def grid_sub_sampling(points,
features=None,
labels=None,
grid_size=0.1,
verbose=0):
"""
CPP wrapper for a grid sub_sampling (method = barycenter for points and features
:param points: (N, 3) matrix of input points
:param features: optional (N, d) matrix of features (floating number)
:param labels: optional (N,) matrix of integer labels
:param grid_size: parameter defining the size of grid voxels
:param verbose: 1 to display
:return: sub_sampled points, with features and/or labels depending of the input
"""
if (features is None) and (labels is None):
return cpp_subsampling.compute(points,
sampleDl=grid_size,
verbose=verbose)
elif labels is None:
return cpp_subsampling.compute(points,
features=features,
sampleDl=grid_size,
verbose=verbose)
elif features is None:
return cpp_subsampling.compute(points,
classes=labels,
sampleDl=grid_size,
verbose=verbose)
else:
return cpp_subsampling.compute(points,
features=features,
classes=labels,
sampleDl=grid_size,
verbose=verbose)
def grid_subsampling(points, features=None, labels=None, sampleDl=0.1, verbose=0):
"""CPP wrapper for a grid subsampling (method = barycenter for points and features）
Args:
points (tensor): input points, (N,3)
features (tensor, optional): point features, (N,d)
labels (tensor, optional): labels, (N,)
sampleDl (float, optional): the size of grid voxels
verbose (int, optional): 1 to display
Returns:
tuple: subsampled points, with features and/or labels depending of the input
"""
if (features is None) and (labels is None):
return cpp_subsampling.compute(points, sampleDl=sampleDl, verbose=verbose)
elif (labels is None):
return cpp_subsampling.compute(points, features=features, sampleDl=sampleDl, verbose=verbose)
elif (features is None):
return cpp_subsampling.compute(points, classes=labels, sampleDl=sampleDl, verbose=verbose)
else:
return cpp_subsampling.compute(points, features=features, classes=labels, sampleDl=sampleDl, verbose=verbose)