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54b482bd66
Summary: davnov134 found that the algorithm crashes if X is an axis-aligned plane. This is because I implemented scaling control points by `X.std()` as a poor man’s version of PCA whitening. I checked that it does not bring consistent improvements, so let’s get rid of it. The algorithm still results in slightly higher errors on the axis aligned planes but at least it does not crash. As a next step, I will experiment with detecting a planar case and using 3-point barycentric coordinates rather than 4-points. Reviewed By: davnov134 Differential Revision: D21179968 fbshipit-source-id: 1f002fce5541934486b51808be0e910324977222
28 lines
883 B
Python
28 lines
883 B
Python
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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from .cubify import cubify
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from .graph_conv import GraphConv
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from .knn import knn_gather, knn_points
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from .mesh_face_areas_normals import mesh_face_areas_normals
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from .packed_to_padded import packed_to_padded, padded_to_packed
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from .perspective_n_points import efficient_pnp
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from .points_alignment import corresponding_points_alignment, iterative_closest_point
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from .points_normals import (
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estimate_pointcloud_local_coord_frames,
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estimate_pointcloud_normals,
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)
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from .sample_points_from_meshes import sample_points_from_meshes
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from .subdivide_meshes import SubdivideMeshes
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from .utils import (
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convert_pointclouds_to_tensor,
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eyes,
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get_point_covariances,
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is_pointclouds,
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wmean,
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)
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from .vert_align import vert_align
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__all__ = [k for k in globals().keys() if not k.startswith("_")]
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