def nearest_correspondance(pts_src, pts_dest, data_src, K=1):
print(pts_dest.shape)
indices = nearest_neighbors.knn(pts_src, pts_dest, K, omp=True)
print(indices.shape)
if K == 1:
indices = indices.ravel()
data_dest = data_src[indices]
else:
data_dest = data_src[indices].mean(1)
return data_dest
def nearest_correspondance(pts_src, pts_dest, data_src, K=1):
print(pts_dest.shape)
indices = nearest_neighbors.knn(pts_src, pts_dest, K, omp=True)
# tree = BallTree(pts_src, leaf_size=2)
# _, indices = tree.query(pts_dest, k=K)
print(indices.shape)
if K == 1:
indices = indices.ravel()
data_dest = data_src[indices]
else:
data_dest = data_src[indices].mean(1)
return data_dest
