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Commit 80b39bd0 authored by zhangwenwei's avatar zhangwenwei
Browse files

Reformat docstrings in code

parent 64d7fbc2
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Showing with 59 additions and 70 deletions
mmdet3d/core/post_processing/box3d_nms.py
View file @ 80b39bd0
......@@ -10,7 +10,7 @@ def box3d_multiclass_nms(mlvl_bboxes,
max_num,
cfg,
mlvl_dir_scores=None):
"""Multi-class nms for 3D boxes
"""Multi-class nms for 3D boxes.
Args:
mlvl_bboxes (torch.Tensor): Multi-level boxes with shape (N, M).
......
mmdet3d/core/visualizer/show_result.py
View file @ 80b39bd0
import os.path as osp
import mmcv
import numpy as np
import trimesh
from os import path as osp
def _write_ply(points, out_filename):
"""Write points into ply format for meshlab visualization
"""Write points into ply format for meshlab visualization.
Args:
points (np.ndarray): Points in shape (N, dim).
......@@ -28,7 +27,7 @@ def _write_ply(points, out_filename):
def _write_oriented_bbox(scene_bbox, out_filename):
"""Export oriented (around Z axis) scene bbox to meshes
"""Export oriented (around Z axis) scene bbox to meshes.
Args:
scene_bbox(list[ndarray] or ndarray): xyz pos of center and
......
mmdet3d/core/voxel/builder.py
View file @ 80b39bd0
......@@ -4,7 +4,7 @@ from . import voxel_generator
def build_voxel_generator(cfg, **kwargs):
"""Builder of voxel generator"""
"""Builder of voxel generator."""
if isinstance(cfg, voxel_generator.VoxelGenerator):
return cfg
elif isinstance(cfg, dict):
......
mmdet3d/core/voxel/voxel_generator.py
View file @ 80b39bd0
......@@ -3,7 +3,7 @@ import numpy as np
class VoxelGenerator(object):
"""Voxel generator in numpy implementation
"""Voxel generator in numpy implementation.
Args:
voxel_size (list[float]): Size of a single voxel
......@@ -33,7 +33,7 @@ class VoxelGenerator(object):
self._grid_size = grid_size
def generate(self, points):
"""Generate voxels given points"""
"""Generate voxels given points."""
return points_to_voxel(points, self._voxel_size,
self._point_cloud_range, self._max_num_points,
True, self._max_voxels)
......
mmdet3d/datasets/custom_3d.py
View file @ 80b39bd0
import os.path as osp
import tempfile
import mmcv
import numpy as np
import tempfile
from os import path as osp
from torch.utils.data import Dataset
from mmdet.datasets import DATASETS
......@@ -12,7 +11,7 @@ from .pipelines import Compose
@DATASETS.register_module()
class Custom3DDataset(Dataset):
"""Customized 3D dataset
"""Customized 3D dataset.
This is the base dataset of SUNRGB-D, ScanNet, nuScenes, and KITTI
dataset.
......@@ -179,7 +178,7 @@ class Custom3DDataset(Dataset):
from mmdet3d.core.evaluation import indoor_eval
assert isinstance(
results, list), f'Expect results to be list, got {type(results)}.'
assert len(results) > 0, f'Expect length of results > 0.'
assert len(results) > 0, 'Expect length of results > 0.'
assert len(results) == len(self.data_infos)
assert isinstance(
results[0], dict
......@@ -220,8 +219,7 @@ class Custom3DDataset(Dataset):
"""Set flag according to image aspect ratio.
Images with aspect ratio greater than 1 will be set as group 1,
otherwise group 0.
In 3D datasets, they are all the same, thus are all zeros
otherwise group 0. In 3D datasets, they are all the same, thus are all
zeros
"""
self.flag = np.zeros(len(self), dtype=np.uint8)
mmdet3d/datasets/kitti_dataset.py
View file @ 80b39bd0
import copy
import os
import os.path as osp
import tempfile
import mmcv
import numpy as np
import os
import tempfile
import torch
from mmcv.utils import print_log
from os import path as osp
from mmdet.datasets import DATASETS
from ..core import show_result
......@@ -16,7 +15,7 @@ from .custom_3d import Custom3DDataset
@DATASETS.register_module()
class KittiDataset(Custom3DDataset):
"""KITTI Dataset
"""KITTI Dataset.
This class serves as the API for experiments on the KITTI Dataset.
......
mmdet3d/datasets/lyft_dataset.py
View file @ 80b39bd0
import os.path as osp
import tempfile
import mmcv
import numpy as np
import pandas as pd
import tempfile
from lyft_dataset_sdk.lyftdataset import LyftDataset as Lyft
from lyft_dataset_sdk.utils.data_classes import Box as LyftBox
from os import path as osp
from pyquaternion import Quaternion
from mmdet3d.core.evaluation.lyft_eval import lyft_eval
......@@ -16,7 +15,7 @@ from .custom_3d import Custom3DDataset
@DATASETS.register_module()
class LyftDataset(Custom3DDataset):
"""Lyft Dataset
"""Lyft Dataset.
This class serves as the API for experiments on the Lyft Dataset.
......
mmdet3d/datasets/nuscenes_dataset.py
View file @ 80b39bd0
import os.path as osp
import tempfile
import mmcv
import numpy as np
import pyquaternion
import tempfile
from nuscenes.utils.data_classes import Box as NuScenesBox
from os import path as osp
from mmdet.datasets import DATASETS
from ..core import show_result
......@@ -14,7 +13,7 @@ from .custom_3d import Custom3DDataset
@DATASETS.register_module()
class NuScenesDataset(Custom3DDataset):
"""NuScenes Dataset
"""NuScenes Dataset.
This class serves as the API for experiments on the NuScenes Dataset.
......
mmdet3d/datasets/pipelines/data_augment_utils.py
View file @ 80b39bd0
import warnings
import numba
import numpy as np
import warnings
from numba.errors import NumbaPerformanceWarning
from mmdet3d.core.bbox import box_np_ops
......@@ -44,11 +43,11 @@ def box_collision_test(boxes, qboxes, clockwise=True):
max(boxes_standup[i, 1], qboxes_standup[j, 1]))
if ih > 0:
for k in range(4):
for l in range(4):
for box_l in range(4):
A = lines_boxes[i, k, 0]
B = lines_boxes[i, k, 1]
C = lines_qboxes[j, l, 0]
D = lines_qboxes[j, l, 1]
C = lines_qboxes[j, box_l, 0]
D = lines_qboxes[j, box_l, 1]
acd = (D[1] - A[1]) * (C[0] -
A[0]) > (C[1] - A[1]) * (
D[0] - A[0])
......@@ -71,15 +70,15 @@ def box_collision_test(boxes, qboxes, clockwise=True):
# now check complete overlap.
# box overlap qbox:
box_overlap_qbox = True
for l in range(4): # point l in qboxes
for box_l in range(4): # point l in qboxes
for k in range(4): # corner k in boxes
vec = boxes[i, k] - boxes[i, (k + 1) % 4]
if clockwise:
vec = -vec
cross = vec[1] * (
boxes[i, k, 0] - qboxes[j, l, 0])
boxes[i, k, 0] - qboxes[j, box_l, 0])
cross -= vec[0] * (
boxes[i, k, 1] - qboxes[j, l, 1])
boxes[i, k, 1] - qboxes[j, box_l, 1])
if cross >= 0:
box_overlap_qbox = False
break
......@@ -88,15 +87,15 @@ def box_collision_test(boxes, qboxes, clockwise=True):
if box_overlap_qbox is False:
qbox_overlap_box = True
for l in range(4): # point l in boxes
for box_l in range(4): # point box_l in boxes
for k in range(4): # corner k in qboxes
vec = qboxes[j, k] - qboxes[j, (k + 1) % 4]
if clockwise:
vec = -vec
cross = vec[1] * (
qboxes[j, k, 0] - boxes[i, l, 0])
qboxes[j, k, 0] - boxes[i, box_l, 0])
cross -= vec[0] * (
qboxes[j, k, 1] - boxes[i, l, 1])
qboxes[j, k, 1] - boxes[i, box_l, 1])
if cross >= 0: #
qbox_overlap_box = False
break
......@@ -264,8 +263,8 @@ def noise_per_object_v3_(gt_boxes,
center_noise_std=1.0,
global_random_rot_range=np.pi / 4,
num_try=100):
"""random rotate or remove each groundtrutn independently.
use kitti viewer to test this function points_transform_
"""random rotate or remove each groundtrutn independently. use kitti viewer
to test this function points_transform_
Args:
gt_boxes: [N, 7], gt box in lidar.points_transform_
......
mmdet3d/datasets/pipelines/dbsampler.py
View file @ 80b39bd0
import copy
import numpy as np
import os
import pickle
import numpy as np
from mmdet3d.core.bbox import box_np_ops
from mmdet3d.datasets.pipelines import data_augment_utils
from ..registry import OBJECTSAMPLERS
......
mmdet3d/datasets/pipelines/loading.py
View file @ 80b39bd0
......@@ -7,7 +7,7 @@ from mmdet.datasets.pipelines import LoadAnnotations
@PIPELINES.register_module()
class LoadMultiViewImageFromFiles(object):
""" Load multi channel images from a list of separate channel files.
"""Load multi channel images from a list of separate channel files.
Expects results['img_filename'] to be a list of filenames
"""
......@@ -43,7 +43,7 @@ class LoadMultiViewImageFromFiles(object):
@PIPELINES.register_module()
class LoadPointsFromMultiSweeps(object):
"""Load points from multiple sweeps
"""Load points from multiple sweeps.
This is usually used for nuScenes dataset to utilize previous sweeps.
......@@ -143,7 +143,7 @@ class PointSegClassMapping(object):
@PIPELINES.register_module()
class NormalizePointsColor(object):
"""Normalize color of points
"""Normalize color of points.
Normalize color of the points.
......
mmdet3d/datasets/pipelines/test_time_aug.py
View file @ 80b39bd0
import mmcv
import warnings
from copy import deepcopy
import mmcv
from mmdet.datasets.builder import PIPELINES
from mmdet.datasets.pipelines import Compose
@PIPELINES.register_module()
class MultiScaleFlipAug3D(object):
"""Test-time augmentation with multiple scales and flipping
"""Test-time augmentation with multiple scales and flipping.
Args:
transforms (list[dict]): Transforms to apply in each augmentation.
......
mmdet3d/datasets/pipelines/transforms_3d.py
View file @ 80b39bd0
......@@ -91,7 +91,7 @@ class RandomFlip3D(RandomFlip):
@PIPELINES.register_module()
class ObjectSample(object):
"""Sample GT objects to the data
"""Sample GT objects to the data.
Args:
db_sampler (dict): Config dict of the database sampler.
......@@ -168,7 +168,7 @@ class ObjectSample(object):
@PIPELINES.register_module()
class ObjectNoise(object):
"""Apply noise to each GT objects in the scene
"""Apply noise to each GT objects in the scene.
Args:
translation_std (list, optional): Standard deviation of the
......@@ -221,7 +221,7 @@ class ObjectNoise(object):
@PIPELINES.register_module()
class GlobalRotScaleTrans(object):
"""Apply global rotation, scaling and translation to a 3D scene
"""Apply global rotation, scaling and translation to a 3D scene.
Args:
rot_range (list[float]): Range of rotation angle.
......@@ -374,7 +374,7 @@ class PointsRangeFilter(object):
@PIPELINES.register_module()
class ObjectNameFilter(object):
"""Filter GT objects by their names
"""Filter GT objects by their names.
Args:
classes (list[str]): list of class names to be kept for training
......
mmdet3d/datasets/scannet_dataset.py
View file @ 80b39bd0
import os.path as osp
import numpy as np
from os import path as osp
from mmdet3d.core import show_result
from mmdet3d.core.bbox import DepthInstance3DBoxes
......@@ -10,7 +9,7 @@ from .custom_3d import Custom3DDataset
@DATASETS.register_module()
class ScanNetDataset(Custom3DDataset):
"""ScanNet Dataset
"""ScanNet Dataset.
This class serves as the API for experiments on the ScanNet Dataset.
......
mmdet3d/datasets/sunrgbd_dataset.py
View file @ 80b39bd0
import os.path as osp
import numpy as np
from os import path as osp
from mmdet3d.core import show_result
from mmdet3d.core.bbox import DepthInstance3DBoxes
......@@ -10,7 +9,7 @@ from .custom_3d import Custom3DDataset
@DATASETS.register_module()
class SUNRGBDDataset(Custom3DDataset):
"""SUNRGBD Dataset
"""SUNRGBD Dataset.
This class serves as the API for experiments on the SUNRGBD Dataset.
......
mmdet3d/models/backbones/pointnet2_sa_ssg.py
View file @ 80b39bd0
import torch
import torch.nn as nn
from mmcv.runner import load_checkpoint
from torch import nn as nn
from mmdet3d.ops import PointFPModule, PointSAModule
from mmdet.models import BACKBONES
......
mmdet3d/models/backbones/second.py
View file @ 80b39bd0
import torch.nn as nn
from mmcv.cnn import build_conv_layer, build_norm_layer
from mmcv.runner import load_checkpoint
from torch import nn as nn
from mmdet.models import BACKBONES
@BACKBONES.register_module()
class SECOND(nn.Module):
"""Backbone network for SECOND/PointPillars/PartA2/MVXNet
"""Backbone network for SECOND/PointPillars/PartA2/MVXNet.
Args:
in_channels (int): Input channels
......
mmdet3d/models/dense_heads/anchor3d_head.py
View file @ 80b39bd0
import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import bias_init_with_prob, normal_init
from torch import nn as nn
from mmdet3d.core import (PseudoSampler, box3d_multiclass_nms, limit_period,
xywhr2xyxyr)
......@@ -244,7 +244,7 @@ class Anchor3DHead(nn.Module, AnchorTrainMixin):
@staticmethod
def add_sin_difference(boxes1, boxes2):
"""Convert the rotation difference to difference in sine function
"""Convert the rotation difference to difference in sine function.
Args:
boxes1 (torch.Tensor): shape (NxC), where C>=7 and
......
mmdet3d/models/dense_heads/free_anchor3d_head.py
View file @ 80b39bd0
import torch
import torch.nn.functional as F
from torch.nn import functional as F
from mmdet3d.core.bbox import bbox_overlaps_nearest_3d
from mmdet.models import HEADS
......@@ -9,7 +9,7 @@ from .train_mixins import get_direction_target
@HEADS.register_module()
class FreeAnchor3DHead(Anchor3DHead):
"""`FreeAnchor <https://arxiv.org/abs/1909.02466>`_ head for 3D detection
"""`FreeAnchor <https://arxiv.org/abs/1909.02466>`_ head for 3D detection.
Note:
This implementation is directly modified from the `mmdet implementation
......@@ -237,7 +237,7 @@ class FreeAnchor3DHead(Anchor3DHead):
return losses
def positive_bag_loss(self, matched_cls_prob, matched_box_prob):
"""Generate positive bag loss
"""Generate positive bag loss.
Args:
matched_cls_prob (torch.Tensor): Classification probability
......@@ -259,7 +259,7 @@ class FreeAnchor3DHead(Anchor3DHead):
bag_prob, torch.ones_like(bag_prob), reduction='none')
def negative_bag_loss(self, cls_prob, box_prob):
"""Generate negative bag loss
"""Generate negative bag loss.
Args:
cls_prob (torch.Tensor): Classification probability
......
mmdet3d/models/dense_heads/parta2_rpn_head.py
View file @ 80b39bd0
......@@ -11,7 +11,7 @@ from .anchor3d_head import Anchor3DHead
@HEADS.register_module()
class PartA2RPNHead(Anchor3DHead):
"""RPN head for PartA2
"""RPN head for PartA2.
Note:
The main difference between the PartA2 RPN head and the Anchor3DHead
......
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