"git@developer.sourcefind.cn:OpenDAS/mmdetection3d.git" did not exist on "ce70413fac7db8aa34cd2c63a5297e8fc5877419"
Unverified Commit 31165186 authored by Ziyi Wu's avatar Ziyi Wu Committed by GitHub
Browse files

[Fix]: fix point type errors in function docstring (#422)

parent ecd0d06a
...@@ -154,7 +154,7 @@ class LoadPointsFromMultiSweeps(object): ...@@ -154,7 +154,7 @@ class LoadPointsFromMultiSweeps(object):
"""Removes point too close within a certain radius from origin. """Removes point too close within a certain radius from origin.
Args: Args:
points (np.ndarray): Sweep points. points (np.ndarray | :obj:`BasePoints`): Sweep points.
radius (float): Radius below which points are removed. radius (float): Radius below which points are removed.
Defaults to 1.0. Defaults to 1.0.
...@@ -183,7 +183,8 @@ class LoadPointsFromMultiSweeps(object): ...@@ -183,7 +183,8 @@ class LoadPointsFromMultiSweeps(object):
dict: The result dict containing the multi-sweep points data. \ dict: The result dict containing the multi-sweep points data. \
Added key and value are described below. Added key and value are described below.
- points (np.ndarray): Multi-sweep point cloud arrays. - points (np.ndarray | :obj:`BasePoints`): Multi-sweep point \
cloud arrays.
""" """
points = results['points'] points = results['points']
points.tensor[:, 4] = 0 points.tensor[:, 4] = 0
...@@ -295,7 +296,7 @@ class NormalizePointsColor(object): ...@@ -295,7 +296,7 @@ class NormalizePointsColor(object):
dict: The result dict containing the normalized points. \ dict: The result dict containing the normalized points. \
Updated key and value are described below. Updated key and value are described below.
- points (np.ndarray): Points after color normalization. - points (:obj:`BasePoints`): Points after color normalization.
""" """
points = results['points'] points = results['points']
assert points.attribute_dims is not None and \ assert points.attribute_dims is not None and \
...@@ -393,7 +394,7 @@ class LoadPointsFromFile(object): ...@@ -393,7 +394,7 @@ class LoadPointsFromFile(object):
dict: The result dict containing the point clouds data. \ dict: The result dict containing the point clouds data. \
Added key and value are described below. Added key and value are described below.
- points (np.ndarray): Point clouds data. - points (:obj:`BasePoints`): Point clouds data.
""" """
pts_filename = results['pts_filename'] pts_filename = results['pts_filename']
points = self._load_points(pts_filename) points = self._load_points(pts_filename)
......
...@@ -147,7 +147,7 @@ class ObjectSample(object): ...@@ -147,7 +147,7 @@ class ObjectSample(object):
"""Remove the points in the sampled bounding boxes. """Remove the points in the sampled bounding boxes.
Args: Args:
points (np.ndarray): Input point cloud array. points (:obj:`BasePoints`): Input point cloud array.
boxes (np.ndarray): Sampled ground truth boxes. boxes (np.ndarray): Sampled ground truth boxes.
Returns: Returns:
...@@ -604,7 +604,7 @@ class IndoorPointSample(object): ...@@ -604,7 +604,7 @@ class IndoorPointSample(object):
Sample points to a certain number. Sample points to a certain number.
Args: Args:
points (np.ndarray): 3D Points. points (np.ndarray | :obj:`BasePoints`): 3D Points.
num_samples (int): Number of samples to be sampled. num_samples (int): Number of samples to be sampled.
replace (bool): Whether the sample is with or without replacement. replace (bool): Whether the sample is with or without replacement.
Defaults to None. Defaults to None.
...@@ -613,7 +613,7 @@ class IndoorPointSample(object): ...@@ -613,7 +613,7 @@ class IndoorPointSample(object):
Returns: Returns:
tuple[np.ndarray] | np.ndarray: tuple[np.ndarray] | np.ndarray:
- points (np.ndarray): 3D Points. - points (np.ndarray | :obj:`BasePoints`): 3D Points.
- choices (np.ndarray, optional): The generated random samples. - choices (np.ndarray, optional): The generated random samples.
""" """
if replace is None: if replace is None:
...@@ -708,10 +708,10 @@ class IndoorPatchPointSample(object): ...@@ -708,10 +708,10 @@ class IndoorPatchPointSample(object):
attributes (np.ndarray): features of input points. attributes (np.ndarray): features of input points.
attribute_dims (dict): Dictionary to indicate the meaning of extra attribute_dims (dict): Dictionary to indicate the meaning of extra
dimension. dimension.
point_type (type): class of input points. point_type (type): class of input points inherited from BasePoints.
Returns: Returns:
np.ndarray: The generated input data. :obj:`BasePoints`: The generated input data.
""" """
# subtract patch center, the z dimension is not centered # subtract patch center, the z dimension is not centered
centered_coords = coords.copy() centered_coords = coords.copy()
...@@ -742,15 +742,15 @@ class IndoorPatchPointSample(object): ...@@ -742,15 +742,15 @@ class IndoorPatchPointSample(object):
Then sample points within that patch to a certain number. Then sample points within that patch to a certain number.
Args: Args:
points (BasePoints): 3D Points. points (:obj:`BasePoints`): 3D Points.
sem_mask (np.ndarray): semantic segmentation mask for input points. sem_mask (np.ndarray): semantic segmentation mask for input points.
replace (bool): Whether the sample is with or without replacement. replace (bool): Whether the sample is with or without replacement.
Defaults to None. Defaults to None.
Returns: Returns:
tuple[np.ndarray] | np.ndarray: tuple[:obj:`BasePoints`, np.ndarray] | :obj:`BasePoints`:
- points (BasePoints): 3D Points. - points (:obj:`BasePoints`): 3D Points.
- choices (np.ndarray): The generated random samples. - choices (np.ndarray): The generated random samples.
""" """
coords = points.coord.numpy() coords = points.coord.numpy()
......
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