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:
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
```
Reviewed By: bottler
Differential Revision: D37775767
Pulled By: d4l3k
fbshipit-source-id: 5f001903985976d7067d1fa0a3102d602790e3e8
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: 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
Summary: As part of removing Task, make the dataset code generate the source cameras for itself. There's a small optimization available here, in that the JsonIndexDataset could avoid loading images.
Reviewed By: shapovalov
Differential Revision: D37313423
fbshipit-source-id: 3e5e0b2aabbf9cc51f10547a3523e98c72ad8755
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: After landing https://github.com/pytorch/pytorch/pull/69607, that made it an error to use indexing with `cpu_tensor[cuda_indices]`. There was one outstanding test in fbcode that incorrectly used indexing in that way, which is fixed here
Reviewed By: bottler, osalpekar
Differential Revision: D37128838
fbshipit-source-id: 611b6f717b5b5d89fa61fd9ebeb513ad7e65a656
Summary:
David had his code crashed when using frame_annot["meta"] dictionary. Turns out we had a typo.
The tests were passing by chance since all the keys were single-character strings.
Reviewed By: bottler
Differential Revision: D37503987
fbshipit-source-id: c12b0df21116cfbbc4675a0182b9b9e6d62bad2e
Summary: small followup to D37172537 (cba26506b6) and D37209012 (81d63c6382): changing default #harmonics and improving a test
Reviewed By: shapovalov
Differential Revision: D37412357
fbshipit-source-id: 1af1005a129425fd24fa6dd213d69c71632099a0
Summary: The blender synthetic dataset contains object masks in the alpha channel. Provide these in the corresponding dataset.
Reviewed By: shapovalov
Differential Revision: D37344380
fbshipit-source-id: 3ddacad9d667c0fa0ae5a61fb1d2ffc806c9abf3
Summary: Images were coming out in the wrong format.
Reviewed By: shapovalov
Differential Revision: D37291278
fbshipit-source-id: c10871c37dd186982e7abf2071ac66ed583df2e6
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: Changes to JsonIndexDataset to make it fit with OmegaConf.structured. Also match some default values to what the provider defaults to.
Reviewed By: davnov134
Differential Revision: D36666704
fbshipit-source-id: 65b059a1dbaa240ce85c3e8762b7c3db3b5a6e75
Summary: Allow a class to modify its subparts in get_default_args by defining the special function provide_config_hook.
Reviewed By: davnov134
Differential Revision: D36671081
fbshipit-source-id: 3e5b73880cb846c494a209c4479835f6352f45cf
Summary: Our tests fail (https://fburl.com/jmoqo9bz) because test_splatter_blend uses torch.tile, which is not supported in earlier torch versions. Replace it with tensor.extend.
Reviewed By: bottler
Differential Revision: D36796098
fbshipit-source-id: 38d5b40667f98f3163b33f44e53e96b858cfeba2
Summary: Fix divide by zero for empty pointcloud in chamfer. Also for empty batches. In process, needed to regularize num_points_per_cloud for empty batches.
Reviewed By: kjchalup
Differential Revision: D36311330
fbshipit-source-id: 3378ab738bee77ecc286f2110a5c8dc445960340
Summary: A few minor additions I didn't fit into the SplatterBlender diffs, as requested by reviewers.
Reviewed By: jcjohnson
Differential Revision: D36682437
fbshipit-source-id: 57af995e766dfd2674b3984a3ba00aef7ca7db80
Summary: The ImplicitronDataset class corresponds to JsonIndexDatasetMapProvider
Reviewed By: shapovalov
Differential Revision: D36661396
fbshipit-source-id: 80ca2ff81ef9ecc2e3d1f4e1cd14b6f66a7ec34d
Summary: test_viewpool was inactive so missed being fixed in D36547815 (2d1c6d5d93)
Reviewed By: kjchalup
Differential Revision: D36625587
fbshipit-source-id: e7224eadfa5581fe61f10f67d2221071783de04a
Summary:
Benchmarking. We only use num_faces=2 for splatter, because as far as I can see one would never need to use more. Pose optimization and mesh optimization experiments (see next two diffs) showed that Splatter with 2 faces beats Softmax with 50 and 100 faces in terms of accuracy.
Results: We're slower at 64px^2. At 128px and 256px, we're slower than Softmax+50faces, but faster than Softmax+100faces. We're also slower at 10 faces/pix, but expectation as well as results show that more then 2 faces shouldn't be necessary. See also more results in .https://fburl.com/gdoc/ttv7u7hp
Reviewed By: jcjohnson
Differential Revision: D36210575
fbshipit-source-id: c8de28c8a59ce5fe21a47263bd43d2757b15d123
Summary: Splatting shader. See code comments for details. Same API as SoftPhongShader.
Reviewed By: jcjohnson
Differential Revision: D36354301
fbshipit-source-id: 71ee37f7ff6bb9ce028ba42a65741424a427a92d
Summary: PLY with mixture of triangle and quadrilateral faces was failing.
Reviewed By: gkioxari
Differential Revision: D36592981
fbshipit-source-id: 5373edb2f38389ac646a75fd2e1fa7300eb8d054
Summary: Use small image size for test_all_gm_configs
Reviewed By: shapovalov
Differential Revision: D36511528
fbshipit-source-id: 2c65f518a4f23626850343a62d103f85abfabd88
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: Separate ImplicitronDatasetBase and FrameData (to be used by all data sources) from ImplicitronDataset (which is specific).
Reviewed By: shapovalov
Differential Revision: D36413111
fbshipit-source-id: 3725744cde2e08baa11aff4048237ba10c7efbc6
Summary: Make ResNetFeatureExtractor be an implementation of FeatureExtractorBase.
Reviewed By: davnov134
Differential Revision: D35433098
fbshipit-source-id: 0664a9166a88e150231cfe2eceba017ae55aed3a
Summary: Allow extra data in a FrameAnnotation. Therefore allow Optional[T] systematically in _dataclass_from_dict
Reviewed By: davnov134
Differential Revision: D36442691
fbshipit-source-id: ba70f6491574c08b0d9c9acb63f35514d29de214
Summary: Fix recently observed case where enable_get_default_args was missing things declared as Optional[something mutable]=None.
Reviewed By: davnov134
Differential Revision: D36440492
fbshipit-source-id: 192ec07564c325b3b24ccc49b003788f67c63a3d
Summary: Make create_x delegate to create_x_impl so that users can rely on create_x_impl in their overrides of create_x.
Reviewed By: shapovalov, davnov134
Differential Revision: D35929810
fbshipit-source-id: 80595894ee93346b881729995775876b016fc08e
Summary:
Applies new import merging and sorting from µsort v1.0.
When merging imports, µsort will make a best-effort to move associated
comments to match merged elements, but there are known limitations due to
the diynamic nature of Python and developer tooling. These changes should
not produce any dangerous runtime changes, but may require touch-ups to
satisfy linters and other tooling.
Note that µsort uses case-insensitive, lexicographical sorting, which
results in a different ordering compared to isort. This provides a more
consistent sorting order, matching the case-insensitive order used when
sorting import statements by module name, and ensures that "frog", "FROG",
and "Frog" always sort next to each other.
For details on µsort's sorting and merging semantics, see the user guide:
https://usort.readthedocs.io/en/stable/guide.html#sorting
Reviewed By: lisroach
Differential Revision: D36402260
fbshipit-source-id: 7cb52f09b740ccc580e61e6d1787d27381a8ce00
Summary: Like vgg16 for lpips, internally we need resnet34 weights for coming feature extractor tests.
Reviewed By: davnov134
Differential Revision: D36349361
fbshipit-source-id: 1c33009c904766fcc15e7e31cd15d0f820c57354
Summary: Implements a ViewPooler that groups ViewSampler and FeatureAggregator.
Reviewed By: shapovalov
Differential Revision: D35852367
fbshipit-source-id: c1bcaf5a1f826ff94efce53aa5836121ad9c50ec
