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Add documentation for KNN index selector.

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Austin J. Garrett
2018-03-19 12:32:23 -04:00
parent 50b77758df
commit 95a75b4bb2
1 changed files with 16 additions and 3 deletions
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pointcnn/core.py
+16 -3
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@@ -90,7 +90,7 @@ class PointCNN(nn.Module):
OUT
======
P_idx : (N, N_neighbors) Array of indices into P such that
P[P_idx] is the set of points
P[P_idx] is the set of points in the "region" around p.
a representative point p and a point cloud P. From these it returns an
array of N_neighbors
@@ -109,8 +109,8 @@ class PointCNN(nn.Module):
Selects
:type P_idx: FloatTensor (N, N_neighbors)
:type P: FloatTensor (N, *, *)
:param P_idx: Indices of points in region to be selected.
:param P: Point cloud to select regional points from.
:param P_idx: Indices of points in region to be selected
:param P: Point cloud to select regional points from
"""
return torch.stack([
P[n,:,:].index_select(0, idx) for n, idx in torch.unbind(P_idx, dim = 0)
@@ -137,3 +137,16 @@ class PointCNN(nn.Module):
for p in torch.unbind(ps, dim = 1)
], dim = 1)
return inp_regions
def knn_indices_func(p, P):
"""
Indexing function based on K-Nearest Neighbors search.
:type p: FloatTensor (N, D)
:type P: FloatTensor (N, *, D)
:rtype: FloatTensor (N, N_neighbors)
:param p: Representative point
:param P: Point cloud to get indices from
:return: Array of indices, P_idx, into P such that P[P_idx] is the set
of points in the "region" around p.
"""
raise NotImplementedError("Implement me!")