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Functions725 in github.com/BAI-Yeqi/OpenPCSeg

⨍ Functions 725◇ Types & classes 120
Method__getitem__
(self, index)
pcseg/data/dataset/waymo/waymo_cylinder.py:83
Method__getitem__
(self, index)
pcseg/data/dataset/waymo/waymo_fusion.py:56
Method__getitem__
(self, index)
pcseg/data/dataset/waymo/waymo_infer.py:56
Method__getitem__
(self, index)
pcseg/data/dataset/waymo/waymo.py:75
Method__getitem__
(self, index)
pcseg/data/dataset/waymo/waymo_voxel.py:67
Method__getstate__
(self)
pcseg/data/dataset/base.py:61
Method__init__
(self, args, cfgs)
train.py:115
Method__init__
(self, args, cfgs)
infer.py:115
Method__init__
(self)
tools/utils/common/lovasz_losses.py:135
Method__init__
(self)
tools/utils/common/common_utils.py:253
Method__init__
(self, lb_smooth=0.1, reduction='mean', ignore_index=-100, weight=None)
tools/utils/train/loss.py:15
Method__init__
Args: gamma: Weighting parameter to balance loss for hard and easy examples. alpha: Weighting parameter to balance lo
tools/utils/train/loss.py:72
Method__init__
Args: beta: Scalar float. L1 to L2 change point. For beta values < 1e-5, L1 loss is computed.
tools/utils/train/loss.py:142
Method__init__
(self)
tools/utils/train/loss.py:244
Method__init__
(self)
tools/utils/train/loss.py:364
Method__init__
(self)
tools/utils/train/loss.py:427
Method__init__
(self, points, bbox3d=None, save_path="pic",
tools/scripts/vis_waymo.py:112
Method__init__
(self, points, bbox3d=None, save_path="pic",
tools/visualizer/vis_SemanticKITTI.py:88
Method__init__
(self, fai_optimizer: OptimWrapper, total_step, lr_phases, mom_phases)
pcseg/optim/learning_schedules_fastai.py:13
Method__init__
(self, optimizer, T_max, eta_min=0, last_epoch=-1)
pcseg/optim/learning_schedules_fastai.py:81
Method__init__
(self)
pcseg/optim/learning_schedules_fastai.py:93
Method__init__
(self, opt, wd, true_wd: bool = False, bn_wd: bool = True)
pcseg/optim/fastai_optim.py:107
Method__init__
( self, model_cfgs, num_class: int, )
pcseg/model/segmentor/base_segmentors.py:7
Method__init__
(self, in_filters, out_filters)
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:95
Method__init__
(self, in_filters, out_filters, dropout_rate, kernel_size=(3, 3), stride=1, pooling=True, dro
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:122
Method__init__
(self, in_filters, out_filters, dropout_rate=0.2, drop_out=True, mid_filters=None)
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:170
Method__init__
(self, model_cfgs, input_channels=5)
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:206
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:266
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, if_
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:293
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:320
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/fusion/rpvnet/rpvnet.py:369
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/fusion/spvcnn/spvcnn.py:35
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, if_
pcseg/model/segmentor/fusion/spvcnn/spvcnn.py:62
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/fusion/spvcnn/spvcnn.py:89
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/fusion/spvcnn/spvcnn.py:138
Method__init__
(self, classes='present', per_image=False, ignore=None)
pcseg/model/segmentor/range/utils.py:510
Method__init__
:param weight: <torch.FloatTensor: n_class>. Optional scalar weight for each class. :param ignore_index: Label id to ignore when cal
pcseg/model/segmentor/range/utils.py:528
Method__init__
:param reduction: Specifies the reduction to apply to the output. Can be 'none', 'mean' or 'sum'. :param ignore_index: Label id to ig
pcseg/model/segmentor/range/utils.py:643
Method__init__
(self, theta0=3, theta=5)
pcseg/model/segmentor/range/utils.py:672
Method__init__
(self, strategy,)
pcseg/model/segmentor/range/utils.py:729
Method__init__
(self, strategy,)
pcseg/model/segmentor/range/utils.py:1849
Method__init__
(self, n_classes, ignore=None)
pcseg/model/segmentor/range/torch_ioueval.py:7
Method__init__
(self, n_classes, ignore=None)
pcseg/model/segmentor/range/np_ioueval.py:5
Method__init__
(self, in_filters, out_filters)
pcseg/model/segmentor/range/salsanext/model/semantic/salsanext.py:10
Method__init__
( self, in_filters: int, out_filters: int, dropout_rate: float, kernel
pcseg/model/segmentor/range/salsanext/model/semantic/salsanext.py:41
Method__init__
( self, model_cfgs, num_class: int, )
pcseg/model/segmentor/range/salsanext/model/semantic/salsanext.py:178
Method__init__
( self, in_planes: int, out_planes: int, kernel_size: int, stride: int
pcseg/model/segmentor/range/cenet/model/semantic/cenet.py:30
Method__init__
(self, backbone_net, semantic_head)
pcseg/model/segmentor/range/cenet/model/semantic/cenet.py:61
Method__init__
( self, inplanes: int, planes: int, stride: int = 1, downsample = None
pcseg/model/segmentor/range/cenet/model/semantic/cenet.py:75
Method__init__
(self, inplanes, planes, bn_d=0.1)
pcseg/model/segmentor/range/rangenet/module/darknet.py:6
Method__init__
(self)
pcseg/model/segmentor/range/rangenet/module/darknet.py:43
Method__init__
(self, params, nclasses)
pcseg/model/segmentor/range/rangenet/postproc/KNN.py:37
Method__init__
Get the binary border mask of a labeled 2d range image. Args: nclasses(int) : The number of classes labeled in the input image
pcseg/model/segmentor/range/rangenet/postproc/borderMask.py:93
Method__init__
(self, h, w, sigma, nclasses)
pcseg/model/segmentor/range/rangenet/postproc/CRF.py:13
Method__init__
( self, model_cfgs, num_class: int, )
pcseg/model/segmentor/range/rangenet/model/semantic/rangenet.py:15
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, if_BN=None)
pcseg/model/segmentor/range/fidnet/model/semantic/fidnet.py:98
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, if_BN=None)
pcseg/model/segmentor/range/fidnet/model/semantic/fidnet.py:133
Method__init__
(self, num_class, input_channel=1024)
pcseg/model/segmentor/range/fidnet/model/semantic/fidnet.py:171
Method__init__
(self, block, layers, if_BN, if_remission, if_range, with_normal, norm_layer=None, groups=1, width_per_group=6
pcseg/model/segmentor/range/fidnet/model/semantic/fidnet.py:198
Method__init__
(self, classes='present', per_image=False, ignore=None)
pcseg/model/segmentor/range/fidnet/model/semantic/utils.py:510
Method__init__
:param weight: <torch.FloatTensor: n_class>. Optional scalar weight for each class. :param ignore_index: Label id to ignore when cal
pcseg/model/segmentor/range/fidnet/model/semantic/utils.py:528
Method__init__
:param reduction: Specifies the reduction to apply to the output. Can be 'none', 'mean' or 'sum'. :param ignore_index: Label id to ig
pcseg/model/segmentor/range/fidnet/model/semantic/utils.py:643
Method__init__
(self, theta0=3, theta=5)
pcseg/model/segmentor/range/fidnet/model/semantic/utils.py:672
Method__init__
(self, strategy,)
pcseg/model/segmentor/range/fidnet/model/semantic/utils.py:729
Method__init__
(self, strategy,)
pcseg/model/segmentor/range/fidnet/model/semantic/utils.py:1849
Method__init__
(self, n_classes, ignore=None)
pcseg/model/segmentor/range/fidnet/model/semantic/torch_ioueval.py:7
Method__init__
(self, n_classes, ignore=None)
pcseg/model/segmentor/range/fidnet/model/semantic/np_ioueval.py:5
Method__init__
(self, in_filters: int, out_filters: int, kernel_size: tuple = (3, 3, 3), stri
pcseg/model/segmentor/voxel/cylinder3d/cylinder_ts.py:89
Method__init__
( self, in_filters: int, out_filters: int, dropout_rate: float, kernel
pcseg/model/segmentor/voxel/cylinder3d/cylinder_ts.py:159
Method__init__
(self, in_filters: int, out_filters: int, kernel_size: tuple = (3, 3, 3), stri
pcseg/model/segmentor/voxel/cylinder3d/cylinder_ts.py:338
Method__init__
( self, model_cfgs, num_class: int = 20, )
pcseg/model/segmentor/voxel/cylinder3d/cylinder_ts.py:389
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/voxel/minkunet/minkunet.py:32
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, if_
pcseg/model/segmentor/voxel/minkunet/minkunet.py:59
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/voxel/minkunet/minkunet.py:86
Method__init__
( self, inc: int, outc: int, ks: int = 3, stride: int = 1, dil
pcseg/model/segmentor/voxel/minkunet/minkunet.py:135
Method__init__
(self, dataset, num_replicas=None, rank=None, shuffle=True)
pcseg/data/__init__.py:25
Method__init__
( self, data_cfgs=None, class_names=None, training=True, root_path=Non
pcseg/data/dataset/base.py:15
Method__init__
( self, nclasses: int, sem_color_dict = None, project: bool = True, H: int = 64
pcseg/data/dataset/semantickitti/laserscan.py:245
Method__init__
( self, data_cfgs = None, training = True, root_path = None, logger =
pcseg/data/dataset/semantickitti/semantickitti_cylinder.py:49
Method__init__
( self, data_cfgs = None, training: bool = True, root_path: bool = None,
pcseg/data/dataset/semantickitti/semantickitti_rv.py:17
Method__init__
(self, strategy,)
pcseg/data/dataset/semantickitti/semantickitti_rv.py:362
Method__init__
( self, data_cfgs=None, training=True, root_path=None, logger=None,
pcseg/data/dataset/semantickitti/semantickitti_voxel.py:18
Method__init__
( self, data_cfgs=None, training: bool = True, class_names: list = None,
pcseg/data/dataset/semantickitti/semantickitti.py:20
Method__init__
( self, data_cfgs=None, training=True, root_path=None, logger=None
pcseg/data/dataset/semantickitti/semantickitti_fusion.py:21
Method__init__
( self, data_cfgs = None, training = True, root_path = None, logger =
pcseg/data/dataset/waymo/waymo_cylinder.py:42
Method__init__
( self, data_cfgs=None, training=True, root_path=None, logger=None
pcseg/data/dataset/waymo/waymo_fusion.py:15
Method__init__
( self, data_cfgs=None, training: bool = True, class_names: list = None,
pcseg/data/dataset/waymo/waymo_infer.py:12
Method__init__
( self, data_cfgs=None, training: bool = True, class_names: list = None,
pcseg/data/dataset/waymo/waymo.py:8
Method__init__
( self, data_cfgs=None, training=True, root_path=None, logger=None,
pcseg/data/dataset/waymo/waymo_voxel.py:14
Method__init__
(self, smooth=1, p=2, reduction='mean')
pcseg/loss/dice_loss_v1.py:39
Method__init__
(self, gamma=0, alpha=None, size_average=True, loss_weight=1.0,ignore_index=None)
pcseg/loss/focalloss.py:7
Method__init__
( self, loss_types: list, loss_weights: list, cls_num_pts: list = None,
pcseg/loss/__init__.py:16
Method__init__
nsample: KNN -> K neighbor of current point
pcseg/loss/geo_loss.py:10
Method__init__
(self, ignore_index=-1, num_per_class=None, class_names=Non
pcseg/loss/group_softmax.py:20
Method__init__
(self, smooth=1, p=2, reduction='mean')
pcseg/loss/dice_loss_v0.py:39
Method__init__
Args: cls_num_pts (list): num_points of each class in the whole dataset normal_wce (bools): whether normalize weights
pcseg/loss/wce_loss.py:6
Method__init__
(self, ignore_index=None, use_sigmoid=True, reduction='mean
pcseg/loss/eqlv2.py:9
Method__init__
(self, ignore_index, label_smoothing, cls_num_pts, normal_w=False, w_dice=0.8, w_cross=0.
pcseg/loss/ell_loss.py:58
Method__init__
(self, ignore_index=-1, num_per_class=None, class_names=Non
pcseg/loss/group_softmax_fgbg_2.py:22
Method__iter__
(self)
pcseg/data/__init__.py:29
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