Summary: We now use unittest.mock
Reviewed By: shapovalov
Differential Revision: D45868799
fbshipit-source-id: cd1042dc2c49c82c7b9e024f761c496049a31beb
Summary:
Hi,
Not sure this is the best fix. But while running this notebook, I only ever saw a blank canvas when trying to visualize the dolphin. It might be that I have a broken dependency, like plotly. I also don't know what the visualization is "supposed" to look like.
But incase other people have this issue, this one line change solved the whole problem for me. Now I have a happy, rotatable dolphin.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1549
Reviewed By: shapovalov
Differential Revision: D46350930
Pulled By: bottler
fbshipit-source-id: e19aa71eb05a93e2955262a2c90d1f0d09576228
Summary:
If my understanding is right, prp_screen[1] should be 32 rather than 48.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1501
Reviewed By: shapovalov
Differential Revision: D45044406
Pulled By: bottler
fbshipit-source-id: 7dd93312db4986f4701e642ba82d94333466b921
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: Autogenerate docs for the renderer too. This will be helpful but make a slightly ugly TOC
Reviewed By: kjchalup
Differential Revision: D40977315
fbshipit-source-id: 10831de3ced68080cb5671c5dc31d4da8500f761
Summary: Try to document implicitron. Most of this is autogenerated.
Reviewed By: shapovalov
Differential Revision: D40623742
fbshipit-source-id: 453508277903b7d987b1703656ba1ee09bc2c570
Summary: new implicitronRayBundle with added cameraIDs and camera counts. Added to enable a single raybundle inside Implicitron and easier extension in the future. Since RayBundle is named tuple and RayBundleHeterogeneous is dataclass and RayBundleHeterogeneous cannot inherit RayBundle. So if there was no ImplicitronRayBundle every function that uses RayBundle now would have to use Union[RayBundle, RaybundleHeterogeneous] which is confusing and unecessary complicated.
Reviewed By: bottler, kjchalup
Differential Revision: D39262999
fbshipit-source-id: ece160e32f6c88c3977e408e966789bf8307af59
Summary: need to pip install visdom in new volumes tutorial.
Reviewed By: kjchalup
Differential Revision: D38501905
fbshipit-source-id: 534bf097e41f05b3389e9420e6dd2b61a4517861
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:
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: bottler
Differential Revision: D35553814
fbshipit-source-id: be49bdb6a4c25264ff8d4db3a601f18736d17be1
Summary: Migrate away from NDCGridRaysampler and GridRaysampler to their more flexible replacements.
Reviewed By: patricklabatut
Differential Revision: D33281584
fbshipit-source-id: 65f8702e700a32d38f7cd6bda3924bb1707a0633
Summary: Add --no-cache and --no-index to all commands which try to download wheels from S3, to avoid hitting pypi.
Reviewed By: nikhilaravi
Differential Revision: D33507975
fbshipit-source-id: ee796e43cc1864e475cd73c248e9900487012f25
Summary: Update all FB license strings to the new format.
Reviewed By: patricklabatut
Differential Revision: D33403538
fbshipit-source-id: 97a4596c5c888f3c54f44456dc07e718a387a02c
Summary: Fix some comments to match the recent change to transform_points_screen.
Reviewed By: patricklabatut
Differential Revision: D33243697
fbshipit-source-id: dc8d182667a9413bca2c2e3657f97b2f7a47c795
Summary: Make code for downloading linux wheels robust to double-digit PyTorch minor version.
Reviewed By: nikhilaravi
Differential Revision: D33170562
fbshipit-source-id: 559a97cc98ff8411e235a9f9e29f84b7a400c716
Summary: Pre 0.6.1 release, make the tutorials expect wheels with PyTorch 1.10.0
Reviewed By: patricklabatut
Differential Revision: D33016834
fbshipit-source-id: b8c5c1c6158f806c3e55ec668117fa762fa4b75f
Summary:
All the renderers in PyTorch3D (pointclouds including pulsar, meshes, raysampling) use align_corners=False style. NDC space goes between the edges of the outer pixels. For a non square image with W>H, the vertical NDC space goes from -1 to 1 and the horizontal from -W/H to W/H.
However it was recently pointed out that functionality which deals with screen space inside the camera classes is inconsistent with this. It unintentionally uses align_corners=True. This fixes that.
This would change behaviour of the following:
- If you create a camera in screen coordinates, i.e. setting in_ndc=False, then anything you do with the camera which touches NDC space may be affected, including trying to use renderers. The transform_points_screen function will not be affected...
- If you call the function “transform_points_screen” on a camera defined in NDC space results will be different. I have illustrated in the diff how to get the old results from the new results but this probably isn’t the right long-term solution..
Reviewed By: gkioxari
Differential Revision: D32536305
fbshipit-source-id: 377325a9137282971dcb7ca11a6cba3fc700c9ce
Summary: Small docs fixes: spelling. Avoid things which get out of date quickly: year, version.
Reviewed By: patricklabatut
Differential Revision: D31659927
fbshipit-source-id: b0111140bdaf3c6cadc09f70621bf5656909ca02
Summary: A small fix for the iou3d note
Reviewed By: bottler
Differential Revision: D31370686
fbshipit-source-id: 6c97302b5c78de52915f31be70f234179c4b246d
Summary:
A note for our new algorithm for IoU of oriented 3D boxes. It includes
* A description of the algorithm
* A comparison with Objectron
Reviewed By: nikhilaravi
Differential Revision: D31288066
fbshipit-source-id: 0ea8da887bc5810bf4a3e0848223dd3590df1538
Summary:
Great work! :)
Just found a link in the examples that is not working. This will fix it.
Best,
Alex
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/818
Reviewed By: nikhilaravi
Differential Revision: D30637532
Pulled By: patricklabatut
fbshipit-source-id: ed6c52375d1e760cb0fb2c0a66648dfeb0c6ed46
Summary: Change doc references to master branch to its new name main.
Reviewed By: nikhilaravi
Differential Revision: D30303018
fbshipit-source-id: cfdbb207dfe3366de7e0ca759ed56f4b8dd894d1
Summary: At the next release, the prebuilt PyTorch3D wheels will depend on PyTorch 1.9.0. Update the tutorials to expect this.
Reviewed By: nikhilaravi
Differential Revision: D29614450
fbshipit-source-id: 39978a6a55b62fb7c7e62aaa8f138e47cadd631e
Summary:
API fix for NDC/screen cameras and compatibility with PyTorch3D renderers.
With this new fix:
* Users can define cameras and `transform_points` under any coordinate system conventions. The transformation applies the camera K and RT to the input points, not regarding for PyTorch3D conventions. So this makes cameras completely independent from PyTorch3D renderer.
* Cameras can be defined either in NDC space or screen space. For existing ones, FoV cameras are in NDC space. Perspective/Orthographic can be defined in NDC or screen space.
* The interface with PyTorch3D renderers happens through `transform_points_ndc` which transforms points to the NDC space and assumes that input points are provided according to PyTorch3D conventions.
* Similarly, `transform_points_screen` transforms points to screen space and again assumes that input points are under PyTorch3D conventions.
* For Orthographic/Perspective cameras, if they are defined in screen space, the `get_ndc_camera_transform` allows points to be converted to NDC for use for the renderers.
Reviewed By: nikhilaravi
Differential Revision: D26932657
fbshipit-source-id: 1a964e3e7caa54d10c792cf39c4d527ba2fb2e79
Summary: Fixes#514, so we don't assume user of the tutorial has access to utils.
Reviewed By: nikhilaravi
Differential Revision: D29557294
fbshipit-source-id: 10ac994be65df0822d3ee4e9d690189ff13074a2
Summary: Deprecate the `so3_exponential_map()` function in favor of its alias `so3_exp_map()`: this aligns with the naming of `so3_log_map()` and the recently introduced `se3_exp_map()` / `se3_log_map()` pair.
Reviewed By: bottler
Differential Revision: D29329966
fbshipit-source-id: b6f60b9e86b2995f70b1fbeb16f9feea05c55de9
