SYMBOL INDEX (286 symbols across 25 files)

FILE: datasets/__init__.py
  function get_dataset (line 8) | def get_dataset(config, type='train', **kwargs):

FILE: datasets/base_dataset.py
  class BaseDataset (line 7) | class BaseDataset:
    method __init__ (line 8) | def __init__(self, path, split, category_name="Car", **kwargs):
    method get_num_tracklets (line 15) | def get_num_tracklets(self):
    method get_num_frames_total (line 18) | def get_num_frames_total(self):
    method get_num_frames_tracklet (line 21) | def get_num_frames_tracklet(self, tracklet_id):
    method get_frames (line 24) | def get_frames(self, seq_id, frame_ids):

FILE: datasets/data_classes.py
  class PointCloud (line 11) | class PointCloud:
    method __init__ (line 13) | def __init__(self, points):
    method load_pcd_bin (line 23) | def load_pcd_bin(file_name):
    method from_file (line 34) | def from_file(cls, file_name):
    method nbr_points (line 50) | def nbr_points(self):
    method subsample (line 57) | def subsample(self, ratio):
    method remove_close (line 67) | def remove_close(self, radius):
    method translate (line 79) | def translate(self, x):
    method rotate (line 88) | def rotate(self, rot_matrix):
    method transform (line 96) | def transform(self, transf_matrix):
    method convertToPytorch (line 105) | def convertToPytorch(self):
    method fromPytorch (line 113) | def fromPytorch(cls, pytorchTensor):
    method normalize (line 123) | def normalize(self, wlh):
  class Box (line 128) | class Box:
    method __init__ (line 131) | def __init__(self, center, size, orientation, label=np.nan, score=np.n...
    method __eq__ (line 156) | def __eq__(self, other):
    method __repr__ (line 167) | def __repr__(self):
    method encode (line 177) | def encode(self):
    method decode (line 185) | def decode(cls, data):
    method rotation_matrix (line 195) | def rotation_matrix(self):
    method translate (line 202) | def translate(self, x):
    method rotate (line 210) | def rotate(self, quaternion):
    method transform (line 220) | def transform(self, transf_matrix):
    method corners (line 226) | def corners(self, wlh_factor=1.0):
    method bottom_corners (line 252) | def bottom_corners(self):

FILE: datasets/generate_waymo_sot.py
  function lood_pickle (line 15) | def lood_pickle(root):
  function generate_waymo_data (line 21) | def generate_waymo_data(root, cla, split):

FILE: datasets/kitti.py
  class kittiDataset (line 18) | class kittiDataset(base_dataset.BaseDataset):
    method __init__ (line 19) | def __init__(self, path, split, category_name="Car", **kwargs):
    method _build_scene_list (line 36) | def _build_scene_list(split):
    method _load_data (line 58) | def _load_data(self):
    method get_num_scenes (line 79) | def get_num_scenes(self):
    method get_num_tracklets (line 82) | def get_num_tracklets(self):
    method get_num_frames_total (line 85) | def get_num_frames_total(self):
    method get_num_frames_tracklet (line 88) | def get_num_frames_tracklet(self, tracklet_id):
    method _build_tracklet_anno (line 91) | def _build_tracklet_anno(self):
    method get_frames (line 130) | def get_frames(self, seq_id, frame_ids):
    method _get_frame_from_anno (line 139) | def _get_frame_from_anno(self, anno):
    method _read_calib_file (line 192) | def _read_calib_file(filepath):

FILE: datasets/nuscenes_data.py
  class NuScenesDataset (line 58) | class NuScenesDataset(base_dataset.BaseDataset):
    method __init__ (line 59) | def __init__(self, path, split, category_name="Car", version='v1.0-tra...
    method filter_instance (line 71) | def filter_instance(self, split, category_name=None, min_points=-1):
    method _build_tracklet_anno (line 93) | def _build_tracklet_anno(self):
    method _load_data (line 115) | def _load_data(self):
    method get_num_tracklets (line 136) | def get_num_tracklets(self):
    method get_num_frames_total (line 139) | def get_num_frames_total(self):
    method get_num_frames_tracklet (line 142) | def get_num_frames_tracklet(self, tracklet_id):
    method get_frames (line 145) | def get_frames(self, seq_id, frame_ids):
    method _get_frame_from_anno_data (line 154) | def _get_frame_from_anno_data(self, anno):

FILE: datasets/points_utils.py
  function random_choice (line 11) | def random_choice(num_samples, size, replacement=False, seed=None):
  function regularize_pc (line 24) | def regularize_pc(points, sample_size, seed=None):
  function getOffsetBB (line 43) | def getOffsetBB(box, offset, degrees=True, use_z=False, limit_box=True, ...
  function getModel (line 88) | def getModel(PCs, boxes, offset=0, scale=1.0, normalize=False):
  function cropAndCenterPC (line 103) | def cropAndCenterPC(PC, box, offset=0, scale=1.0, normalize=False):
  function get_point_to_box_distance (line 127) | def get_point_to_box_distance(pc, box, wlh_factor=1.0):
  function crop_pc_axis_aligned (line 146) | def crop_pc_axis_aligned(PC, box, offset=0, scale=1.0, return_mask=False):
  function crop_pc_oriented (line 174) | def crop_pc_oriented(PC, box, offset=0, scale=1.0, return_mask=False):
  function generate_subwindow (line 218) | def generate_subwindow(pc, sample_bb, scale, offset=2, oriented=True):
  function transform_box (line 253) | def transform_box(box, ref_box, inplace=False):
  function transform_pc (line 261) | def transform_pc(pc, ref_box, inplace=False):
  function get_in_box_mask (line 269) | def get_in_box_mask(PC, box):
  function apply_transform (line 299) | def apply_transform(in_box_pc, box, translation, rotation, flip_x, flip_...
  function apply_augmentation (line 348) | def apply_augmentation(pc, box, wlh_factor=1.25):
  function roty_batch_tensor (line 364) | def roty_batch_tensor(t):
  function rotz_batch_tensor (line 377) | def rotz_batch_tensor(t):
  function get_offset_points_tensor (line 390) | def get_offset_points_tensor(points, ref_box_params, offset_box_params):
  function get_offset_box_tensor (line 418) | def get_offset_box_tensor(ref_box_params, offset_box_params):
  function remove_transform_points_tensor (line 437) | def remove_transform_points_tensor(points, ref_box_params):
  function np_to_torch_tensor (line 454) | def np_to_torch_tensor(data, device=None):

FILE: datasets/sampler.py
  function no_processing (line 12) | def no_processing(data, *args):
  function siamese_processing (line 16) | def siamese_processing(data, config, template_transform=None, search_tra...
  function motion_processing (line 82) | def motion_processing(data, config, template_transform=None, search_tran...
  class PointTrackingSampler (line 183) | class PointTrackingSampler(torch.utils.data.Dataset):
    method __init__ (line 184) | def __init__(self, dataset, random_sample, sample_per_epoch=10000, pro...
    method get_anno_index (line 206) | def get_anno_index(self, index):
    method get_candidate_index (line 209) | def get_candidate_index(self, index):
    method __len__ (line 212) | def __len__(self):
    method __getitem__ (line 218) | def __getitem__(self, index):
  class TestTrackingSampler (line 246) | class TestTrackingSampler(torch.utils.data.Dataset):
    method __init__ (line 247) | def __init__(self, dataset, config=None, **kwargs):
    method __len__ (line 253) | def __len__(self):
    method __getitem__ (line 256) | def __getitem__(self, index):
  class MotionTrackingSampler (line 262) | class MotionTrackingSampler(PointTrackingSampler):
    method __init__ (line 263) | def __init__(self, dataset, config=None, **kwargs):
    method __getitem__ (line 267) | def __getitem__(self, index):

FILE: datasets/searchspace.py
  class SearchSpace (line 6) | class SearchSpace(object):
    method reset (line 8) | def reset(self):
    method sample (line 11) | def sample(self):
    method addData (line 14) | def addData(self, data, score):
  class ExhaustiveSearch (line 18) | class ExhaustiveSearch(SearchSpace):
    method __init__ (line 20) | def __init__(self,
    method reset (line 42) | def reset(self):
    method sample (line 45) | def sample(self, n=0):
  class ParticleFiltering (line 49) | class ParticleFiltering(SearchSpace):
    method __init__ (line 50) | def __init__(self, bnd=[1, 1, 10]):
    method sample (line 54) | def sample(self, n=10):
    method addData (line 71) | def addData(self, data, score):
    method reset (line 76) | def reset(self):
  class KalmanFiltering (line 85) | class KalmanFiltering(SearchSpace):
    method __init__ (line 86) | def __init__(self, bnd=[1, 1, 10]):
    method sample (line 90) | def sample(self, n=10):
    method addData (line 93) | def addData(self, data, score):
    method reset (line 100) | def reset(self):
  class GaussianMixtureModel (line 110) | class GaussianMixtureModel(SearchSpace):
    method __init__ (line 112) | def __init__(self, n_comp=5, dim=3):
    method sample (line 116) | def sample(self, n=10):
    method addData (line 157) | def addData(self, data, score):
    method reset (line 173) | def reset(self, n_comp=5):

FILE: datasets/utils.py
  function roty (line 10) | def roty(t):
  function get_3d_box (line 18) | def get_3d_box(box_size, heading_angle, center):
  function write_ply (line 39) | def write_ply(verts, colors, indices, output_file):
  function box2obj (line 66) | def box2obj(box, objname):
  function write_bbox (line 79) | def write_bbox(corners, mode, output_file):
  function write_obj (line 209) | def write_obj(points, file, rgb=False):

FILE: datasets/waymo_data.py
  class WaymoDataset (line 21) | class WaymoDataset(base_dataset.BaseDataset):
    method __init__ (line 22) | def __init__(self, path, split, category_name="VEHICLE", **kwargs):
    method _load_data (line 48) | def _load_data(self):
    method get_num_scenes (line 77) | def get_num_scenes(self):
    method get_num_tracklets (line 80) | def get_num_tracklets(self):
    method get_num_frames_total (line 83) | def get_num_frames_total(self):
    method get_num_frames_tracklet (line 86) | def get_num_frames_tracklet(self, tracklet_id):
    method _build_tracklet_anno (line 89) | def _build_tracklet_anno(self):
    method get_frames (line 109) | def get_frames(self, seq_id, frame_ids):
    method _get_frame_from_anno (line 118) | def _get_frame_from_anno(self, anno, track_id=None, check=False):
    method veh_pos_to_transform (line 170) | def veh_pos_to_transform(veh_pos):

FILE: main.py
  function load_yaml (line 23) | def load_yaml(file_name):
  function parse_config (line 32) | def parse_config():

FILE: models/__init__.py
  function get_model (line 19) | def get_model(name):

FILE: models/backbone/pointnet.py
  class Pointnet_Backbone (line 12) | class Pointnet_Backbone(nn.Module):
    method __init__ (line 28) | def __init__(self, use_fps=False, normalize_xyz=False, return_intermed...
    method _break_up_pc (line 60) | def _break_up_pc(self, pc):
    method forward (line 66) | def forward(self, pointcloud, numpoints):
  class MiniPointNet (line 91) | class MiniPointNet(nn.Module):
    method __init__ (line 93) | def __init__(self, input_channel, per_point_mlp, hidden_mlp, output_si...
    method forward (line 128) | def forward(self, x):
  class SegPointNet (line 144) | class SegPointNet(nn.Module):
    method __init__ (line 146) | def __init__(self, input_channel, per_point_mlp1, per_point_mlp2, outp...
    method forward (line 184) | def forward(self, x):

FILE: models/base_model.py
  class BaseModel (line 17) | class BaseModel(pl.LightningModule):
    method __init__ (line 18) | def __init__(self, config=None, **kwargs):
    method configure_optimizers (line 28) | def configure_optimizers(self):
    method compute_loss (line 38) | def compute_loss(self, data, output):
    method build_input_dict (line 41) | def build_input_dict(self, sequence, frame_id, results_bbs, **kwargs):
    method evaluate_one_sample (line 44) | def evaluate_one_sample(self, data_dict, ref_box):
    method evaluate_one_sequence (line 59) | def evaluate_one_sequence(self, sequence):
    method validation_step (line 88) | def validation_step(self, batch, batch_idx):
    method validation_epoch_end (line 97) | def validation_epoch_end(self, outputs):
    method test_step (line 103) | def test_step(self, batch, batch_idx):
    method test_epoch_end (line 113) | def test_epoch_end(self, outputs):
  class MatchingBaseModel (line 120) | class MatchingBaseModel(BaseModel):
    method compute_loss (line 122) | def compute_loss(self, data, output):
    method generate_template (line 166) | def generate_template(self, sequence, current_frame_id, results_bbs):
    method generate_search_area (line 197) | def generate_search_area(self, sequence, current_frame_id, results_bbs):
    method prepare_input (line 220) | def prepare_input(self, template_pc, search_pc, template_box, *args, *...
    method build_input_dict (line 240) | def build_input_dict(self, sequence, frame_id, results_bbs, **kwargs):
  class MotionBaseModel (line 250) | class MotionBaseModel(BaseModel):
    method __init__ (line 251) | def __init__(self, config, **kwargs):
    method build_input_dict (line 255) | def build_input_dict(self, sequence, frame_id, results_bbs):

FILE: models/bat.py
  class BAT (line 17) | class BAT(base_model.MatchingBaseModel):
    method __init__ (line 18) | def __init__(self, config=None, **kwargs):
    method prepare_input (line 41) | def prepare_input(self, template_pc, search_pc, template_box):
    method compute_loss (line 57) | def compute_loss(self, data, output):
    method forward (line 67) | def forward(self, input_dict):
    method training_step (line 114) | def training_step(self, batch, batch_idx):

FILE: models/head/rpn.py
  class P2BVoteNetRPN (line 12) | class P2BVoteNetRPN(nn.Module):
    method __init__ (line 14) | def __init__(self, feature_channel, vote_channel=256, num_proposal=64,...
    method forward (line 41) | def forward(self, xyz, feature):

FILE: models/head/xcorr.py
  class BaseXCorr (line 10) | class BaseXCorr(nn.Module):
    method __init__ (line 11) | def __init__(self, in_channel, hidden_channel, out_channel):
  class P2B_XCorr (line 20) | class P2B_XCorr(BaseXCorr):
    method __init__ (line 21) | def __init__(self, feature_channel, hidden_channel, out_channel):
    method forward (line 25) | def forward(self, template_feature, search_feature, template_xyz):
  class BoxAwareXCorr (line 56) | class BoxAwareXCorr(BaseXCorr):
    method __init__ (line 57) | def __init__(self, feature_channel, hidden_channel, out_channel, k=8, ...
    method forward (line 67) | def forward(self, template_feature, search_feature, template_xyz,

FILE: models/m2track.py
  class M2TRACK (line 17) | class M2TRACK(base_model.MotionBaseModel):
    method __init__ (line 18) | def __init__(self, config, **kwargs):
    method forward (line 73) | def forward(self, input_dict):
    method compute_loss (line 153) | def compute_loss(self, data, output):
    method training_step (line 233) | def training_step(self, batch, batch_idx):

FILE: models/p2b.py
  class P2B (line 13) | class P2B(base_model.MatchingBaseModel):
    method __init__ (line 14) | def __init__(self, config=None, **kwargs):
    method forward (line 28) | def forward(self, input_dict):
    method training_step (line 61) | def training_step(self, batch, batch_idx):

FILE: pointnet2/utils/linalg_utils.py
  function pdist2 (line 15) | def pdist2(X, Z=None, order=PDist2Order.d_second):
  function pdist2_slow (line 66) | def pdist2_slow(X, Z=None):

FILE: pointnet2/utils/pointnet2_modules.py
  class _PointnetSAModuleBase (line 24) | class _PointnetSAModuleBase(nn.Module):
    method __init__ (line 25) | def __init__(self, use_fps=False):
    method forward (line 31) | def forward(self, xyz, features, npoint, return_idx=False):
  class PointnetSAModuleMSG (line 82) | class PointnetSAModuleMSG(_PointnetSAModuleBase):
    method __init__ (line 99) | def __init__(self, radii, nsamples, mlps, bn=True, use_xyz=True, use_f...
  class PointnetSAModule (line 120) | class PointnetSAModule(PointnetSAModuleMSG):
    method __init__ (line 137) | def __init__(
  class PointnetFPModule (line 152) | class PointnetFPModule(nn.Module):
    method __init__ (line 163) | def __init__(self, mlp, bn=True):
    method forward (line 168) | def forward(self, unknown, known, unknow_feats, known_feats):
  class FlowEmbedding (line 215) | class FlowEmbedding(nn.Module):
    method __init__ (line 218) | def __init__(self, radius, nsample, in_channel, mlp, pooling='max', co...
    method forward (line 234) | def forward(self, xyz1, xyz2, feature1, feature2):
  class PointNetSetUpConv (line 272) | class PointNetSetUpConv(nn.Module):
    method __init__ (line 273) | def __init__(self, nsample, radius, f1_channel, f2_channel, mlp, mlp2,...
    method forward (line 296) | def forward(self, xyz1, xyz2, feature1, feature2):

FILE: pointnet2/utils/pointnet2_utils.py
  class RandomDropout (line 24) | class RandomDropout(nn.Module):
    method __init__ (line 25) | def __init__(self, p=0.5, inplace=False):
    method forward (line 30) | def forward(self, X):
  class FurthestPointSampling (line 35) | class FurthestPointSampling(Function):
    method forward (line 37) | def forward(ctx, xyz, npoint):
    method backward (line 61) | def backward(xyz, a=None):
  class GatherOperation (line 68) | class GatherOperation(Function):
    method forward (line 70) | def forward(ctx, features, idx):
    method backward (line 95) | def backward(ctx, grad_out):
  class ThreeNN (line 105) | class ThreeNN(Function):
    method forward (line 107) | def forward(ctx, unknown, known):
    method backward (line 130) | def backward(ctx, a=None, b=None):
  class ThreeInterpolate (line 137) | class ThreeInterpolate(Function):
    method forward (line 139) | def forward(ctx, features, idx, weight):
    method backward (line 165) | def backward(ctx, grad_out):
  class GroupingOperation (line 194) | class GroupingOperation(Function):
    method forward (line 196) | def forward(ctx, features, idx):
    method backward (line 220) | def backward(ctx, grad_out):
  class BallQuery (line 245) | class BallQuery(Function):
    method forward (line 247) | def forward(ctx, radius, nsample, xyz, new_xyz):
    method backward (line 273) | def backward(ctx, a=None):
  class QueryAndGroup (line 280) | class QueryAndGroup(nn.Module):
    method __init__ (line 292) | def __init__(self, radius, nsample, use_xyz=True, return_idx=False, no...
    method forward (line 299) | def forward(self, xyz, new_xyz, features=None):
  class GroupAll (line 342) | class GroupAll(nn.Module):
    method __init__ (line 350) | def __init__(self, use_xyz=True):
    method forward (line 355) | def forward(self, xyz, new_xyz, features=None):
  function knn_point (line 388) | def knn_point(k, points1, points2):

FILE: pointnet2/utils/pytorch_utils.py
  class SharedMLP (line 12) | class SharedMLP(nn.Sequential):
    method __init__ (line 14) | def __init__(
  class _BNBase (line 40) | class _BNBase(nn.Sequential):
    method __init__ (line 42) | def __init__(self, in_size, batch_norm=None, name=""):
  class BatchNorm1d (line 50) | class BatchNorm1d(_BNBase):
    method __init__ (line 52) | def __init__(self, in_size: int, *, name: str = ""):
  class BatchNorm2d (line 56) | class BatchNorm2d(_BNBase):
    method __init__ (line 58) | def __init__(self, in_size: int, name: str = ""):
  class BatchNorm3d (line 62) | class BatchNorm3d(_BNBase):
    method __init__ (line 64) | def __init__(self, in_size: int, name: str = ""):
  class _ConvBase (line 68) | class _ConvBase(nn.Sequential):
    method __init__ (line 70) | def __init__(
  class Conv1d (line 124) | class Conv1d(_ConvBase):
    method __init__ (line 126) | def __init__(
  class Conv2d (line 158) | class Conv2d(_ConvBase):
    method __init__ (line 160) | def __init__(
  class Conv3d (line 192) | class Conv3d(_ConvBase):
    method __init__ (line 194) | def __init__(
  class FC (line 226) | class FC(nn.Sequential):
    method __init__ (line 228) | def __init__(
  function set_bn_momentum_default (line 263) | def set_bn_momentum_default(bn_momentum):
  class BNMomentumScheduler (line 272) | class BNMomentumScheduler(object):
    method __init__ (line 274) | def __init__(
    method step (line 292) | def step(self, epoch=None):
  class Seq (line 300) | class Seq(nn.Sequential):
    method __init__ (line 302) | def __init__(self, input_channels):
    method conv1d (line 307) | def conv1d(self,
    method conv2d (line 341) | def conv2d(self,
    method conv3d (line 375) | def conv3d(self,
    method fc (line 409) | def fc(self,
    method dropout (line 432) | def dropout(self, p=0.5):
    method maxpool2d (line 439) | def maxpool2d(self,

FILE: utils/metrics.py
  class AverageMeter (line 8) | class AverageMeter(object):
    method __init__ (line 11) | def __init__(self):
    method reset (line 14) | def reset(self):
    method update (line 20) | def update(self, val, n=1):
  function estimateAccuracy (line 27) | def estimateAccuracy(box_a, box_b, dim=3, up_axis=(0, -1, 0)):
  function fromBoxToPoly (line 36) | def fromBoxToPoly(box, up_axis=(0, -1, 0)):
  function estimateOverlap (line 49) | def estimateOverlap(box_a, box_b, dim=2, up_axis=(0, -1, 0)):
  class TorchPrecision (line 75) | class TorchPrecision(Metric):
    method __init__ (line 78) | def __init__(self, n=21, max_accuracy=2, dist_sync_on_step=False):
    method value (line 84) | def value(self, accs):
    method update (line 91) | def update(self, val):
    method compute (line 94) | def compute(self):
  class TorchSuccess (line 101) | class TorchSuccess(Metric):
    method __init__ (line 104) | def __init__(self, n=21, max_overlap=1, dist_sync_on_step=False):
    method value (line 110) | def value(self, overlaps):
    method compute (line 117) | def compute(self):
    method update (line 124) | def update(self, val):