SYMBOL INDEX (839 symbols across 76 files)

FILE: paper_experiments/models/aligned_reid_model.py
  class Model (line 10) | class Model(nn.Module):
    method __init__ (line 11) | def __init__(self, local_conv_out_channels=128, num_classes=None):
    method forward (line 24) | def forward(self, x):
  function conv3x3 (line 60) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 66) | class BasicBlock(nn.Module):
    method __init__ (line 69) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 79) | def forward(self, x):
  class Bottleneck (line 98) | class Bottleneck(nn.Module):
    method __init__ (line 101) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 114) | def forward(self, x):
  class ResNet (line 137) | class ResNet(nn.Module):
    method __init__ (line 139) | def __init__(self, block, layers):
    method _make_layer (line 160) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 177) | def forward(self, x):
  function remove_fc (line 191) | def remove_fc(state_dict):
  function resnet18 (line 200) | def resnet18(pretrained=False):
  function resnet34 (line 212) | def resnet34(pretrained=False):
  function resnet50 (line 224) | def resnet50(pretrained=False):
  function resnet101 (line 236) | def resnet101(pretrained=False):
  function resnet152 (line 249) | def resnet152(pretrained=False):

FILE: paper_experiments/models/combination_model.py
  class CombiNet (line 6) | class CombiNet(nn.Module):
    method __init__ (line 7) | def __init__(self, in_dim = 2560, hidden_units = 512, out_dim = 2560):
    method forward (line 16) | def forward(self, x):
  class CombiLSTM (line 30) | class CombiLSTM(nn.Module):
    method __init__ (line 31) | def __init__(self, in_dim = 2560, hidden_units = 512, out_dim = 2560):
    method forward (line 43) | def forward(self, x, hidden = None):
  function weight_init (line 65) | def weight_init(m):

FILE: paper_experiments/models/deep_sort_model.py
  class ImageEncoder (line 5) | class ImageEncoder(object):
    method __init__ (line 7) | def __init__(self, checkpoint_filename="weights/deep_sort_weights.pb",...
    method __call__ (line 26) | def __call__(self, data_x):

FILE: paper_experiments/models/featurepointnet_model.py
  class FPointNet (line 13) | class FPointNet():
    method __init__ (line 14) | def __init__(self, config_path):
    method __call__ (line 57) | def __call__(self, input_point_cloud, rot_angle, peds=False):
    method get_instance_seg_v1_net (line 130) | def get_instance_seg_v1_net(self, point_cloud, one_hot_vec, is_trainin...
    method get_3d_box_estimation_v1_net (line 201) | def get_3d_box_estimation_v1_net(self, object_point_cloud, one_hot_vec...
    method get_model (line 250) | def get_model(self, point_cloud, one_hot_vec, is_training, bn_decay=No...
    method get_depth_feature_op (line 298) | def get_depth_feature_op(self, is_training):
    method get_depth_feature (line 321) | def get_depth_feature(self, object_pointcloud):
    method softmax (line 327) | def softmax(self, x):
  function create_depth_model (line 334) | def create_depth_model(model, config_path):

FILE: paper_experiments/models/pointnet_model.py
  class PointNet (line 9) | class PointNet():
    method __init__ (line 10) | def __init__(self, config_path):
    method __call__ (line 37) | def __call__(self, input_point_cloud):
    method placeholder_inputs (line 43) | def placeholder_inputs(self, batch_size, num_point):
    method get_model (line 49) | def get_model(self, point_cloud, is_training, bn_decay=None):
    method get_loss (line 96) | def get_loss(self, pred, label, end_points, reg_weight=0.001):

FILE: paper_experiments/models/resnet_reid_models.py
  class FeatureResNet (line 8) | class FeatureResNet(nn.Module):
    method __init__ (line 9) | def __init__(self,n_layers=50,pretrained=True):
    method forward (line 25) | def forward(self,x):
  class ResNet (line 30) | class ResNet(nn.Module):
    method __init__ (line 31) | def __init__(self,n_id,n_layers=50,pretrained=True):
    method forward (line 47) | def forward(self,x):
  class NLayersFC (line 54) | class NLayersFC(nn.Module):
    method __init__ (line 55) | def __init__(self, in_dim, out_dim, hidden_dim=1, n_layers=0):
    method forward (line 69) | def forward(self, x):
  class ICT_ResNet (line 72) | class ICT_ResNet(nn.Module):
    method __init__ (line 73) | def __init__(self,n_id,n_color,n_type,n_layers=50,pretrained=True):
    method forward (line 91) | def forward(self,x):
  class TripletNet (line 101) | class TripletNet(nn.Module):
    method __init__ (line 102) | def __init__(self, net):
    method forward (line 106) | def forward(self, x, y, z):

FILE: paper_experiments/models/yolo_models.py
  function create_modules (line 19) | def create_modules(module_defs):
  class EmptyLayer (line 94) | class EmptyLayer(nn.Module):
    method __init__ (line 97) | def __init__(self):
  class Interpolate (line 100) | class Interpolate(nn.Module):
    method __init__ (line 101) | def __init__(self, scale_factor, mode):
    method forward (line 107) | def forward(self, x):
  class YOLOLayer (line 111) | class YOLOLayer(nn.Module):
    method __init__ (line 114) | def __init__(self, anchors, num_classes, img_dim):
    method forward (line 128) | def forward(self, x, targets=None):
  class Darknet (line 240) | class Darknet(nn.Module):
    method __init__ (line 243) | def __init__(self, config_path):
    method forward (line 252) | def forward(self, x, targets=None):
    method load_weights (line 282) | def load_weights(self, weights_path):
    method save_weights (line 337) | def save_weights(self, path, cutoff=-1):

FILE: paper_experiments/track.py
  function parse_arguments (line 28) | def parse_arguments():
  function main (line 92) | def main(opt):

FILE: paper_experiments/utils/EKF.py
  function squared_mahalanobis_distance (line 79) | def squared_mahalanobis_distance(mean, covariance, measurements):
  class EKF (line 106) | class EKF(object):
    method __init__ (line 112) | def __init__(self):
    method initiate (line 115) | def initiate(self, measurement):
    method predict_mean (line 132) | def predict_mean(self, mean):
    method get_process_noise (line 138) | def get_process_noise(self, mean, covariance):
    method predict_covariance (line 141) | def predict_covariance(self, mean, covariance):
    method project_mean (line 144) | def project_mean(self, mean):
    method project_cov (line 149) | def project_cov(self, mean, covariance):
    method predict (line 152) | def predict(self, mean, covariance, last_detection, next_to_last_detec...
    method get_innovation_cov (line 176) | def get_innovation_cov(self, covariance):
    method project (line 179) | def project(self, mean, covariance):
    method update (line 200) | def update(self, mean, covariance, measurement_t, marginalization=None...

FILE: paper_experiments/utils/JPDA_matching.py
  function get_unmatched (line 8) | def get_unmatched(all_idx, matches, i, marginalization=None):
  class Matcher (line 19) | class Matcher:
    method __init__ (line 21) | def __init__(self, detections, marginalizations, confirmed_tracks,
    method match (line 31) | def match(self):
    method get_matches (line 37) | def get_matches(self):
    method get_unmatched_tracks (line 51) | def get_unmatched_tracks(self):
    method get_unmatched_detections (line 55) | def get_unmatched_detections(self):
    method max_match (line 58) | def max_match(self):
    method max_and_threshold_matching (line 84) | def max_and_threshold_matching(self):
    method hungarian (line 103) | def hungarian(self):

FILE: paper_experiments/utils/aligned_reid_utils.py
  function time_str (line 17) | def time_str(fmt=None):
  function load_pickle (line 23) | def load_pickle(path):
  function save_pickle (line 35) | def save_pickle(obj, path):
  function save_mat (line 42) | def save_mat(ndarray, path):
  function to_scalar (line 47) | def to_scalar(vt):
  function transfer_optim_state (line 58) | def transfer_optim_state(state, device_id=-1):
  function may_transfer_optims (line 83) | def may_transfer_optims(optims, device_id=-1):
  function may_transfer_modules_optims (line 96) | def may_transfer_modules_optims(modules_and_or_optims, device_id=-1):
  class TransferVarTensor (line 115) | class TransferVarTensor(object):
    method __init__ (line 118) | def __init__(self, device_id=-1):
    method __call__ (line 121) | def __call__(self, var_or_tensor):
  class TransferModulesOptims (line 126) | class TransferModulesOptims(object):
    method __init__ (line 129) | def __init__(self, device_id=-1):
    method __call__ (line 132) | def __call__(self, modules_and_or_optims):
  function set_devices (line 136) | def set_devices(sys_device_ids):
  function set_devices_for_ml (line 165) | def set_devices_for_ml(sys_device_ids):
  function load_ckpt (line 230) | def load_ckpt(modules_optims, ckpt_file, load_to_cpu=True, verbose=True):
  function save_ckpt (line 253) | def save_ckpt(modules_optims, ep, scores, ckpt_file):
  function load_state_dict (line 274) | def load_state_dict(model, src_state_dict):
  function is_iterable (line 315) | def is_iterable(obj):
  function may_set_mode (line 319) | def may_set_mode(maybe_modules, mode):
  function may_make_dir (line 332) | def may_make_dir(path):
  class AverageMeter (line 348) | class AverageMeter(object):
    method __init__ (line 352) | def __init__(self):
    method reset (line 358) | def reset(self):
    method update (line 364) | def update(self, val, n=1):
  class RunningAverageMeter (line 371) | class RunningAverageMeter(object):
    method __init__ (line 374) | def __init__(self, hist=0.99):
    method reset (line 379) | def reset(self):
    method update (line 383) | def update(self, val):
  class RecentAverageMeter (line 391) | class RecentAverageMeter(object):
    method __init__ (line 394) | def __init__(self, hist_size=100):
    method reset (line 399) | def reset(self):
    method update (line 403) | def update(self, val):
    method avg (line 410) | def avg(self):
  function get_model_wrapper (line 415) | def get_model_wrapper(model, multi_gpu):
  class ReDirectSTD (line 423) | class ReDirectSTD(object):
    method __init__ (line 443) | def __init__(self, fpath=None, console='stdout', immediately_visible=F...
    method __del__ (line 464) | def __del__(self):
    method __enter__ (line 467) | def __enter__(self):
    method __exit__ (line 470) | def __exit__(self, *args):
    method write (line 473) | def write(self, msg):
    method flush (line 485) | def flush(self):
    method close (line 492) | def close(self):
  function set_seed (line 498) | def set_seed(seed):
  function print_array (line 515) | def print_array(array, fmt='{:.2f}', end=' '):
  function str2bool (line 526) | def str2bool(v):
  function tight_float_str (line 530) | def tight_float_str(x, fmt='{:.4f}'):
  function find_index (line 534) | def find_index(seq, item):
  function adjust_lr_exp (line 541) | def adjust_lr_exp(optimizer, base_lr, ep, total_ep, start_decay_at_ep):
  function adjust_lr_staircase (line 573) | def adjust_lr_staircase(optimizer, base_lr, ep, decay_at_epochs, factor):
  function measure_time (line 609) | def measure_time(enter_msg):
  function generate_features (line 616) | def generate_features(appearance_model, patches, opt, object_ids = None):
  function generate_features_batched (line 645) | def generate_features_batched(appearance_model, patches, opt, object_ids...
  function get_image_patches (line 713) | def get_image_patches(input_img, detections):
  function create_appearance_model (line 735) | def create_appearance_model(model_type, alignreid_checkpoint, resnet_rei...

FILE: paper_experiments/utils/assign_ids_detections.py
  function assign_detection_id (line 11) | def assign_detection_id(detection_path, gt_path, conf_threshold = 0, iou...

FILE: paper_experiments/utils/calibration.py
  class Calibration (line 8) | class Calibration(object):
    method __init__ (line 33) | def __init__(self, calib_filepath):
    method read_calib_file (line 71) | def read_calib_file(self, filepath):
    method read_calib_from_video (line 92) | def read_calib_from_video(self, calib_root_dir):
    method cart2hom (line 107) | def cart2hom(self, pts_3d):
    method cart2hom_torch (line 115) | def cart2hom_torch(self, pts_3d):
    method project_velo_to_ref (line 123) | def project_velo_to_ref(self, pts_3d_velo):
    method project_ref_to_velo (line 127) | def project_ref_to_velo(self, pts_3d_ref):
    method project_rect_to_ref (line 131) | def project_rect_to_ref(self, pts_3d_rect):
    method project_ref_to_rect (line 135) | def project_ref_to_rect(self, pts_3d_ref):
    method project_ref_to_rect_torch (line 139) | def project_ref_to_rect_torch(self, pts_3d_ref):
    method project_rect_to_velo (line 143) | def project_rect_to_velo(self, pts_3d_rect):
    method project_velo_to_rect (line 150) | def project_velo_to_rect(self, pts_3d_velo):
    method project_rect_to_image (line 157) | def project_rect_to_image(self, pts_3d_rect):
    method project_rect_to_image_torch (line 167) | def project_rect_to_image_torch(self, pts_3d_rect):
    method project_ref_to_image_torch (line 177) | def project_ref_to_image_torch(self, pts_3d_ref):
    method project_velo_to_image (line 187) | def project_velo_to_image(self, pts_3d_velo):
    method project_image_to_rect (line 197) | def project_image_to_rect(self, uv_depth):
    method project_image_to_velo (line 211) | def project_image_to_velo(self, uv_depth):
  function rotx (line 215) | def rotx(t):
  function roty (line 224) | def roty(t):
  function rotz (line 233) | def rotz(t):
  function transform_from_rot_trans (line 242) | def transform_from_rot_trans(R, t):
  function inverse_rigid_trans (line 249) | def inverse_rigid_trans(Tr):
  function read_label (line 258) | def read_label(label_filename):
  function load_image (line 263) | def load_image(img_filename):
  function load_velo_scan (line 266) | def load_velo_scan(velo_filename):
  function project_to_image (line 271) | def project_to_image(pts_3d, P):
  function compute_box_3d (line 291) | def compute_box_3d(obj, P):
  function compute_orientation_3d (line 329) | def compute_orientation_3d(obj, P):
  function draw_projected_box3d (line 358) | def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
  class OmniCalibration (line 385) | class OmniCalibration(Calibration):
    method __init__ (line 386) | def __init__(self, calib_folder):
    method project_ref_to_image_torch (line 402) | def project_ref_to_image_torch(self, pointcloud):
    method project_image_to_rect (line 413) | def project_image_to_rect(self, uvdepth):
    method project_velo_to_ref (line 422) | def project_velo_to_ref(self, pointcloud):
    method move_lidar_to_camera_frame (line 430) | def move_lidar_to_camera_frame(self, pointcloud, upper = True):
    method calculate_median_param_value (line 445) | def calculate_median_param_value(self, param):

FILE: paper_experiments/utils/combine_and_process_detections.py
  function threshold (line 13) | def threshold(filename, thresh, min, max):

FILE: paper_experiments/utils/dataset.py
  class SequenceDataset (line 23) | class SequenceDataset(Dataset):
    method __init__ (line 24) | def __init__(self, folder_path, point_cloud=False, cuda=False, omni=Fa...
    method __getitem__ (line 44) | def __getitem__(self, index):
    method __len__ (line 75) | def __len__(self):
  function is_image_file (line 78) | def is_image_file(file):
  class TripletDataset (line 85) | class TripletDataset(Dataset):
    method __init__ (line 87) | def __init__(self, feature_path, num_negative_samples = 100, cuda = Tr...
    method __getitem__ (line 115) | def __getitem__(self, index):
    method __len__ (line 157) | def __len__(self):
  class STIPDataset (line 160) | class STIPDataset(Dataset):
    method __init__ (line 161) | def __init__(self, folder_path, img_size=416, point_cloud = False, pad...
    method __getitem__ (line 169) | def __getitem__(self, index):
    method __len__ (line 194) | def __len__(self):
  function collate_fn (line 197) | def collate_fn(inputs):

FILE: paper_experiments/utils/deep_sort_utils.py
  function non_max_suppression (line 6) | def non_max_suppression(boxes, max_bbox_overlap, scores=None):

FILE: paper_experiments/utils/detection.py
  class Detection (line 5) | class Detection(object):
    method __init__ (line 29) | def __init__(self, tlwh, box_3d, confidence, appearance_feature, featu...
    method to_tlbr (line 44) | def to_tlbr(self):
    method to_xyah (line 52) | def to_xyah(self):
    method to_xywh (line 60) | def to_xywh(self):
    method get_3d_distance (line 67) | def get_3d_distance(self):

FILE: paper_experiments/utils/double_measurement_kf.py
  class KF_3D (line 19) | class KF_3D(kf_2d.KalmanFilter2D):
    method __init__ (line 34) | def __init__(self, calib, pos_weight_3d, pos_weight, velocity_weight, ...
    method initiate (line 65) | def initiate(self, measurement_3d):
    method get_process_noise (line 84) | def get_process_noise(self, mean):
    method get_2d_measurement_noise (line 102) | def get_2d_measurement_noise(self, measurement_2d):
    method get_3d_measurement_noise (line 114) | def get_3d_measurement_noise(self, measurement):
    method gating_distance (line 130) | def gating_distance(self, mean, covariance, measurements,
    method project_cov (line 179) | def project_cov(self, mean, covariance):
    method project_cov_2d (line 188) | def project_cov_2d(self, mean, covariance, H_2d):
    method update (line 197) | def update(self, mean, covariance, measurement_2d, measurement_3d = No...
    method get_2d_measurement_matrix (line 301) | def get_2d_measurement_matrix(self, mean, corner_points, corner_points...
    method jacobian (line 338) | def jacobian(self, pt_3d):
    method jacobian_omni (line 344) | def jacobian_omni(self, pt_3d):
    method calculate_corners (line 360) | def calculate_corners(self, box):
    method corner_jacobian (line 379) | def corner_jacobian(self, pt_3d, corner_idx):
    method project_2d (line 406) | def project_2d(self, pts_3d):
  function swap (line 415) | def swap(detections_3d, iou, idx, swap_prob = 0):

FILE: paper_experiments/utils/evaluate_detections.py
  function evaluate_detections (line 11) | def evaluate_detections(detection_path_1, detection_path_2, detection_pa...
  function iou (line 99) | def iou(bbox_1, bbox_2):

FILE: paper_experiments/utils/featurepointnet_model_util.py
  function tf_gather_object_pc (line 39) | def tf_gather_object_pc(point_cloud, mask, npoints=512):
  function get_box3d_corners_helper (line 72) | def get_box3d_corners_helper(centers, headings, sizes):
  function get_box3d_corners (line 99) | def get_box3d_corners(center, heading_residuals, size_residuals):
  function huber_loss (line 124) | def huber_loss(error, delta):
  function parse_output_to_tensors (line 132) | def parse_output_to_tensors(output, end_points):
  function from_prediction_to_label_format (line 170) | def from_prediction_to_label_format(center, angle_class, angle_res,\
  function size2class (line 179) | def size2class(size, type_name):
  function class2size (line 194) | def class2size(pred_cls, residual):
  function angle2class (line 199) | def angle2class(angle, num_class):
  function class2angle (line 219) | def class2angle(pred_cls, residual, num_class, to_label_format=True):
  function rotate_pc_along_y (line 230) | def rotate_pc_along_y(pc, rot_angle):
  function placeholder_inputs (line 249) | def placeholder_inputs(batch_size, num_point):
  function point_cloud_masking (line 274) | def point_cloud_masking(point_cloud, logits, end_points, xyz_only=True):
  function get_center_regression_net (line 322) | def get_center_regression_net(object_point_cloud, one_hot_vec,
  function get_loss (line 360) | def get_loss(mask_label, center_label, \
  function get_lidar_in_image_fov (line 482) | def get_lidar_in_image_fov(pc_velo, calib, xmin, ymin, xmax, ymax,
  function preprocess_pointcloud (line 497) | def preprocess_pointcloud(detections, point_cloud, pc_image_coord,
  function generate_detections_3d (line 551) | def generate_detections_3d(detector, detections_2d, point_cloud, calib, ...
  function convert_depth_features (line 564) | def convert_depth_features(depth_features_orig, ids_3d, cuda = True):

FILE: paper_experiments/utils/featurepointnet_tf_util.py
  function _variable_on_cpu (line 10) | def _variable_on_cpu(name, shape, initializer, use_fp16=False):
  function _variable_with_weight_decay (line 24) | def _variable_with_weight_decay(name, shape, stddev, wd, use_xavier=True):
  function conv1d (line 52) | def conv1d(inputs,
  function conv2d (line 120) | def conv2d(inputs,
  function conv2d_transpose (line 188) | def conv2d_transpose(inputs,
  function conv3d (line 268) | def conv3d(inputs,
  function fully_connected (line 327) | def fully_connected(inputs,
  function max_pool2d (line 366) | def max_pool2d(inputs,
  function avg_pool2d (line 391) | def avg_pool2d(inputs,
  function max_pool3d (line 417) | def max_pool3d(inputs,
  function avg_pool3d (line 442) | def avg_pool3d(inputs,
  function batch_norm_template_unused (line 468) | def batch_norm_template_unused(inputs, is_training, scope, moments_dims,...
  function batch_norm_template (line 512) | def batch_norm_template(inputs, is_training, scope, moments_dims_unused,...
  function batch_norm_for_fc (line 534) | def batch_norm_for_fc(inputs, is_training, bn_decay, scope):
  function batch_norm_for_conv1d (line 548) | def batch_norm_for_conv1d(inputs, is_training, bn_decay, scope, data_for...
  function batch_norm_for_conv2d (line 565) | def batch_norm_for_conv2d(inputs, is_training, bn_decay, scope, data_for...
  function batch_norm_for_conv3d (line 580) | def batch_norm_for_conv3d(inputs, is_training, bn_decay, scope):
  function dropout (line 594) | def dropout(inputs,

FILE: paper_experiments/utils/imm.py
  class IMMFilter2D (line 11) | class IMMFilter2D(EKF.EKF):
    method __init__ (line 31) | def __init__(self, kf_vel_params=(1./20, 1./160, 1, 1, 2), kf_walk_par...
    method initiate (line 38) | def initiate(self, measurement, flow):
    method gating_distance (line 64) | def gating_distance(self, mean, covariance, measurements,
    method update (line 94) | def update(self, mean, covariance, measurement, model_probabilities, m...
    method predict (line 147) | def predict(self, mean, covariance, model_probabilities):
    method mix_models (line 176) | def mix_models(self, mean_1, cov_1, mean_2, cov_2, model_transition_pr...
    method combine_states (line 193) | def combine_states(mean, cov, model_probabilities):
  function generate_particle_motion (line 200) | def generate_particle_motion(motion_matrices, initial_state, process_noi...
  function generate_observations (line 215) | def generate_observations(input_state_list, observation_matrix, observat...

FILE: paper_experiments/utils/iou_matching.py
  function iou (line 8) | def iou(bbox, candidates):
  function iou_cost (line 43) | def iou_cost(tracks, detections, track_indices=None,

FILE: paper_experiments/utils/kf_2d.py
  class KalmanFilter2D (line 8) | class KalmanFilter2D(EKF.EKF):
    method __init__ (line 25) | def __init__(self, pos_weight, velocity_weight, std_process, std_measu...
    method initiate (line 47) | def initiate(self, measurement, flow):
    method predict_mean (line 87) | def predict_mean(self, mean):
    method predict_covariance (line 93) | def predict_covariance(self, mean, covariance, last_detection, next_to...
    method get_process_noise (line 101) | def get_process_noise(self, mean, last_detection, next_to_last_detecti...
    method project_mean (line 136) | def project_mean(self, mean):
    method get_measurement_noise (line 144) | def get_measurement_noise(self, measurement):
    method project_cov (line 156) | def project_cov(self, mean, covariance):
    method gating_distance (line 165) | def gating_distance(self, mean, covariance, measurements,
  class RandomWalkKalmanFilter2D (line 206) | class RandomWalkKalmanFilter2D(KalmanFilter2D): #TODO UPDATE THIS DOCUME...
    method __init__ (line 222) | def __init__(self, pos_weight, velocity_weight, std_process, std_measu...

FILE: paper_experiments/utils/kf_3d.py
  class KalmanFilter3D (line 8) | class KalmanFilter3D(EKF.EKF):
    method __init__ (line 24) | def __init__(self):
    method initiate (line 76) | def initiate(self, measurement):
    method motion_update (line 103) | def motion_update(self, mean, covariance):
    method get_motion_cov (line 110) | def get_motion_cov(self, mean, covariance):
    method sensor_update (line 115) | def sensor_update(self, mean, covariance):
    method get_innovation_cov (line 122) | def get_innovation_cov(self, mean, covariance):
    method adjust_angle (line 126) | def adjust_angle(self, measured, target):
    method update (line 131) | def update(self, mean, covariance, meas_in, marginalization=None, JPDA...
    method gating_distance (line 139) | def gating_distance(self, mean, covariance, measurements,

FILE: paper_experiments/utils/linear_assignment.py
  function min_marg_matching (line 14) | def min_marg_matching(marginalizations, track_indices=None, max_distance...
  function min_cost_matching (line 60) | def min_cost_matching(
  function JPDA (line 141) | def JPDA(
  function calculate_entropy (line 212) | def calculate_entropy(matrix, idx, idy):
  function get_JPDA_output (line 220) | def get_JPDA_output(cluster, cost_matrix, dummy_node_cost_app, dummy_nod...
  function matching_cascade (line 273) | def matching_cascade(
  function gate_cost_matrix (line 339) | def gate_cost_matrix(
  function find_clusters (line 410) | def find_clusters(cost_matrix, cutoff):

FILE: paper_experiments/utils/logger.py
  class Logger (line 6) | class Logger:
    method __init__ (line 7) | def __init__(self, logdir):
    method close (line 12) | def close(self):
    method log_scalar (line 15) | def log_scalar(self, tag, value, global_step):
    method log_image (line 21) | def log_image(self, tag, img, global_step):

FILE: paper_experiments/utils/mbest_ilp.py
  function ilp_assignment (line 16) | def ilp_assignment(model):
  function initialize_model (line 29) | def initialize_model(cost_matrix, cutoff, model = None):
  function cache (line 59) | def cache(func):
  function num_solutions (line 74) | def num_solutions(cost_matrix):
  function enumerate_solutions (line 85) | def enumerate_solutions(cost_matrix, cutoff, num_solutions):
  function new_m_best_sol (line 104) | def new_m_best_sol(cost_matrix, m_sol, cutoff, model = None):
  function linear_assignment_wrapper (line 189) | def linear_assignment_wrapper(a):

FILE: paper_experiments/utils/nn_matching.py
  function _pdist (line 6) | def _pdist(a, b):
  function _cosine_distance (line 32) | def _cosine_distance(a, b, data_is_normalized=False):
  function _cosine_distance_torch (line 57) | def _cosine_distance_torch(a, b, data_is_normalized=False):
  function _nn_euclidean_distance (line 66) | def _nn_euclidean_distance(x, y):
  function _nn_euclidean_distance_torch (line 86) | def _nn_euclidean_distance_torch(x, y):
  function _nn_cosine_distance (line 111) | def _nn_cosine_distance(x, y):
  function _nn_cosine_distance_torch (line 131) | def _nn_cosine_distance_torch(x,y):
  class NearestNeighborDistanceMetric (line 138) | class NearestNeighborDistanceMetric(object):
    method __init__ (line 162) | def __init__(self, metric, budget=None):
    method partial_fit (line 178) | def partial_fit(self, features, features_2d, targets, targets_2d, acti...
    method distance (line 209) | def distance(self, features, targets, compare_2d=False):
    method distance_torch (line 235) | def distance_torch(self, features, targets, compare_2d=False):
    method check_samples (line 248) | def check_samples(self, targets):

FILE: paper_experiments/utils/pointnet_tf_util.py
  function _variable_on_cpu (line 10) | def _variable_on_cpu(name, shape, initializer, use_fp16=False):
  function _variable_with_weight_decay (line 24) | def _variable_with_weight_decay(name, shape, stddev, wd, use_xavier=True):
  function conv1d (line 52) | def conv1d(inputs,
  function conv2d (line 112) | def conv2d(inputs,
  function conv2d_transpose (line 172) | def conv2d_transpose(inputs,
  function conv3d (line 252) | def conv3d(inputs,
  function fully_connected (line 311) | def fully_connected(inputs,
  function max_pool2d (line 350) | def max_pool2d(inputs,
  function avg_pool2d (line 375) | def avg_pool2d(inputs,
  function max_pool3d (line 401) | def max_pool3d(inputs,
  function avg_pool3d (line 426) | def avg_pool3d(inputs,
  function batch_norm_template (line 455) | def batch_norm_template(inputs, is_training, scope, moments_dims, bn_dec...
  function batch_norm_for_fc (line 495) | def batch_norm_for_fc(inputs, is_training, bn_decay, scope):
  function batch_norm_for_conv1d (line 509) | def batch_norm_for_conv1d(inputs, is_training, bn_decay, scope):
  function batch_norm_for_conv2d (line 525) | def batch_norm_for_conv2d(inputs, is_training, bn_decay, scope):
  function batch_norm_for_conv3d (line 540) | def batch_norm_for_conv3d(inputs, is_training, bn_decay, scope):
  function dropout (line 554) | def dropout(inputs,

FILE: paper_experiments/utils/pointnet_transform_nets.py
  function input_transform_net (line 10) | def input_transform_net(point_cloud, is_training, bn_decay=None, K=3):
  function feature_transform_net (line 54) | def feature_transform_net(inputs, is_training, bn_decay=None, K=64):

FILE: paper_experiments/utils/read_detections.py
  function read_ground_truth_2d_detections (line 5) | def read_ground_truth_2d_detections(detection_path_2d, frame_idx, detect...
  function read_ground_truth_3d_detections (line 82) | def read_ground_truth_3d_detections(detection_path_3d, frame_idx):

FILE: paper_experiments/utils/resnet_reid_utils.py
  class Feature_ResNet (line 14) | class Feature_ResNet(nn.Module):
    method __init__ (line 15) | def __init__(self,n_layer,output_color):
    method forward (line 24) | def forward(self,x):
  class ResNet_Loader (line 35) | class ResNet_Loader(object):
    method __init__ (line 36) | def __init__(self,model_path,n_layer=50,batch_size=4,output_color=False):
    method inference (line 56) | def inference(self,patches):

FILE: paper_experiments/utils/test_kf/run_kf_test.py
  class Track (line 12) | class Track:
    method __init__ (line 13) | def __init__(self, track_id, first_detection, kf_type):
    method update (line 36) | def update(self, measurement, gt, frame):
    method plot (line 53) | def plot(self):
  function file2data (line 99) | def file2data(fname):
  function cmp_tracks (line 108) | def cmp_tracks(track1, track2):
  function cmp (line 114) | def cmp(data, val):
  function validate (line 128) | def validate(data, fname):
  function run_kf_test (line 137) | def run_kf_test(fname, kf_type):

FILE: paper_experiments/utils/test_kf/write_kf_test.py
  function data2file (line 8) | def data2file(data, fname):
  function add_noise (line 17) | def add_noise(center, std):
  function single_track_4state_test (line 23) | def single_track_4state_test():
  function two_track_4state_test (line 49) | def two_track_4state_test():
  function single_track_6state_test (line 88) | def single_track_6state_test():

FILE: paper_experiments/utils/track.py
  class TrackState (line 9) | class TrackState:
  class Track (line 24) | class Track:
    method __init__ (line 70) | def __init__(self, mean, covariance, model_probabilities, track_id, n_...
    method to_tlwh (line 107) | def to_tlwh(self, kf):
    method to_tlbr (line 129) | def to_tlbr(self):
    method update_feature (line 143) | def update_feature(self, img, appearance_model):
    method predict (line 168) | def predict(self, kf):
    method update (line 186) | def update(self, kf, detection, detections_3d=None,
    method delete_track (line 239) | def delete_track(self):
    method mark_missed (line 242) | def mark_missed(self):
    method update_velocity (line 250) | def update_velocity(self, new_detection):
    method is_tentative (line 265) | def is_tentative(self):
    method is_confirmed (line 270) | def is_confirmed(self):
    method is_deleted (line 274) | def is_deleted(self):
    method is_exiting (line 278) | def is_exiting(self):
    method mark_exiting (line 281) | def mark_exiting(self):
    method feature_update (line 284) | def feature_update(self, detections, detection_idx, lstm, JPDA=False, ...

FILE: paper_experiments/utils/track_3d.py
  class TrackState (line 6) | class TrackState:
  class Track_3d (line 21) | class Track_3d:
    method __init__ (line 67) | def __init__(self, mean, covariance, track_id, n_init, max_age,
    method to_tlwh3d (line 96) | def to_tlwh3d(self):
    method to_tlwh (line 109) | def to_tlwh(self, kf):
    method predict (line 124) | def predict(self, kf):
    method update (line 139) | def update(self, kf, detection, compare_2d=False,
    method mark_missed (line 178) | def mark_missed(self):
    method is_tentative (line 186) | def is_tentative(self):
    method is_confirmed (line 191) | def is_confirmed(self):
    method is_deleted (line 195) | def is_deleted(self):

FILE: paper_experiments/utils/tracker.py
  class Tracker (line 16) | class Tracker:
    method __init__ (line 46) | def __init__(self, max_age=5, n_init=3,
    method gated_metric (line 81) | def gated_metric(self, tracks, dets, track_indices, detection_indices,...
    method predict (line 100) | def predict(self):
    method update (line 109) | def update(self, cur_frame, detections, compare_2d = False):
    method _match (line 170) | def _match(self, detections, compare_2d):
    method _initiate_track (line 207) | def _initiate_track(self, detection, flow=None):
    method prune_tracks (line 221) | def prune_tracks(self):

FILE: paper_experiments/utils/tracker_3d.py
  class Tracker_3d (line 14) | class Tracker_3d:
    method __init__ (line 44) | def __init__(self, max_age=30, n_init=3,
    method gated_metric (line 68) | def gated_metric(self, tracks, dets, track_indices, detection_indices,...
    method predict (line 97) | def predict(self):
    method update (line 106) | def update(self, input_img, detections, compare_2d):
    method _match (line 159) | def _match(self, detections, compare_2d):
    method _initiate_track (line 195) | def _initiate_track(self, detection):
    method prune_tracks (line 205) | def prune_tracks(self):

FILE: paper_experiments/utils/tracking_utils.py
  function create_detector (line 14) | def create_detector(config_path, weight_path, cuda):
  function get_depth_patches (line 23) | def get_depth_patches(point_cloud, box_3d, ids_3d, rot_angles, num_point...
  function non_max_suppression_3D_prime (line 63) | def non_max_suppression_3D_prime(detections, boxes_3d, ids_3d, ids_2d, n...
  function non_max_suppression_3D (line 77) | def non_max_suppression_3D(depth_patches, ids_3d, ids_2d, nms_thresh = 1...
  function iou_3d (line 108) | def iou_3d(patch_1, patch_2):
  function convert_detections (line 128) | def convert_detections(detections, features, appearance_features, detect...
  function combine_features (line 147) | def combine_features(features, depth_features, ids_3d, combination_model...
  function filter (line 164) | def filter(detections):

FILE: paper_experiments/utils/visualise.py
  function draw_track (line 9) | def draw_track(bbox, track = None, bbox_colors = None, det = True,
  function draw_detection (line 38) | def draw_detection(detection, color='k'):
  function draw_ellipse (line 47) | def draw_ellipse(track, color):
  function draw_velocity (line 73) | def draw_velocity(track, color):
  function draw_box3d (line 84) | def draw_box3d(mu, color, alpha, facecolor='none', ax=None):
  function draw_velocity_3d (line 105) | def draw_velocity_3d(track, color, ax=None):
  function draw_ellipse3d (line 116) | def draw_ellipse3d(covariance, x, y, color, ax=None):
  function draw_track3d (line 136) | def draw_track3d(track, color, ax=None):
  function draw_detection3d (line 148) | def draw_detection3d(det, color, ax=None):

FILE: paper_experiments/utils/yolo_utils/datasets.py
  class ImageFolder (line 19) | class ImageFolder(Dataset):
    method __init__ (line 20) | def __init__(self, folder_path, img_size=416):
    method __getitem__ (line 24) | def __getitem__(self, index):
    method __len__ (line 45) | def __len__(self):
  class ListDataset (line 49) | class ListDataset(Dataset):
    method __init__ (line 50) | def __init__(self, list_path, img_size=416):
    method __getitem__ (line 57) | def __getitem__(self, index):
    method __len__ (line 120) | def __len__(self):

FILE: paper_experiments/utils/yolo_utils/parse_config.py
  function parse_model_config (line 3) | def parse_model_config(path):
  function parse_data_config (line 23) | def parse_data_config(path):

FILE: paper_experiments/utils/yolo_utils/utils.py
  function load_classes (line 14) | def load_classes(path):
  function weights_init_normal (line 23) | def weights_init_normal(m):
  function compute_ap (line 32) | def compute_ap(recall, precision):
  function bbox_iou (line 60) | def bbox_iou(box1, box2, x1y1x2y2=True):
  function bbox_iou_numpy (line 93) | def bbox_iou_numpy(box1, box2):
  function non_max_suppression (line 127) | def non_max_suppression(prediction, num_classes, conf_thres=0.5, nms_thr...
  function build_targets (line 187) | def build_targets(
  function to_categorical (line 256) | def to_categorical(y, num_classes):

FILE: src/3d_detector.py
  class Detector_3d (line 28) | class Detector_3d:
    method __init__ (line 29) | def __init__(self):
    method get_3d_feature (line 60) | def get_3d_feature(self, y1_bboxes, pointcloud_upper, pointcloud_lower):
    method publish_pointcloud_from_array (line 169) | def publish_pointcloud_from_array(self, pointcloud, publisher, frame =...
    method cleanup (line 178) | def cleanup(self):
  function main (line 181) | def main(args):

FILE: src/EKF.py
  function squared_mahalanobis_distance (line 79) | def squared_mahalanobis_distance(mean, covariance, measurements):
  class EKF (line 95) | class EKF(object):
    method __init__ (line 101) | def __init__(self):
    method initiate (line 104) | def initiate(self, measurement):
    method predict_mean (line 121) | def predict_mean(self, mean):
    method get_process_noise (line 127) | def get_process_noise(self, mean, covariance):
    method predict_covariance (line 130) | def predict_covariance(self, mean, covariance):
    method project_mean (line 133) | def project_mean(self, mean):
    method project_cov (line 138) | def project_cov(self, mean, covariance):
    method predict (line 141) | def predict(self, mean, covariance):
    method get_innovation_cov (line 165) | def get_innovation_cov(self, covariance):
    method project (line 168) | def project(self, mean, covariance):
    method update (line 189) | def update(self, mean, covariance, measurement_t, marginalization=None...

FILE: src/JPDA_matching.py
  function get_unmatched (line 8) | def get_unmatched(all_idx, matches, i, marginalization=None):
  class Matcher (line 19) | class Matcher:
    method __init__ (line 21) | def __init__(self, detections, marginalizations, confirmed_tracks,
    method match (line 31) | def match(self):
    method get_matches (line 37) | def get_matches(self):
    method get_unmatched_tracks (line 51) | def get_unmatched_tracks(self):
    method get_unmatched_detections (line 55) | def get_unmatched_detections(self):
    method max_match (line 58) | def max_match(self):
    method max_and_threshold_matching (line 84) | def max_and_threshold_matching(self):
    method hungarian (line 103) | def hungarian(self):

FILE: src/aligned_reid_model.py
  class Model (line 10) | class Model(nn.Module):
    method __init__ (line 11) | def __init__(self, local_conv_out_channels=128, num_classes=None):
    method forward (line 24) | def forward(self, x):
  function conv3x3 (line 55) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 61) | class BasicBlock(nn.Module):
    method __init__ (line 64) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 74) | def forward(self, x):
  class Bottleneck (line 93) | class Bottleneck(nn.Module):
    method __init__ (line 96) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 109) | def forward(self, x):
  class ResNet (line 132) | class ResNet(nn.Module):
    method __init__ (line 134) | def __init__(self, block, layers):
    method _make_layer (line 155) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 172) | def forward(self, x):
  function remove_fc (line 186) | def remove_fc(state_dict):
  function resnet18 (line 195) | def resnet18(pretrained=False):
  function resnet34 (line 207) | def resnet34(pretrained=False):
  function resnet50 (line 219) | def resnet50(pretrained=False):
  function resnet101 (line 231) | def resnet101(pretrained=False):
  function resnet152 (line 244) | def resnet152(pretrained=False):

FILE: src/aligned_reid_utils.py
  function time_str (line 16) | def time_str(fmt=None):
  function load_pickle (line 22) | def load_pickle(path):
  function save_pickle (line 34) | def save_pickle(obj, path):
  function save_mat (line 41) | def save_mat(ndarray, path):
  function to_scalar (line 46) | def to_scalar(vt):
  function transfer_optim_state (line 57) | def transfer_optim_state(state, device_id=-1):
  function may_transfer_optims (line 82) | def may_transfer_optims(optims, device_id=-1):
  function may_transfer_modules_optims (line 95) | def may_transfer_modules_optims(modules_and_or_optims, device_id=-1):
  class TransferVarTensor (line 114) | class TransferVarTensor(object):
    method __init__ (line 117) | def __init__(self, device_id=-1):
    method __call__ (line 120) | def __call__(self, var_or_tensor):
  class TransferModulesOptims (line 125) | class TransferModulesOptims(object):
    method __init__ (line 128) | def __init__(self, device_id=-1):
    method __call__ (line 131) | def __call__(self, modules_and_or_optims):
  function set_devices (line 135) | def set_devices(sys_device_ids):
  function set_devices_for_ml (line 164) | def set_devices_for_ml(sys_device_ids):
  function load_ckpt (line 229) | def load_ckpt(modules_optims, ckpt_file, load_to_cpu=True, verbose=True):
  function save_ckpt (line 252) | def save_ckpt(modules_optims, ep, scores, ckpt_file):
  function load_state_dict (line 273) | def load_state_dict(model, src_state_dict):
  function is_iterable (line 314) | def is_iterable(obj):
  function may_set_mode (line 318) | def may_set_mode(maybe_modules, mode):
  function may_make_dir (line 331) | def may_make_dir(path):
  class AverageMeter (line 347) | class AverageMeter(object):
    method __init__ (line 351) | def __init__(self):
    method reset (line 357) | def reset(self):
    method update (line 363) | def update(self, val, n=1):
  class RunningAverageMeter (line 370) | class RunningAverageMeter(object):
    method __init__ (line 373) | def __init__(self, hist=0.99):
    method reset (line 378) | def reset(self):
    method update (line 382) | def update(self, val):
  class RecentAverageMeter (line 390) | class RecentAverageMeter(object):
    method __init__ (line 393) | def __init__(self, hist_size=100):
    method reset (line 398) | def reset(self):
    method update (line 402) | def update(self, val):
    method avg (line 409) | def avg(self):
  function get_model_wrapper (line 414) | def get_model_wrapper(model, multi_gpu):
  class ReDirectSTD (line 422) | class ReDirectSTD(object):
    method __init__ (line 442) | def __init__(self, fpath=None, console='stdout', immediately_visible=F...
    method __del__ (line 463) | def __del__(self):
    method __enter__ (line 466) | def __enter__(self):
    method __exit__ (line 469) | def __exit__(self, *args):
    method write (line 472) | def write(self, msg):
    method flush (line 484) | def flush(self):
    method close (line 491) | def close(self):
  function set_seed (line 497) | def set_seed(seed):
  function print_array (line 514) | def print_array(array, fmt='{:.2f}', end=' '):
  function str2bool (line 525) | def str2bool(v):
  function tight_float_str (line 529) | def tight_float_str(x, fmt='{:.4f}'):
  function find_index (line 533) | def find_index(seq, item):
  function adjust_lr_exp (line 540) | def adjust_lr_exp(optimizer, base_lr, ep, total_ep, start_decay_at_ep):
  function adjust_lr_staircase (line 572) | def adjust_lr_staircase(optimizer, base_lr, ep, decay_at_epochs, factor):
  function measure_time (line 608) | def measure_time(enter_msg):
  function generate_features (line 615) | def generate_features(appearance_model, patches):
  function generate_features_batched (line 626) | def generate_features_batched(appearance_model, patches, object_ids = No...
  function get_image_patches (line 674) | def get_image_patches(input_img, detections):
  function create_appearance_model (line 689) | def create_appearance_model(alignreid_checkpoint, resnet_reid_checkpoint...

FILE: src/calibration.py
  class Calibration (line 8) | class Calibration(object):
    method __init__ (line 33) | def __init__(self, calib_filepath):
    method read_calib_file (line 71) | def read_calib_file(self, filepath):
    method read_calib_from_video (line 92) | def read_calib_from_video(self, calib_root_dir):
    method cart2hom (line 107) | def cart2hom(self, pts_3d):
    method cart2hom_torch (line 115) | def cart2hom_torch(self, pts_3d):
    method project_velo_to_ref (line 123) | def project_velo_to_ref(self, pts_3d_velo):
    method project_ref_to_velo (line 127) | def project_ref_to_velo(self, pts_3d_ref):
    method project_rect_to_ref (line 131) | def project_rect_to_ref(self, pts_3d_rect):
    method project_ref_to_rect (line 135) | def project_ref_to_rect(self, pts_3d_ref):
    method project_ref_to_rect_torch (line 139) | def project_ref_to_rect_torch(self, pts_3d_ref):
    method project_rect_to_velo (line 143) | def project_rect_to_velo(self, pts_3d_rect):
    method project_velo_to_rect (line 150) | def project_velo_to_rect(self, pts_3d_velo):
    method project_rect_to_image (line 157) | def project_rect_to_image(self, pts_3d_rect):
    method project_rect_to_image_torch (line 167) | def project_rect_to_image_torch(self, pts_3d_rect):
    method project_ref_to_image_torch (line 177) | def project_ref_to_image_torch(self, pts_3d_ref):
    method project_velo_to_image (line 187) | def project_velo_to_image(self, pts_3d_velo):
    method project_image_to_rect (line 197) | def project_image_to_rect(self, uv_depth):
    method project_image_to_velo (line 211) | def project_image_to_velo(self, uv_depth):
  function rotx (line 215) | def rotx(t):
  function roty (line 224) | def roty(t):
  function rotz (line 233) | def rotz(t):
  function transform_from_rot_trans (line 242) | def transform_from_rot_trans(R, t):
  function inverse_rigid_trans (line 249) | def inverse_rigid_trans(Tr):
  function read_label (line 258) | def read_label(label_filename):
  function load_image (line 263) | def load_image(img_filename):
  function load_velo_scan (line 266) | def load_velo_scan(velo_filename):
  function project_to_image (line 271) | def project_to_image(pts_3d, P):
  function compute_box_3d (line 291) | def compute_box_3d(obj, P):
  function compute_orientation_3d (line 329) | def compute_orientation_3d(obj, P):
  function draw_projected_box3d (line 358) | def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
  class OmniCalibration (line 385) | class OmniCalibration(Calibration):
    method __init__ (line 386) | def __init__(self, calib_folder):
    method project_ref_to_image_torch (line 402) | def project_ref_to_image_torch(self, pointcloud):
    method project_image_to_rect (line 413) | def project_image_to_rect(self, uvdepth):
    method project_velo_to_ref (line 422) | def project_velo_to_ref(self, pointcloud):
    method move_lidar_to_camera_frame (line 430) | def move_lidar_to_camera_frame(self, pointcloud, upper = True):
    method calculate_median_param_value (line 450) | def calculate_median_param_value(self, param):

FILE: src/combination_model.py
  class CombiNet (line 6) | class CombiNet(nn.Module):
    method __init__ (line 7) | def __init__(self, in_dim = 2560, hidden_units = 512, out_dim = 2560):
    method forward (line 16) | def forward(self, x):
  class CombiLSTM (line 30) | class CombiLSTM(nn.Module):
    method __init__ (line 31) | def __init__(self, in_dim = 2560, hidden_units = 512, out_dim = 2560):
    method forward (line 43) | def forward(self, x, hidden = None):
  function weight_init (line 65) | def weight_init(m):

FILE: src/deep_sort_utils.py
  function non_max_suppression (line 6) | def non_max_suppression(boxes, max_bbox_overlap, scores=None):

FILE: src/detection.py
  class Detection (line 5) | class Detection(object):
    method __init__ (line 29) | def __init__(self, tlwh, box_3d, confidence, appearance_feature, featu...
    method to_tlbr (line 44) | def to_tlbr(self):
    method to_xyah (line 52) | def to_xyah(self):
    method to_xywh (line 60) | def to_xywh(self):
    method get_3d_distance (line 67) | def get_3d_distance(self):

FILE: src/distances.py
  function norm2squared_matrix (line 10) | def norm2squared_matrix(objs, hyps, max_d2=float('inf')):
  function iou_matrix (line 52) | def iou_matrix(objs, hyps, max_iou=1.):
  function find_area (line 112) | def find_area(vertices):
  function get_angle (line 118) | def get_angle(p):
  function clip_polygon (line 125) | def clip_polygon(box1, box2):
  function compute_intersection_point (line 163) | def compute_intersection_point(pt1, pt2, line1):
  function point_inside_edge (line 189) | def point_inside_edge(pt, edge):
  function iou_matrix_3d (line 197) | def iou_matrix_3d(objs, hyps, max_iou=1.):

FILE: src/double_measurement_kf.py
  class KF_3D (line 18) | class KF_3D(kf_2d.KalmanFilter2D):
    method __init__ (line 33) | def __init__(self, calib, pos_weight_3d, pos_weight, velocity_weight, ...
    method initiate (line 64) | def initiate(self, measurement_3d):
    method get_process_noise (line 83) | def get_process_noise(self, mean):
    method get_2d_measurement_noise (line 102) | def get_2d_measurement_noise(self, measurement_2d):
    method get_3d_measurement_noise (line 114) | def get_3d_measurement_noise(self, measurement):
    method gating_distance (line 130) | def gating_distance(self, mean, covariance, measurements,
    method project_cov (line 182) | def project_cov(self, mean, covariance):
    method project_cov_2d (line 191) | def project_cov_2d(self, mean, covariance, H_2d):
    method update (line 200) | def update(self, mean, covariance, measurement_2d, measurement_3d = No...
    method get_2d_measurement_matrix (line 312) | def get_2d_measurement_matrix(self, mean, corner_points, corner_points...
    method jacobian (line 349) | def jacobian(self, pt_3d):
    method jacobian_omni (line 356) | def jacobian_omni(self, pt_3d):
    method calculate_corners (line 370) | def calculate_corners(self, box):
    method corner_jacobian (line 389) | def corner_jacobian(self, pt_3d, corner_idx):
    method project_2d (line 416) | def project_2d(self, pts_3d):
  function swap (line 436) | def swap(detections_3d, iou, idx, swap_prob = 0):

FILE: src/evaluation/distances 2.py
  function norm2squared_matrix (line 10) | def norm2squared_matrix(objs, hyps, max_d2=float('inf')):
  function iou_matrix (line 52) | def iou_matrix(objs, hyps, max_iou=1.):
  function find_area (line 112) | def find_area(vertices):
  function get_angle (line 118) | def get_angle(p):
  function clip_polygon (line 125) | def clip_polygon(box1, box2):
  function sort_points (line 163) | def sort_points(pts, center):
  function compute_intersection_point (line 169) | def compute_intersection_point(pt1, pt2, line1):
  function point_inside_edge (line 195) | def point_inside_edge(pt, edge):
  function iou_matrix_3d (line 203) | def iou_matrix_3d(objs, hyps, max_iou=1.):

FILE: src/evaluation/distances.py
  function norm2squared_matrix (line 10) | def norm2squared_matrix(objs, hyps, max_d2=float('inf')):
  function iou_matrix (line 52) | def iou_matrix(objs, hyps, max_iou=1.):
  function find_area (line 112) | def find_area(vertices):
  function get_angle (line 118) | def get_angle(p):
  function clip_polygon (line 125) | def clip_polygon(box1, box2):
  function sort_points (line 163) | def sort_points(pts, center):
  function compute_intersection_point (line 169) | def compute_intersection_point(pt1, pt2, line1):
  function point_inside_edge (line 195) | def point_inside_edge(pt, edge):
  function iou_matrix_3d (line 203) | def iou_matrix_3d(objs, hyps, max_iou=1.):

FILE: src/featurepointnet_model.py
  class FPointNet (line 13) | class FPointNet():
    method __init__ (line 14) | def __init__(self, config_path):
    method __call__ (line 57) | def __call__(self, input_point_cloud, rot_angle, peds=False):
    method get_instance_seg_v1_net (line 126) | def get_instance_seg_v1_net(self, point_cloud, one_hot_vec, is_trainin...
    method get_3d_box_estimation_v1_net (line 197) | def get_3d_box_estimation_v1_net(self, object_point_cloud, one_hot_vec...
    method get_model (line 246) | def get_model(self, point_cloud, one_hot_vec, is_training, bn_decay=No...
    method get_depth_feature_op (line 294) | def get_depth_feature_op(self, is_training):
    method get_depth_feature (line 317) | def get_depth_feature(self, object_pointcloud):
    method softmax (line 323) | def softmax(self, x):
  function create_depth_model (line 330) | def create_depth_model(model, config_path):

FILE: src/featurepointnet_model_util.py
  function tf_gather_object_pc (line 39) | def tf_gather_object_pc(point_cloud, mask, npoints=512):
  function get_box3d_corners_helper (line 72) | def get_box3d_corners_helper(centers, headings, sizes):
  function get_box3d_corners (line 99) | def get_box3d_corners(center, heading_residuals, size_residuals):
  function huber_loss (line 124) | def huber_loss(error, delta):
  function parse_output_to_tensors (line 132) | def parse_output_to_tensors(output, end_points):
  function from_prediction_to_label_format (line 170) | def from_prediction_to_label_format(center, angle_class, angle_res,\
  function size2class (line 179) | def size2class(size, type_name):
  function class2size (line 194) | def class2size(pred_cls, residual):
  function angle2class (line 199) | def angle2class(angle, num_class):
  function class2angle (line 219) | def class2angle(pred_cls, residual, num_class, to_label_format=True):
  function rotate_pc_along_y (line 230) | def rotate_pc_along_y(pc, rot_angle):
  function rotate_pc_along_y_torch (line 247) | def rotate_pc_along_y_torch(pc, rot_angle):
  function placeholder_inputs (line 270) | def placeholder_inputs(batch_size, num_point):
  function point_cloud_masking (line 295) | def point_cloud_masking(point_cloud, logits, end_points, xyz_only=True):
  function get_center_regression_net (line 343) | def get_center_regression_net(object_point_cloud, one_hot_vec,
  function softmax (line 380) | def softmax(x):
  function get_loss (line 388) | def get_loss(mask_label, center_label, \
  function get_lidar_in_image_fov (line 510) | def get_lidar_in_image_fov(pc_velo, calib, xmin, ymin, xmax, ymax,
  function preprocess_pointcloud (line 524) | def preprocess_pointcloud(detections, point_cloud, pc_image_coord,
  function generate_detections_3d (line 576) | def generate_detections_3d(detector, detections_2d, point_cloud, calib, ...
  function convert_depth_features (line 590) | def convert_depth_features(depth_features_orig, ids_3d):

FILE: src/featurepointnet_tf_util.py
  function _variable_on_cpu (line 10) | def _variable_on_cpu(name, shape, initializer, use_fp16=False):
  function _variable_with_weight_decay (line 24) | def _variable_with_weight_decay(name, shape, stddev, wd, use_xavier=True):
  function conv1d (line 52) | def conv1d(inputs,
  function conv2d (line 120) | def conv2d(inputs,
  function conv2d_transpose (line 188) | def conv2d_transpose(inputs,
  function conv3d (line 268) | def conv3d(inputs,
  function fully_connected (line 327) | def fully_connected(inputs,
  function max_pool2d (line 366) | def max_pool2d(inputs,
  function avg_pool2d (line 391) | def avg_pool2d(inputs,
  function max_pool3d (line 417) | def max_pool3d(inputs,
  function avg_pool3d (line 442) | def avg_pool3d(inputs,
  function batch_norm_template_unused (line 468) | def batch_norm_template_unused(inputs, is_training, scope, moments_dims,...
  function batch_norm_template (line 512) | def batch_norm_template(inputs, is_training, scope, moments_dims_unused,...
  function batch_norm_for_fc (line 534) | def batch_norm_for_fc(inputs, is_training, bn_decay, scope):
  function batch_norm_for_conv1d (line 548) | def batch_norm_for_conv1d(inputs, is_training, bn_decay, scope, data_for...
  function batch_norm_for_conv2d (line 565) | def batch_norm_for_conv2d(inputs, is_training, bn_decay, scope, data_for...
  function batch_norm_for_conv3d (line 580) | def batch_norm_for_conv3d(inputs, is_training, bn_decay, scope):
  function dropout (line 594) | def dropout(inputs,

FILE: src/iou_matching.py
  function iou (line 8) | def iou(bbox, candidates):
  function iou_cost (line 43) | def iou_cost(tracks, detections, track_indices=None,

FILE: src/kf_2d.py
  class KalmanFilter2D (line 8) | class KalmanFilter2D(EKF.EKF):
    method __init__ (line 25) | def __init__(self, pos_weight, velocity_weight, std_process, std_measu...
    method initiate (line 47) | def initiate(self, measurement, flow):
    method predict_mean (line 87) | def predict_mean(self, mean):
    method predict_covariance (line 93) | def predict_covariance(self, mean, covariance):
    method get_process_noise (line 100) | def get_process_noise(self, mean):
    method project_mean (line 118) | def project_mean(self, mean):
    method get_measurement_noise (line 126) | def get_measurement_noise(self, measurement):
    method project_cov (line 138) | def project_cov(self, mean, covariance):
    method gating_distance (line 147) | def gating_distance(self, mean, covariance, measurements,
  class RandomWalkKalmanFilter2D (line 187) | class RandomWalkKalmanFilter2D(KalmanFilter2D): #TODO UPDATE THIS DOCUME...
    method __init__ (line 203) | def __init__(self, pos_weight, velocity_weight, std_process, std_measu...

FILE: src/linear_assignment.py
  function min_marg_matching (line 15) | def min_marg_matching(marginalizations, track_indices=None, max_distance...
  function min_cost_matching (line 61) | def min_cost_matching(
  function JPDA (line 142) | def JPDA(
  function calculate_entropy (line 208) | def calculate_entropy(matrix, idx, idy):
  function get_JPDA_output (line 216) | def get_JPDA_output(cluster, cost_matrix, dummy_node_cost_app, dummy_nod...
  function matching_cascade (line 273) | def matching_cascade(
  function gate_cost_matrix (line 339) | def gate_cost_matrix(
  function find_clusters (line 401) | def find_clusters(cost_matrix, cutoff):

FILE: src/mbest_ilp.py
  function ilp_assignment (line 16) | def ilp_assignment(model):
  function initialize_model (line 29) | def initialize_model(cost_matrix, cutoff, model = None):
  function cache (line 59) | def cache(func):
  function num_solutions (line 74) | def num_solutions(cost_matrix):
  function enumerate_solutions (line 85) | def enumerate_solutions(cost_matrix, cutoff, num_solutions):
  function new_m_best_sol (line 104) | def new_m_best_sol(cost_matrix, m_sol, cutoff, model = None):
  function linear_assignment_wrapper (line 189) | def linear_assignment_wrapper(a):

FILE: src/nn_matching.py
  function _pdist (line 6) | def _pdist(a, b):
  function _cosine_distance (line 32) | def _cosine_distance(a, b, data_is_normalized=False):
  function _cosine_distance_torch (line 57) | def _cosine_distance_torch(a, b, data_is_normalized=False):
  function _nn_euclidean_distance (line 66) | def _nn_euclidean_distance(x, y):
  function _nn_euclidean_distance_torch (line 86) | def _nn_euclidean_distance_torch(x, y):
  function _nn_cosine_distance (line 111) | def _nn_cosine_distance(x, y):
  function _nn_cosine_distance_torch (line 131) | def _nn_cosine_distance_torch(x,y):
  class NearestNeighborDistanceMetric (line 138) | class NearestNeighborDistanceMetric(object):
    method __init__ (line 162) | def __init__(self, metric, budget=None):
    method partial_fit (line 178) | def partial_fit(self, features, features_2d, targets, targets_2d, acti...
    method distance (line 209) | def distance(self, features, targets, compare_2d=False):
    method distance_torch (line 235) | def distance_torch(self, features, targets, compare_2d=False):
    method check_samples (line 248) | def check_samples(self, targets):

FILE: src/pointnet_model.py
  class PointNet (line 9) | class PointNet():
    method __init__ (line 10) | def __init__(self, config_path):
    method __call__ (line 37) | def __call__(self, input_point_cloud):
    method placeholder_inputs (line 43) | def placeholder_inputs(self, batch_size, num_point):
    method get_model (line 49) | def get_model(self, point_cloud, is_training, bn_decay=None):
    method get_loss (line 96) | def get_loss(self, pred, label, end_points, reg_weight=0.001):

FILE: src/template 2.py
  class Appearance_Features (line 19) | class Appearance_Features:
    method __init__ (line 20) | def __init__(self):
    method get_2d_feature (line 39) | def get_2d_feature(self, y1_bboxes, ros_image):
    method cleanup (line 86) | def cleanup(self):
  function main (line 89) | def main(args):

FILE: src/template.py
  class Appearance_Features (line 19) | class Appearance_Features:
    method __init__ (line 20) | def __init__(self):
    method get_2d_feature (line 39) | def get_2d_feature(self, y1_bboxes, ros_image):
    method cleanup (line 86) | def cleanup(self):
  function main (line 89) | def main(args):

FILE: src/track_3d 2.py
  class TrackState (line 6) | class TrackState:
  class Track_3d (line 21) | class Track_3d:
    method __init__ (line 67) | def __init__(self, mean, covariance, track_id, n_init, max_age,
    method to_tlwh3d (line 97) | def to_tlwh3d(self):
    method to_tlwh (line 112) | def to_tlwh(self, kf):
    method predict (line 127) | def predict(self, kf):
    method update (line 142) | def update(self, kf, detection, compare_2d=False,
    method mark_missed (line 191) | def mark_missed(self):
    method is_tentative (line 199) | def is_tentative(self):
    method is_confirmed (line 204) | def is_confirmed(self):
    method is_deleted (line 208) | def is_deleted(self):
    method feature_update (line 212) | def feature_update(self, detections, detection_idx, lstm, JPDA=False, ...
    method get_cov (line 244) | def get_cov(self):

FILE: src/track_3d.py
  class TrackState (line 6) | class TrackState:
  class Track_3d (line 21) | class Track_3d:
    method __init__ (line 67) | def __init__(self, mean, covariance, track_id, n_init, max_age,
    method to_tlwh3d (line 97) | def to_tlwh3d(self):
    method to_tlwh (line 112) | def to_tlwh(self, kf):
    method predict (line 127) | def predict(self, kf):
    method update (line 142) | def update(self, kf, detection, compare_2d=False,
    method mark_missed (line 191) | def mark_missed(self):
    method is_tentative (line 199) | def is_tentative(self):
    method is_confirmed (line 204) | def is_confirmed(self):
    method is_deleted (line 208) | def is_deleted(self):
    method feature_update (line 212) | def feature_update(self, detections, detection_idx, lstm, JPDA=False, ...
    method get_cov (line 244) | def get_cov(self):

FILE: src/tracker_3d 2.py
  class Tracker_3d (line 15) | class Tracker_3d:
    method __init__ (line 45) | def __init__(self, max_age=30, n_init=3,
    method gated_metric (line 71) | def gated_metric(self, tracks, dets, track_indices, detection_indices,...
    method predict (line 99) | def predict(self):
    method update (line 108) | def update(self, input_img, detections):
    method _match (line 148) | def _match(self, detections):
    method _initiate_track (line 213) | def _initiate_track(self, detection):
    method prune_tracks (line 223) | def prune_tracks(self):

FILE: src/tracker_3d.py
  class Tracker_3d (line 15) | class Tracker_3d:
    method __init__ (line 45) | def __init__(self, max_age=30, n_init=3,
    method gated_metric (line 71) | def gated_metric(self, tracks, dets, track_indices, detection_indices,...
    method predict (line 99) | def predict(self):
    method update (line 108) | def update(self, input_img, detections):
    method _match (line 148) | def _match(self, detections):
    method _initiate_track (line 213) | def _initiate_track(self, detection):
    method prune_tracks (line 223) | def prune_tracks(self):

FILE: src/tracker_3d_node 2.py
  class Tracker_3D_node (line 30) | class Tracker_3D_node:
    method __init__ (line 31) | def __init__(self):
    method do_3d_tracking (line 87) | def do_3d_tracking(self, detections_2d, detections_3d):
    method find_time_diff_2d (line 157) | def find_time_diff_2d(self, a):
    method find_time_diff_3d (line 161) | def find_time_diff_3d(self, a):
    method cleanup (line 165) | def cleanup(self):
  function main (line 174) | def main(args):

FILE: src/tracker_3d_node.py
  class Tracker_3D_node (line 30) | class Tracker_3D_node:
    method __init__ (line 31) | def __init__(self):
    method do_3d_tracking (line 87) | def do_3d_tracking(self, detections_2d, detections_3d):
    method find_time_diff_2d (line 157) | def find_time_diff_2d(self, a):
    method find_time_diff_3d (line 161) | def find_time_diff_3d(self, a):
    method cleanup (line 165) | def cleanup(self):
  function main (line 174) | def main(args):

FILE: src/tracking_utils 2.py
  function create_detector (line 13) | def create_detector(config_path, weight_path, cuda):
  function get_depth_patches (line 22) | def get_depth_patches(point_cloud, box_3d, ids_3d, rot_angles, num_point...
  function non_max_suppression_3D_prime (line 62) | def non_max_suppression_3D_prime(detections, boxes_3d, ids_3d, ids_2d, n...
  function non_max_suppression_3D (line 76) | def non_max_suppression_3D(depth_patches, ids_3d, ids_2d, nms_thresh = 1...
  function iou_3d (line 107) | def iou_3d(patch_1, patch_2):
  function convert_detections (line 127) | def convert_detections(detections, features, appearance_features, detect...
  function combine_features (line 146) | def combine_features(features, depth_features, ids_3d, combination_model...
  function filter (line 164) | def filter(detections):

FILE: src/tracking_utils.py
  function create_detector (line 13) | def create_detector(config_path, weight_path, cuda):
  function get_depth_patches (line 22) | def get_depth_patches(point_cloud, box_3d, ids_3d, rot_angles, num_point...
  function non_max_suppression_3D_prime (line 62) | def non_max_suppression_3D_prime(detections, boxes_3d, ids_3d, ids_2d, n...
  function non_max_suppression_3D (line 76) | def non_max_suppression_3D(depth_patches, ids_3d, ids_2d, nms_thresh = 1...
  function iou_3d (line 107) | def iou_3d(patch_1, patch_2):
  function convert_detections (line 127) | def convert_detections(detections, features, appearance_features, detect...
  function combine_features (line 146) | def combine_features(features, depth_features, ids_3d, combination_model...
  function filter (line 164) | def filter(detections):