GitLab

Summary:
Similar to non square image rasterization for meshes, apply the same updates to the pointcloud rasterizer.

Main API Change:
- PointRasterizationSettings now accepts a tuple/list of (H, W) for the image size.

Reviewed By: jcjohnson

Differential Revision: D25465206

fbshipit-source-id: 7370d83c431af1b972158cecae19d82364623380

Add check for verts and faces being on same device and also checks for pointclouds/features/normals being on the same device (#384)

Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/384

Test Plan: `test_meshes` and `test_points`

Reviewed By: gkioxari

Differential Revision: D24730524

Pulled By: nikhilaravi

fbshipit-source-id: acbd35be5d9f1b13b4d56f3db14f6e8c2c0f7596

Summary: Add `return self` to the `to` function for the renderer classes.

Reviewed By: bottler

Differential Revision: D25534487

fbshipit-source-id: e8dbd35524f0bd40e835439e93184b5a1f1532ca

Summary:
As for now, epsilon value is ignored, since `kwargs` are passed to constructor only

Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/418

Reviewed By: gkioxari

Differential Revision: D24730500

Pulled By: nikhilaravi

fbshipit-source-id: 7cce820dbe14f8c74d3df4f18c45d50e228c6a45

Differential Revision: D25497975

fbshipit-source-id: 9f7aa8d1dd31fa62a428321394d8c97b2d9d937d

Summary:
There are a couple of options for supporting non square images:
1) NDC stays at [-1, 1] in both directions with the distance calculations all modified by (W/H). There are a lot of distance based calculations (e.g. triangle areas for barycentric coordinates etc) so this requires changes in many places.
2) NDC is scaled by (W/H) so the smallest side has [-1, 1]. In this case none of the distance calculations need to be updated and only the pixel to NDC calculation needs to be modified.

I decided to go with option 2 after trying option 1!

API Changes:
- Image size can now be specified optionally as a tuple

TODO:
- add a benchmark test for the non square case.

Reviewed By: jcjohnson

Differential Revision: D24404975

fbshipit-source-id: 545efb67c822d748ec35999b35762bce58db2cf4

Reviewed By: zertosh

Differential Revision: D25241045

fbshipit-source-id: c3a1e1e02ef557b1e82cb672e987e05016e246fd

Summary: Taubin Smoothing for filtering meshes and making them smoother. Taubin smoothing is an iterative approach.

Reviewed By: nikhilaravi

Differential Revision: D24751149

fbshipit-source-id: fb779e955f1a1f6750e704f1b4c6dfa37aebac1a

Summary: If a pointcloud had less than pointcloud_max_points, the colors would not render. This diff fixes that.

Reviewed By: bottler

Differential Revision: D25099044

fbshipit-source-id: 47c3ddcdb4e06284b0a7966ffca1b973f394921f

Summary: Previously, grids where the columns don't divide the number of plots evenly would error. Now, there'll just be a sparse last row.

Reviewed By: bottler

Differential Revision: D25069236

fbshipit-source-id: 9d2fd62f3d39bfebc07ce0a41718621fa69d6057

Summary: This fixed #442 by declaring two math functions to be device-only.

Reviewed By: bottler

Differential Revision: D24896992

fbshipit-source-id: a15918d06d2a3e6ee5cf250fec7af5f2f50a6164

Reviewed By: nikhilaravi

Differential Revision: D24390049

fbshipit-source-id: d86ba8dd933bce18e65ae71b3ea42426838b8fc2

Summary:
Changes to CI and some minor fixes now that pulsar is part of pytorch3d. Most significantly, add CUB to CI builds.

Make CUB_HOME override the CUB already in cudatoolkit (important for cuda11.0 which uses cub 1.9.9 which pulsar doesn't work well with.
Make imageio available for testing.
Lint fixes.
Fix some test verbosity.
Avoid use of atomicAdd_block on older GPUs.

Reviewed By: nikhilaravi, classner

Differential Revision: D24773716

fbshipit-source-id: 2428356bb2e62735f2bc0c15cbe4cff35b1b24b8

Summary:
Removes the now-unnecessary kernels from point mesh edge file

Migrates all point mesh functionality into one file.

Reviewed By: gkioxari

Differential Revision: D24550086

fbshipit-source-id: f924996cd38a7c2c1cf189d8a01611de4506cfa3

Summary: This diff creates the generic MeshBackwardKernel which can handle distance calculations between point, edge and faces in either direction. Replaces only point_mesh_face code for now.

Reviewed By: gkioxari

Differential Revision: D24549374

fbshipit-source-id: 2853c1da1c2a6b6de8d0e40007ba0735b8959044

Summary: This diff creates the generic MeshForwardKernel which can handle distance calculations between point, edge and faces in either direction. Replaces only point_mesh_face code for now.

Reviewed By: gkioxari

Differential Revision: D24543316

fbshipit-source-id: 302707d7cec2d77a899738adf40481035c240da8

Summary: Added missing include for cstdint for Windows and removed problematic inline assembly.

Reviewed By: bottler

Differential Revision: D24838053

fbshipit-source-id: 95496be841c2c22a82068073d4740e98ee8a02ac

Summary: Users want to be able to obtain the depth from the renderer. Current work-around requires running the rasterizer and extra time. This change creates a new renderer class that also returns the fragments from the rasterizer.

Reviewed By: nikhilaravi

Differential Revision: D24432381

fbshipit-source-id: 6552e8a6bfee646791afb34bdb7452fbc4094aed

Summary: Move to a local import for calculating pointcloud normals, similar to _compute_face_areas_normals on Meshes.

Reviewed By: theschnitz

Differential Revision: D24695260

fbshipit-source-id: 9e1eb5d15017975b8c4f4175690cc3654f38d9a4

Summary: This diff updates the documentation and tutorials with information about the new pulsar backend. For more information about the pulsar backend, see the release notes and the paper (https://arxiv.org/abs/2004.07484). For information on how to use the backend, see the point cloud rendering notebook and the examples in the folder docs/examples.

Reviewed By: nikhilaravi

Differential Revision: D24498129

fbshipit-source-id: e312b0169a72b13590df6e4db36bfe6190d742f9

Summary:
This diff builds on top of the `pulsar integration` diff to provide a unified interface for the existing PyTorch3D point renderer and Pulsar. For more information about the pulsar backend, see the release notes and the paper (https://arxiv.org/abs/2004.07484). For information on how to use the backend, see the point cloud rendering notebook and the examples in the folder docs/examples.

The unified interfaces are completely consistent. Switching the render backend is as easy as using `renderer = PulsarPointsRenderer(rasterizer=rasterizer).to(device)` instead of `renderer = PointsRenderer(rasterizer=rasterizer, compositor=compositor)` and adding the `gamma` parameter to the forward function. All PyTorch3D camera types are supported as far as possible; keyword arguments are properly forwarded to the camera. The `PerspectiveCamera` and `OrthographicCamera` require znear and zfar as additional parameters for the forward pass.

Reviewed By: nikhilaravi

Differential Revision: D21421443

fbshipit-source-id: 4aa0a83a419592d9a0bb5d62486a1cdea9d73ce6

Summary:
This diff integrates the pulsar renderer source code into PyTorch3D as an alternative backend for the PyTorch3D point renderer. This diff is the first of a series of three diffs to complete that migration and focuses on the packaging and integration of the source code.

For more information about the pulsar backend, see the release notes and the paper (https://arxiv.org/abs/2004.07484). For information on how to use the backend, see the point cloud rendering notebook and the examples in the folder `docs/examples`.

Tasks addressed in the following diffs:
* Add the PyTorch3D interface,
* Add notebook examples and documentation (or adapt the existing ones to feature both interfaces).

Reviewed By: nikhilaravi

Differential Revision: D23947736

fbshipit-source-id: a5e77b53e6750334db22aefa89b4c079cda1b443

Summary: To initialize the Cameras class currently we require the principal point, focal length and other parameters to be specified from which we calculate the intrinsic matrix. In some cases the matrix might be directly available e.g. from a dataset and the associated metadata for an image.

Reviewed By: nikhilaravi

Differential Revision: D24489509

fbshipit-source-id: 1b411f19c5f6c8074bcfbf613f3339d5e242c119

Summary: We envision `pytorch3d.vis` to contain submodules with different dependencies. Allow (and require) them to be imported independently.

Reviewed By: theschnitz

Differential Revision: D24622519

fbshipit-source-id: 44840f70f5fd2bd410405bf09546024e48238744

Summary: New methods to directly plot a TexturesUV map with its used points, using PIL and matplotlib.

Reviewed By: gkioxari

Differential Revision: D23782968

fbshipit-source-id: 692970857b5be13a35a3175dc82ac03963a73555

Summary: Fix axis_angle conversions where I used torch.square which doesn't work with pytorch 1.4

Reviewed By: nikhilaravi

Differential Revision: D24451546

fbshipit-source-id: ba26f7dad5fa991f0a8f7d3d09ee7151163aecf4

Summary: We can represent a rotation as a vector in the axis direction, whose length is the rotation anticlockwise in radians around that axis.

Reviewed By: gkioxari

Differential Revision: D24306293

fbshipit-source-id: 2e0f138eda8329f6cceff600a6e5f17a00e4deb7

Summary: Take in a renderer with camera(s) and render the cameras as wireframes in the corresponding plotly plots

Reviewed By: nikhilaravi

Differential Revision: D24151706

fbshipit-source-id: f8e86d61f3d991500bafc0533738c79b96bda630

Summary:
Use a provided renderer's camera positions to render a plotly plot to match what the renderer would render for pointclouds and meshes.
- takes in a Cameras object for viewpoints
- for each subplot, will index into the Cameras object (or use the Cameras object, if len(viewpoint_cameras) == 1 and use the Cameras' eye and at vectors to set plotly's camera's corresponding values, the eye and center values.

Reviewed By: nikhilaravi

Differential Revision: D24094934

fbshipit-source-id: 48abcdb04c6909a172ba9f721522c3446952a089

Summary:
- adds plot_batch_individually
- for each batched object, plots each object in its own subplot with other same-indexed elements of the other batched objects provided as input

Reviewed By: nikhilaravi

Differential Revision: D24258389

fbshipit-source-id: a80128e6e7a03a44c257b0598569159afadb2d39

Summary: Defines a function plot_scene that takes in a dictionary defining subplot and trace layouts for Mesh/Pointcloud objects and plots them. Also supports other plotly axis arguments and mesh lighting. Plot_batch_individually is a wrapper function that takes in one or multiple batched Meshes/Pointclouds and uses plot_scene to plot each element within a batch in an individual subplot, possibly sharing that subplot with traces of other individual elements of the other batched structures passed in.

Reviewed By: nikhilaravi

Differential Revision: D24235479

fbshipit-source-id: 9f669f1b186d55fe5c75552083316c0cf1387472

Summary:
As pointed out in #328, we had an indexing operation where a reshape would do and be faster. The resulting faces_packed_to_edges_packed is no longer contiguous.

Also fix a use of faces_packed_to_edges_packed which might modify the object unintentionally.

Reviewed By: theschnitz

Differential Revision: D24390292

fbshipit-source-id: 225677d8fcc1d6b76efad7706718ecdb5182ffe1

Summary: The linter has become stricter about the indenting of comments and docstrings. This was accompanied by a codemod. In a few places we can fix the problem nicer than the codemod has.

Reviewed By: gkioxari

Differential Revision: D24363880

fbshipit-source-id: 4cff3bbe3d2a834bc92a490469a2b24fa376e6ab

Summary:
Small fix and updated tests for multigpu rendering case.

This resolves the issue seen in: https://github.com/facebookresearch/pytorch3d/issues/401

Reviewed By: gkioxari

Differential Revision: D24314681

fbshipit-source-id: 84c5a5359844c77518b48044001daa9a86f3c43a

Summary: Issue #119. The function `sqrt(max(x, 0))` is not convex and has infinite gradient at 0, but 0 is a subgradient at 0. Here we implement it in such a way as to give 0 as the gradient.

Reviewed By: gkioxari

Differential Revision: D24306294

fbshipit-source-id: 48d136faca083babad4d64970be7ea522dbe9e09

Summary:
allow-large-files

black_any_style

Reviewed By: zertosh

Differential Revision: D24325133

fbshipit-source-id: b4afe80d1e8b2bc993f4b8e3822c02964df47462

Summary: As mentioned in a comment on https://github.com/facebookresearch/pytorch3d/issues/77, we can't use this function in Python 3.6. It's easy to write our own version.

Reviewed By: gkioxari

Differential Revision: D24249915

fbshipit-source-id: 4c70a3efb03daa115041d082e616511297eab8fa

Summary:
Fix for GitHub issue #381.

The example mesh provided in the issue only had material properties but no texture image. The current implementation of texture atlassing generated an atlas using both the material properties and the texture image but only worked if there was a texture image and associated vertex uv coordinates. I have now modified the texture atlas creation so that it doesn't require an image and can work with materials which only have material properties.

Reviewed By: gkioxari

Differential Revision: D24153068

fbshipit-source-id: 63e9d325db09a84b336b83369d5342ce588a9932

Summary: Importing from pytorch3d.visualization is wordy, so shortened the path to the vis module and updated the relevant imports.

Reviewed By: nikhilaravi

Differential Revision: D24116527

fbshipit-source-id: e0e4da7d48c5afedec07482d7be43362b6822445

Summary: Enhance every texture type with `faces_verts_textures_packed` that allows users to query the texture of each vertex in mesh

Reviewed By: nikhilaravi

Differential Revision: D24058778

fbshipit-source-id: 19d0e3a244fa96aae462c47bf52e07dfd3b7c6f0