Summary:
Added export of UV textures to IO.save_mesh in Pytorch3d
MeshObjFormat now passes verts_uv, faces_uv, and texture_map as input to save_obj
TODO: check if TexturesUV.verts_uv_list or TexturesUV.verts_uv_padded() should be passed to save_obj
IO.save_mesh(obj_file, meshes, decimal_places=2) should be IO().save_mesh(obj_file, meshes, decimal_places=2)
Reviewed By: bottler
Differential Revision: D39617441
fbshipit-source-id: 4628b7f26f70e38c65f235852b990c8edb0ded23
Summary:
- indicate location of OmegaConf.structured failures
- split the data gathering from enable_get_default_args to ease experimenting with it.
- comment fixes.
- nicer error when a_class_type has weird type.
Reviewed By: kjchalup
Differential Revision: D39434447
fbshipit-source-id: b80c7941547ca450e848038ef5be95b7ebbe8f3e
Summary:
Move the flyaround rendering function into core implicitron.
The unblocks an example in the facebookresearch/co3d repo.
Reviewed By: bottler
Differential Revision: D39257801
fbshipit-source-id: 6841a88a43d4aa364dd86ba83ca2d4c3cf0435a4
Summary: Currently some implicit functions in implicitron take a raybundle, others take ray_points_world. raybundle is what they really need. However, the raybundle is going to become a bit more flexible later, as it will contain different numbers of rays for each camera.
Reviewed By: bottler
Differential Revision: D39173751
fbshipit-source-id: ebc038e426d22e831e67a18ba64655d8a61e1eb9
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: 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
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: 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: 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:
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:
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:
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
