples images by padding xys first. This reduces memory consumption.
Reviewed By: bottler, kjchalup
Differential Revision: D39542221
fbshipit-source-id: a6fec23838d3049ae5c2fd2e1f641c46c7c927e3
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: 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:
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:
Added _NEED_CONTROL
to JsonIndexDatasetMapProviderV2 and made dataset_tweak_args use it.
Reviewed By: bottler
Differential Revision: D38313914
fbshipit-source-id: 529847571065dfba995b609a66737bd91e002cfe
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: A new version of json index dataset provider supporting CO3Dv2
Reviewed By: shapovalov
Differential Revision: D37690918
fbshipit-source-id: bf2d5fc9d0f1220259e08661dafc69cdbe6b7f94
Summary:
Make ViewMetrics easy to replace by putting them into an OmegaConf dataclass.
Also, re-word a few variable names and fix minor TODOs.
Reviewed By: bottler
Differential Revision: D37327157
fbshipit-source-id: 78d8e39bbb3548b952f10abbe05688409fb987cc
Summary: Allow specifying a color for non-opaque pixels in LSTMRenderer.
Reviewed By: davnov134
Differential Revision: D37172537
fbshipit-source-id: 6039726678bb7947f7d8cd04035b5023b2d5398c
Summary: Copy code from NeRF for loading LLFF data and blender synthetic data, and create dataset objects for them
Reviewed By: shapovalov
Differential Revision: D35581039
fbshipit-source-id: af7a6f3e9a42499700693381b5b147c991f57e5d
Summary: Make dataset type and args configurable on JsonIndexDatasetMapProvider.
Reviewed By: davnov134
Differential Revision: D36666705
fbshipit-source-id: 4d0a3781d9a956504f51f1c7134c04edf1eb2846
Summary: replace dataset_zoo with a pluggable DatasetMapProvider. The logic is now in annotated_file_dataset_map_provider.
Reviewed By: shapovalov
Differential Revision: D36443965
fbshipit-source-id: 9087649802810055e150b2fbfcc3c197a761f28a
Summary: Make ResNetFeatureExtractor be an implementation of FeatureExtractorBase.
Reviewed By: davnov134
Differential Revision: D35433098
fbshipit-source-id: 0664a9166a88e150231cfe2eceba017ae55aed3a
Summary: Implements a ViewPooler that groups ViewSampler and FeatureAggregator.
Reviewed By: shapovalov
Differential Revision: D35852367
fbshipit-source-id: c1bcaf5a1f826ff94efce53aa5836121ad9c50ec
