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:
We currently support caching bounding boxes in MaskAnnotation. If present, they are not re-computed from the mask. However, the masks need to be loaded for the bbox to be set.
This diff fixes that. Even if load_masks / load_blobs are unset, the bounding box can be picked up from the metadata.
Reviewed By: bottler
Differential Revision: D45144918
fbshipit-source-id: 8a2e2c115e96070b6fcdc29cbe57e1cee606ddcd
Summary: The code does not crash if depth map/mask are not given.
Reviewed By: bottler
Differential Revision: D45082985
fbshipit-source-id: 3610d8beb4ac897fbbe52f56a6dd012a6365b89b
Summary:
The pattern
```
X.Y if hasattr(X, "Y") else Z
```
can be replaced with
```
getattr(X, "Y", Z)
```
The [getattr](https://www.w3schools.com/python/ref_func_getattr.asp) function gives more succinct code than the [hasattr](https://www.w3schools.com/python/ref_func_hasattr.asp) function. Please use it when appropriate.
**This diff is very low risk. Green tests indicate that you can safely Accept & Ship.**
Reviewed By: bottler
Differential Revision: D44886893
fbshipit-source-id: 86ba23e837217e1ebd64bf8e27d286257894839e
Summary: Provide an extension point pre_expand to let a configurable class A make sure another class B is registered before A is expanded. This reduces top level imports.
Reviewed By: bottler
Differential Revision: D44504122
fbshipit-source-id: c418bebbe6d33862d239be592d9751378eee3a62
Summary:
Introduces the OverfitModel for NeRF-style training with overfitting to one scene.
It is a specific case of GenericModel. It has been disentangle to ease usage.
## General modification
1. Modularize a minimum GenericModel to introduce OverfitModel
2. Introduce OverfitModel and ensure through unit testing that it behaves like GenericModel.
## Modularization
The following methods have been extracted from GenericModel to allow modularity with ManyViewModel:
- get_objective is now a call to weighted_sum_losses
- log_loss_weights
- prepare_inputs
The generic methods have been moved to an utils.py file.
Simplify the code to introduce OverfitModel.
Private methods like chunk_generator are now public and can now be used by ManyViewModel.
Reviewed By: shapovalov
Differential Revision: D43771992
fbshipit-source-id: 6102aeb21c7fdd56aa2ff9cd1dd23fd9fbf26315
Summary: For safety checks, make inplace forward operations in cuda and c++ call increment_version.
Reviewed By: davidsonic
Differential Revision: D44302504
fbshipit-source-id: 6ff62251e352d6778cb54399e2e11459e16e77ba
Summary: - Replace all the relative imports for generic models to absolute import: (from . import y => from pytorch3.x import y)
Reviewed By: shapovalov
Differential Revision: D43620682
fbshipit-source-id: 937318b339b5020d17b511a891c7b000ff659328
Summary: Indexing with a big matrix now fails with a ValueError, possibly because of pytorch improvements. Remove the testcase for it.
Reviewed By: davidsonic
Differential Revision: D42609741
fbshipit-source-id: 0a5a6632ed199cb942bfc4cc4ed347b72e491125
Summary:
Aligning the logic with the official CO3Dv2 evaluation: 92283c4368/co3d/dataset/utils.py (L7)
This will make the evaluator work with the datasets that do not define known/unseen subsets.
Reviewed By: bottler
Differential Revision: D42803136
fbshipit-source-id: cfac389eab010c32d2e33b40fc7f6ed845c327ef
Summary: If a configurable class inherits torch.nn.Module and is instantiated, automatically call `torch.nn.Module.__init__` on it before doing anything else.
Reviewed By: shapovalov
Differential Revision: D42760349
fbshipit-source-id: 409894911a4252b7987e1fd218ee9ecefbec8e62
Summary: ChainDataset is iterable, and it toes not go along with a custom batch sampler.
Reviewed By: bottler
Differential Revision: D42742315
fbshipit-source-id: 40a715c8d24abe72cb2777634247d7467f628564
Summary: For the new API, filtering iterators over sequences by subsets is quite helpful. The change is backwards compatible.
Reviewed By: bottler
Differential Revision: D42739669
fbshipit-source-id: d150a404aeaf42fd04a81304c63a4cba203f897d
Summary:
V2 dataset does not have the concept of known/unseen frames. Test-time conditining is done with train-set frames, which violates the previous check.
Also fixing a corner case in VideoWriter.
Reviewed By: bottler
Differential Revision: D42706976
fbshipit-source-id: d43be3dd3060d18cb9f46d5dcf6252d9f084110f
Summary:
Fixes some issues with RayBundle plotting:
- allows plotting raybundles on gpu
- view -> reshape since we do not require contiguous raybundle tensors as input
Reviewed By: bottler, shapovalov
Differential Revision: D42665923
fbshipit-source-id: e9c6c7810428365dca4cb5ec80ef15ff28644163
Summary: We don’t see much value in reporting metrics by camera difficulty while supporting that in new datasets is quite painful, hence deprecating training cameras in the data API and ignoring in evaluation.
Reviewed By: bottler
Differential Revision: D42678879
fbshipit-source-id: aad511f6cb2ca82745f31c19594e1d80594b61d7
Summary:
The file [rasterizer.py](de3a474d2b/pytorch3d/renderer/mesh/rasterizer.py (L201)) contains a duplicate line before the check if the projection_transform exists. This causes an exception in the case that a projection transform matrix is already provided. The corresponding lines should be (and are already) in the else case of the if-statement.
Removing these lines fixes the bug and produces the desired behavior.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1421
Reviewed By: shapovalov
Differential Revision: D42450999
Pulled By: bottler
fbshipit-source-id: f7464e87ec9ff8768455656324b0b008132c8a54
Summary: Use IndexError so that a camera object is an iterable
Reviewed By: shapovalov
Differential Revision: D42312021
fbshipit-source-id: 67c417d5f1398e8b30a6944468eda057b4ceb444
Summary:
- Fix the numbers in the headers. Currently, there are no header number 2, the tutorial jump from 1 to 3.
- Clean some unnecessary code.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1423
Reviewed By: shapovalov
Differential Revision: D42478609
Pulled By: bottler
fbshipit-source-id: c49fc10b7d38c3573c92fea737101e6c06bbea38
Summary:
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1394
The bash logic for building conda packages became fiddly to edit. We need to switch cuda-toolkit to pytorch-cuda when PyTorch>=1.12 which was going to be a pain, so here I rewrite the code in python and do it.
Reviewed By: shapovalov
Differential Revision: D42036406
fbshipit-source-id: 8bb80c2f7545477182b23fc97c8514dcafcee176
