SYMBOL INDEX (1404 symbols across 184 files)

FILE: CurveNet/core/data.py
  function download_modelnet40 (line 26) | def download_modelnet40():
  function download_shapenetpart (line 38) | def download_shapenetpart():
  function load_data_normal (line 50) | def load_data_normal(partition):
  function load_data_cls (line 58) | def load_data_cls(partition):
  function load_data_partseg (line 74) | def load_data_partseg(partition):
  function translate_pointcloud (line 99) | def translate_pointcloud(pointcloud):
  function jitter_pointcloud (line 107) | def jitter_pointcloud(pointcloud, sigma=0.01, clip=0.02):
  function rotate_pointcloud (line 113) | def rotate_pointcloud(pointcloud):
  class ModelNet40 (line 120) | class ModelNet40(Dataset):
    method __init__ (line 121) | def __init__(self, num_points, partition='train'):
    method __getitem__ (line 126) | def __getitem__(self, item):
    method __len__ (line 135) | def __len__(self):
  class ModelNetNormal (line 138) | class ModelNetNormal(Dataset):
    method __init__ (line 139) | def __init__(self, num_points, partition='train'):
    method __getitem__ (line 144) | def __getitem__(self, item):
    method __len__ (line 155) | def __len__(self):
  class ShapeNetPart (line 158) | class ShapeNetPart(Dataset):
    method __init__ (line 159) | def __init__(self, num_points=2048, partition='train', class_choice=No...
    method __getitem__ (line 182) | def __getitem__(self, item):
    method __len__ (line 194) | def __len__(self):

FILE: CurveNet/core/main_cls.py
  function _init_ (line 29) | def _init_():
  function train (line 50) | def train(args, io):
  function test (line 147) | def test(args, io):

FILE: CurveNet/core/main_normal.py
  function _init_ (line 24) | def _init_():
  function train (line 45) | def train(args, io):
  function test (line 130) | def test(args, io):

FILE: CurveNet/core/main_partseg.py
  function _init_ (line 32) | def _init_():
  function calculate_shape_IoU (line 53) | def calculate_shape_IoU(pred_np, seg_np, label, class_choice, eva=False):
  function train (line 84) | def train(args, io):
  function test (line 231) | def test(args, io):

FILE: CurveNet/core/models/curvenet_cls.py
  class CurveNet (line 18) | class CurveNet(nn.Module):
    method __init__ (line 19) | def __init__(self, num_classes=40, k=20, setting='default'):
    method forward (line 49) | def forward(self, xyz):

FILE: CurveNet/core/models/curvenet_normal.py
  class CurveNet (line 17) | class CurveNet(nn.Module):
    method __init__ (line 18) | def __init__(self, num_classes=3, k=20, multiplier=1.0, setting='defau...
    method forward (line 60) | def forward(self, xyz):

FILE: CurveNet/core/models/curvenet_seg.py
  class CurveNet (line 17) | class CurveNet(nn.Module):
    method __init__ (line 18) | def __init__(self, num_classes=50, category=16, k=32, setting='default'):
    method forward (line 78) | def forward(self, xyz, l=None):

FILE: CurveNet/core/models/curvenet_util.py
  function knn (line 22) | def knn(x, k):
  function normal_knn (line 31) | def normal_knn(x, k):
  function pc_normalize (line 39) | def pc_normalize(pc):
  function square_distance (line 47) | def square_distance(src, dst):
  function index_points (line 58) | def index_points(points, idx):
  function farthest_point_sample (line 78) | def farthest_point_sample(xyz, npoint):
  function query_ball_point (line 101) | def query_ball_point(radius, nsample, xyz, new_xyz):
  function sample_and_group (line 123) | def sample_and_group(npoint, radius, nsample, xyz, points, returnfps=Fal...
  class Attention_block (line 149) | class Attention_block(nn.Module):
    method __init__ (line 153) | def __init__(self,F_g,F_l,F_int):
    method forward (line 171) | def forward(self,g,x):
  class LPFA (line 180) | class LPFA(nn.Module):
    method __init__ (line 181) | def __init__(self, in_channel, out_channel, k, mlp_num=2, initial=False):
    method forward (line 200) | def forward(self, x, xyz, idx=None):
    method group_feature (line 211) | def group_feature(self, x, xyz, idx):
  class PointNetFeaturePropagation (line 244) | class PointNetFeaturePropagation(nn.Module):
    method __init__ (line 245) | def __init__(self, in_channel, mlp, att=None):
    method forward (line 259) | def forward(self, xyz1, xyz2, points1, points2):
  class CIC (line 308) | class CIC(nn.Module):
    method __init__ (line 309) | def __init__(self, npoint, radius, k, in_channels, output_channels, bo...
    method forward (line 351) | def forward(self, xyz, x):
  class CurveAggregation (line 383) | class CurveAggregation(nn.Module):
    method __init__ (line 384) | def __init__(self, in_channel):
    method forward (line 419) | def forward(self, x, curves):
  class CurveGrouping (line 445) | class CurveGrouping(nn.Module):
    method __init__ (line 446) | def __init__(self, in_channel, k, curve_num, curve_length):
    method forward (line 457) | def forward(self, x, xyz, idx):
  class MaskedMaxPool (line 473) | class MaskedMaxPool(nn.Module):
    method __init__ (line 474) | def __init__(self, npoint, radius, k):
    method forward (line 480) | def forward(self, xyz, features):

FILE: CurveNet/core/models/walk.py
  function batched_index_select (line 14) | def batched_index_select(input, dim, index):
  function gumbel_softmax (line 23) | def gumbel_softmax(logits, dim, temperature=1):
  class Walk (line 40) | class Walk(nn.Module):
    method __init__ (line 44) | def __init__(self, in_channel, k, curve_num, curve_length):
    method crossover_suppression (line 61) | def crossover_suppression(self, cur, neighbor, bn, n, k):
    method forward (line 78) | def forward(self, xyz, x, adj, cur):

FILE: CurveNet/core/util.py
  function cal_loss (line 14) | def cal_loss(pred, gold, smoothing=True):
  class IOStream (line 34) | class IOStream():
    method __init__ (line 35) | def __init__(self, path):
    method cprint (line 38) | def cprint(self, text):
    method close (line 43) | def close(self):

FILE: GDANet/model/GDANet_cls.py
  class GDANET (line 7) | class GDANET(nn.Module):
    method __init__ (line 8) | def __init__(self, number_class=40):
    method forward (line 62) | def forward(self, x):

FILE: GDANet/model/GDANet_ptseg.py
  class GDANet (line 7) | class GDANet(nn.Module):
    method __init__ (line 8) | def __init__(self, num_classes):
    method forward (line 71) | def forward(self, x, norm_plt, cls_label):

FILE: GDANet/model/util/GDANet_util.py
  function knn (line 5) | def knn(x, k):
  function local_operator (line 14) | def local_operator(x, k):
  function local_operator_withnorm (line 42) | def local_operator_withnorm(x, norm_plt, k):
  function GDM (line 74) | def GDM(x, M):
  class SGCAM (line 153) | class SGCAM(nn.Module):
    method __init__ (line 155) | def __init__(self, in_channels, inter_channels=None, bn_layer=True):
    method forward (line 192) | def forward(self, x, x_2):

FILE: GDANet/model/util/data_util.py
  function load_data (line 9) | def load_data(partition):
  function pc_normalize (line 24) | def pc_normalize(pc):
  function translate_pointcloud (line 32) | def translate_pointcloud(pointcloud):
  function jitter_pointcloud (line 40) | def jitter_pointcloud(pointcloud, sigma=0.01, clip=0.02):
  class ModelNet40 (line 47) | class ModelNet40(Dataset):
    method __init__ (line 48) | def __init__(self, num_points, partition='train'):
    method __getitem__ (line 53) | def __getitem__(self, item):  # indice of the pts or label
    method __len__ (line 62) | def __len__(self):
  class PartNormalDataset (line 67) | class PartNormalDataset(Dataset):
    method __init__ (line 68) | def __init__(self, npoints=2500, split='train', normalize=False):
    method __getitem__ (line 125) | def __getitem__(self, index):
    method __len__ (line 154) | def __len__(self):

FILE: GDANet/model/util/util.py
  function cal_loss (line 6) | def cal_loss(pred, gold, smoothing=True):
  class IOStream (line 27) | class IOStream():
    method __init__ (line 28) | def __init__(self, path):
    method cprint (line 31) | def cprint(self, text):
    method close (line 36) | def close(self):
  function to_categorical (line 40) | def to_categorical(y, num_classes):
  function compute_overall_iou (line 48) | def compute_overall_iou(pred, target, num_classes):

FILE: PCT_Pytorch/data.py
  function download (line 7) | def download():
  function load_data (line 19) | def load_data(partition):
  function random_point_dropout (line 36) | def random_point_dropout(pc, max_dropout_ratio=0.875):
  function translate_pointcloud (line 47) | def translate_pointcloud(pointcloud):
  function jitter_pointcloud (line 54) | def jitter_pointcloud(pointcloud, sigma=0.01, clip=0.02):
  class ModelNet40 (line 60) | class ModelNet40(Dataset):
    method __init__ (line 61) | def __init__(self, num_points, partition='train'):
    method __getitem__ (line 66) | def __getitem__(self, item):
    method __len__ (line 75) | def __len__(self):

FILE: PCT_Pytorch/main.py
  function _init_ (line 17) | def _init_():
  function train (line 29) | def train(args, io):
  function test (line 132) | def test(args, io):

FILE: PCT_Pytorch/model.py
  class Local_op (line 6) | class Local_op(nn.Module):
    method __init__ (line 7) | def __init__(self, in_channels, out_channels):
    method forward (line 14) | def forward(self, x):
  class Pct (line 25) | class Pct(nn.Module):
    method __init__ (line 26) | def __init__(self, args, output_channels=40):
    method forward (line 51) | def forward(self, x):
  class Point_Transformer_Last (line 77) | class Point_Transformer_Last(nn.Module):
    method __init__ (line 78) | def __init__(self, args, channels=256):
    method forward (line 92) | def forward(self, x):
  class SA_Layer (line 111) | class SA_Layer(nn.Module):
    method __init__ (line 112) | def __init__(self, channels):
    method forward (line 125) | def forward(self, x):

FILE: PCT_Pytorch/model_new.py
  class Local_op (line 6) | class Local_op(nn.Module):
    method __init__ (line 7) | def __init__(self, in_channels, out_channels):
    method forward (line 14) | def forward(self, x):
  class Pct (line 25) | class Pct(nn.Module):
    method __init__ (line 26) | def __init__(self, args, output_channels=40):
    method forward (line 50) | def forward(self, x):
  class Point_Transformer_Last (line 76) | class Point_Transformer_Last(nn.Module):
    method __init__ (line 77) | def __init__(self, args, channels=256):
    method forward (line 89) | def forward(self, x, xyz):
  class SA_Layer (line 108) | class SA_Layer(nn.Module):
    method __init__ (line 109) | def __init__(self, channels):
    method forward (line 123) | def forward(self, x, xyz):

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/_ext-src/include/cuda_utils.h
  function opt_n_threads (line 15) | inline int opt_n_threads(int work_size) {
  function dim3 (line 21) | inline dim3 opt_block_config(int x, int y) {

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/_ext-src/src/ball_query.cpp
  function ball_query (line 8) | at::Tensor ball_query(at::Tensor new_xyz, at::Tensor xyz, const float ra...

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/_ext-src/src/bindings.cpp
  function PYBIND11_MODULE (line 6) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/_ext-src/src/group_points.cpp
  function group_points (line 12) | at::Tensor group_points(at::Tensor points, at::Tensor idx) {
  function group_points_grad (line 38) | at::Tensor group_points_grad(at::Tensor grad_out, at::Tensor idx, const ...

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/_ext-src/src/interpolate.cpp
  function three_nn (line 14) | std::vector<at::Tensor> three_nn(at::Tensor unknowns, at::Tensor knows) {
  function three_interpolate (line 42) | at::Tensor three_interpolate(at::Tensor points, at::Tensor idx,
  function three_interpolate_grad (line 71) | at::Tensor three_interpolate_grad(at::Tensor grad_out, at::Tensor idx,

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/_ext-src/src/sampling.cpp
  function gather_points (line 15) | at::Tensor gather_points(at::Tensor points, at::Tensor idx) {
  function gather_points_grad (line 40) | at::Tensor gather_points_grad(at::Tensor grad_out, at::Tensor idx,
  function furthest_point_sampling (line 66) | at::Tensor furthest_point_sampling(at::Tensor points, const int nsamples) {

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/pointnet2_modules.py
  function build_shared_mlp (line 9) | def build_shared_mlp(mlp_spec: List[int], bn: bool = True):
  class _PointnetSAModuleBase (line 22) | class _PointnetSAModuleBase(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 29) | def forward(
  class PointnetSAModuleMSG (line 77) | class PointnetSAModuleMSG(_PointnetSAModuleBase):
    method __init__ (line 94) | def __init__(self, npoint, radii, nsamples, mlps, bn=True, use_xyz=True):
  class PointnetSAModule (line 118) | class PointnetSAModule(PointnetSAModuleMSG):
    method __init__ (line 135) | def __init__(
  class PointnetFPModule (line 149) | class PointnetFPModule(nn.Module):
    method __init__ (line 160) | def __init__(self, mlp, bn=True):
    method forward (line 165) | def forward(self, unknown, known, unknow_feats, known_feats):

FILE: PCT_Pytorch/pointnet2_ops_lib/pointnet2_ops/pointnet2_utils.py
  class FurthestPointSampling (line 34) | class FurthestPointSampling(Function):
    method forward (line 36) | def forward(ctx, xyz, npoint):
    method backward (line 61) | def backward(ctx, grad_out):
  class GatherOperation (line 68) | class GatherOperation(Function):
    method forward (line 70) | def forward(ctx, features, idx):
    method backward (line 93) | def backward(ctx, grad_out):
  class ThreeNN (line 104) | class ThreeNN(Function):
    method forward (line 106) | def forward(ctx, unknown, known):
    method backward (line 132) | def backward(ctx, grad_dist, grad_idx):
  class ThreeInterpolate (line 139) | class ThreeInterpolate(Function):
    method forward (line 141) | def forward(ctx, features, idx, weight):
    method backward (line 164) | def backward(ctx, grad_out):
  class GroupingOperation (line 194) | class GroupingOperation(Function):
    method forward (line 196) | def forward(ctx, features, idx):
    method backward (line 217) | def backward(ctx, grad_out):
  class BallQuery (line 243) | class BallQuery(Function):
    method forward (line 245) | def forward(ctx, radius, nsample, xyz, new_xyz):
    method backward (line 272) | def backward(ctx, grad_out):
  class QueryAndGroup (line 279) | class QueryAndGroup(nn.Module):
    method __init__ (line 291) | def __init__(self, radius, nsample, use_xyz=True):
    method forward (line 296) | def forward(self, xyz, new_xyz, features=None):
  class GroupAll (line 336) | class GroupAll(nn.Module):
    method __init__ (line 344) | def __init__(self, use_xyz=True):
    method forward (line 349) | def forward(self, xyz, new_xyz, features=None):

FILE: PCT_Pytorch/util.py
  function cal_loss (line 5) | def cal_loss(pred, gold, smoothing=True):
  class IOStream (line 24) | class IOStream():
    method __init__ (line 25) | def __init__(self, path):
    method cprint (line 28) | def cprint(self, text):
    method close (line 33) | def close(self):
  function square_distance (line 36) | def square_distance(src, dst):
  function index_points (line 57) | def index_points(points, idx):
  function query_ball_point (line 75) | def query_ball_point(radius, nsample, xyz, new_xyz):
  function knn_point (line 97) | def knn_point(nsample, xyz, new_xyz):
  function sample_and_group (line 110) | def sample_and_group(npoint, radius, nsample, xyz, points):

FILE: all_utils.py
  class TensorboardManager (line 23) | class TensorboardManager:
    method __init__ (line 24) | def __init__(self, path):
    method update (line 27) | def update(self, split, step, vals):
    method close (line 31) | def close(self):
  class TrackTrain (line 36) | class TrackTrain:
    method __init__ (line 37) | def __init__(self, early_stop_patience):
    method record_epoch (line 48) | def record_epoch(self, epoch_id, train_metric, val_metric, test_metric):
    method save_model (line 66) | def save_model(self, epoch_id, split):
    method early_stop (line 94) | def early_stop(self, epoch_id):
  class PerfTrackVal (line 102) | class PerfTrackVal:
    method __init__ (line 106) | def __init__(self, task, extra_param=None):
    method update (line 115) | def update(self, data_batch, out):
    method agg (line 122) | def agg(self):
    method update_class_see_corr (line 132) | def update_class_see_corr(self, logit, label):
    method get_correct_list (line 145) | def get_correct_list(logit, label):
    method get_avg_list (line 150) | def get_avg_list(all_list):
  class PerfTrackTrain (line 156) | class PerfTrackTrain(PerfTrackVal):
    method __init__ (line 160) | def __init__(self, task, extra_param=None):
    method update_loss (line 165) | def update_loss(self, loss):
    method agg_loss (line 168) | def agg_loss(self):
    method update_all (line 172) | def update_all(self, data_batch, out, loss):
  function smooth_loss (line 178) | def smooth_loss(pred, gold):
  function rscnn_voting_evaluate_cls (line 192) | def rscnn_voting_evaluate_cls(loader, model, data_batch_to_points_target,
  function pn2_vote_evaluate_cls (line 279) | def pn2_vote_evaluate_cls(dataloader, model, log_file, num_votes=[12]):

FILE: aug_utils.py
  function cutmix_r (line 8) | def cutmix_r(data_batch,cfg):
  function cutmix_k (line 50) | def cutmix_k(data_batch,cfg):
  function mixup (line 95) | def mixup(data_batch,cfg):
  function knn_points (line 130) | def knn_points(k, xyz, query, nsample=512):
  function cut_points_knn (line 154) | def cut_points_knn(data_batch, idx, radius, nsample=512, k=512):
  function cut_points (line 173) | def cut_points(data_batch, idx, radius, nsample=512):
  function query_ball_point_for_rsmix (line 193) | def query_ball_point_for_rsmix(radius, nsample, xyz, new_xyz):
  function square_distance (line 223) | def square_distance(src, dst):
  function pts_num_ctrl (line 250) | def pts_num_ctrl(pts_erase_idx, pts_add_idx):
  function rsmix (line 266) | def rsmix(data, cfg, n_sample=512, KNN=False):
  function pgd (line 331) | def pgd(data_batch,model, task, loss_name, dataset_name, step= 7, eps=0....

FILE: configs.py
  function get_cfg_defaults (line 106) | def get_cfg_defaults():

FILE: data/convert.py
  function load_mesh (line 4) | def load_mesh(filepath):
  function export_mesh (line 8) | def export_mesh(mesh, filepath):
  function load_pcd (line 12) | def load_pcd(filepath):
  function export_pcd (line 16) | def export_pcd(pcd, filepath):
  function mesh_to_pcd (line 20) | def mesh_to_pcd(mesh, number_of_points=2048):

FILE: data/create_modelnet40_small.py
  function main (line 9) | def main(split_size):

FILE: data/create_modelnet40_valid.py
  function main (line 7) | def main():

FILE: data/distortion.py
  function core_distortion (line 9) | def core_distortion(points, n_control_points=[2,2,2], displacement=None):
  function distortion (line 28) | def distortion(points, direction_mask=np.array([1,1,1]), point_mask=np.o...
  function distortion_2 (line 44) | def distortion_2(points, severity=(0.4,3), func = 'gaussian_spline'):
  function distortion_3 (line 65) | def distortion_3(points, severity=(0.4,3)):

FILE: data/generate_c.py
  function rotation (line 19) | def rotation(pointcloud,severity):
  function shear (line 39) | def shear(pointcloud,severity):
  function scale (line 56) | def scale(pointcloud,severity):
  function uniform_noise (line 82) | def uniform_noise(pointcloud, severity):
  function gaussian_noise (line 93) | def gaussian_noise(pointcloud, severity):
  function background_noise (line 104) | def background_noise(pointcloud, severity):
  function upsampling (line 114) | def upsampling(pointcloud, severity):
  function impulse_noise (line 125) | def impulse_noise(pointcloud, severity):
  function cutout (line 137) | def cutout(pointcloud, severity):
  function uniform_sampling (line 153) | def uniform_sampling(pointcloud, severity):
  function density_inc (line 162) | def density_inc(pointcloud, severity):
  function density (line 187) | def density(pointcloud, severity):
  function occlusion (line 202) | def occlusion(severity):
  function simulate_lidar (line 238) | def simulate_lidar(pointcloud,pose,severity):
  function lidar (line 270) | def lidar(severity):
  function ffd_distortion (line 309) | def ffd_distortion(pointcloud, severity):
  function rbf_distortion (line 315) | def rbf_distortion(pointcloud, severity):
  function rbf_distortion_inv (line 321) | def rbf_distortion_inv(pointcloud, severity):
  function load_data (line 329) | def load_data():
  function save_data (line 352) | def save_data(data,corruption,severity):

FILE: data/occlusion.py
  function random_pose (line 7) | def random_pose(severity):
  function lidar_pose (line 32) | def lidar_pose(severity):
  function get_default_camera_extrinsic (line 58) | def get_default_camera_extrinsic():
  function get_default_camera_intrinsic (line 65) | def get_default_camera_intrinsic(width=1920, height=1080):
  function core_occlusion (line 76) | def core_occlusion(mesh, type, camera_extrinsic=None, camera_intrinsic=N...
  function occlusion_1 (line 114) | def occlusion_1(mesh, type, severity, window_width=1080, window_height=7...

FILE: data/util.py
  function get_points (line 6) | def get_points(data):
  function set_points (line 15) | def set_points(data, points):
  function normalize (line 26) | def normalize(new_pc):
  function denomalize (line 41) | def denomalize(points, scale, offset, hard_copy=False):
  function shuffle_data (line 51) | def shuffle_data(data):
  function appendSpherical_np (line 58) | def appendSpherical_np(xyz):
  function appendCart_np (line 67) | def appendCart_np(xyz):

FILE: dataloader.py
  class ModelNet40Rscnn (line 18) | class ModelNet40Rscnn(Dataset):
    method __init__ (line 19) | def __init__(self, split, data_path, train_data_path,
    method __len__ (line 39) | def __len__(self):
    method __getitem__ (line 42) | def __getitem__(self, idx):
    method batch_proc (line 50) | def batch_proc(self, data_batch, device):
  class ModelNet40PN2 (line 75) | class ModelNet40PN2(Dataset):
    method __init__ (line 76) | def __init__(self, split, train_data_path,
    method __len__ (line 105) | def __len__(self):
    method __getitem__ (line 108) | def __getitem__(self, idx):
    method batch_proc (line 111) | def batch_proc(self, data_batch, device):
  class ModelNet40Dgcnn (line 123) | class ModelNet40Dgcnn(Dataset):
    method __init__ (line 124) | def __init__(self, split, train_data_path,
    method __len__ (line 140) | def __len__(self):
    method __getitem__ (line 143) | def __getitem__(self, idx):
  function load_data (line 147) | def load_data(data_path,corruption,severity):
  class ModelNet40C (line 157) | class ModelNet40C(Dataset):
    method __init__ (line 158) | def __init__(self, split, test_data_path,corruption,severity):
    method __getitem__ (line 171) | def __getitem__(self, item):
    method __len__ (line 176) | def __len__(self):
  function create_dataloader (line 180) | def create_dataloader(split, cfg):

FILE: dgcnn/pytorch/data.py
  function download (line 19) | def download():
  function load_data (line 32) | def load_data(data_path):
  function translate_pointcloud (line 53) | def translate_pointcloud(pointcloud):
  function jitter_pointcloud (line 61) | def jitter_pointcloud(pointcloud, sigma=0.01, clip=0.02):
  class ModelNet40 (line 67) | class ModelNet40(Dataset):
    method __init__ (line 68) | def __init__(self, num_points, data_path, partition='train'):
    method __getitem__ (line 73) | def __getitem__(self, item):
    method __len__ (line 81) | def __len__(self):

FILE: dgcnn/pytorch/main.py
  function _init_ (line 27) | def _init_():
  function train (line 39) | def train(args, io):
  function test (line 139) | def test(args, io):

FILE: dgcnn/pytorch/model.py
  function knn (line 21) | def knn(x, k):
  function get_graph_feature (line 30) | def get_graph_feature(x, k=20, idx=None):
  class PointNet (line 56) | class PointNet(nn.Module):
    method __init__ (line 57) | def __init__(self, args, output_channels=40):
    method forward (line 75) | def forward(self, x):
  class DGCNN (line 88) | class DGCNN(nn.Module):
    method __init__ (line 89) | def __init__(self, args, output_channels=40):
    method forward (line 131) | def forward(self, x):

FILE: dgcnn/pytorch/util.py
  function cal_loss (line 16) | def cal_loss(pred, gold, smoothing=True):
  class IOStream (line 36) | class IOStream():
    method __init__ (line 37) | def __init__(self, path):
    method cprint (line 40) | def cprint(self, text):
    method close (line 45) | def close(self):

FILE: dgcnn/tensorflow/evaluate.py
  function log_string (line 51) | def log_string(out_str):
  function evaluate (line 56) | def evaluate(num_votes):
  function eval_one_epoch (line 90) | def eval_one_epoch(sess, ops, num_votes=1, topk=1):

FILE: dgcnn/tensorflow/models/dgcnn.py
  function placeholder_inputs (line 14) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 20) | def get_model(point_cloud, is_training, bn_decay=None):
  function get_loss (line 101) | def get_loss(pred, label, end_points):

FILE: dgcnn/tensorflow/models/transform_nets.py
  function input_transform_net (line 10) | def input_transform_net(edge_feature, is_training, bn_decay=None, K=3, i...

FILE: dgcnn/tensorflow/part_seg/part_seg_model.py
  function get_model (line 14) | def get_model(point_cloud, input_label, is_training, cat_num, part_num, \
  function get_loss (line 123) | def get_loss(seg_pred, seg):

FILE: dgcnn/tensorflow/part_seg/test.py
  function printout (line 56) | def printout(flog, data):
  function output_color_point_cloud (line 60) | def output_color_point_cloud(data, seg, out_file):
  function output_color_point_cloud_red_blue (line 67) | def output_color_point_cloud_red_blue(data, seg, out_file):
  function pc_normalize (line 81) | def pc_normalize(pc):
  function placeholder_inputs (line 89) | def placeholder_inputs():
  function output_color_point_cloud (line 94) | def output_color_point_cloud(data, seg, out_file):
  function load_pts_seg_files (line 101) | def load_pts_seg_files(pts_file, seg_file, catid):
  function pc_augment_to_point_num (line 110) | def pc_augment_to_point_num(pts, pn):
  function convert_label_to_one_hot (line 119) | def convert_label_to_one_hot(labels):
  function predict (line 125) | def predict():

FILE: dgcnn/tensorflow/part_seg/train_multi_gpu.py
  function printout (line 84) | def printout(flog, data):
  function convert_label_to_one_hot (line 88) | def convert_label_to_one_hot(labels):
  function average_gradients (line 94) | def average_gradients(tower_grads):
  function train (line 131) | def train():

FILE: dgcnn/tensorflow/provider.py
  function shuffle_data (line 20) | def shuffle_data(data, labels):
  function rotate_point_cloud (line 33) | def rotate_point_cloud(batch_data):
  function rotate_point_cloud_by_angle (line 54) | def rotate_point_cloud_by_angle(batch_data, rotation_angle):
  function rotate_perturbation_point_cloud (line 74) | def rotate_perturbation_point_cloud(batch_data, angle_sigma=0.06, angle_...
  function jitter_point_cloud (line 99) | def jitter_point_cloud(batch_data, sigma=0.01, clip=0.05):
  function shift_point_cloud (line 112) | def shift_point_cloud(batch_data, shift_range=0.1):
  function random_scale_point_cloud (line 126) | def random_scale_point_cloud(batch_data, scale_low=0.8, scale_high=1.25):
  function getDataFiles (line 139) | def getDataFiles(list_filename):
  function load_h5 (line 142) | def load_h5(h5_filename):
  function loadDataFile (line 148) | def loadDataFile(filename):
  function load_h5_data_label_seg (line 152) | def load_h5_data_label_seg(h5_filename):

FILE: dgcnn/tensorflow/sem_seg/batch_inference.py
  function log_string (line 34) | def log_string(out_str):
  function evaluate (line 39) | def evaluate():
  function eval_one_epoch (line 85) | def eval_one_epoch(sess, ops, room_path, out_data_label_filename, out_gt...

FILE: dgcnn/tensorflow/sem_seg/indoor3d_util.py
  function collect_point_label (line 37) | def collect_point_label(anno_path, out_filename, file_format='txt'):
  function point_label_to_obj (line 80) | def point_label_to_obj(input_filename, out_filename, label_color=True, e...
  function sample_data (line 111) | def sample_data(data, num_sample):
  function sample_data_label (line 128) | def sample_data_label(data, label, num_sample):
  function room2blocks (line 133) | def room2blocks(data, label, num_point, block_size=1.0, stride=1.0,
  function room2blocks_plus (line 205) | def room2blocks_plus(data_label, num_point, block_size, stride,
  function room2blocks_wrapper (line 216) | def room2blocks_wrapper(data_label_filename, num_point, block_size=1.0, ...
  function room2blocks_plus_normalized (line 228) | def room2blocks_plus_normalized(data_label, num_point, block_size, stride,
  function room2blocks_wrapper_normalized (line 255) | def room2blocks_wrapper_normalized(data_label_filename, num_point, block...
  function room2samples (line 267) | def room2samples(data, label, sample_num_point):
  function room2samples_plus_normalized (line 303) | def room2samples_plus_normalized(data_label, num_point):
  function room2samples_wrapper_normalized (line 329) | def room2samples_wrapper_normalized(data_label_filename, num_point):
  function collect_bounding_box (line 344) | def collect_bounding_box(anno_path, out_filename):
  function bbox_label_to_obj (line 386) | def bbox_label_to_obj(input_filename, out_filename_prefix, easy_view=Fal...
  function bbox_label_to_obj_room (line 449) | def bbox_label_to_obj_room(input_filename, out_filename_prefix, easy_vie...
  function collect_point_bounding_box (line 528) | def collect_point_bounding_box(anno_path, out_filename, file_format):

FILE: dgcnn/tensorflow/sem_seg/model.py
  function placeholder_inputs (line 13) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 20) | def get_model(point_cloud, is_training, bn_decay=None):
  function get_loss (line 109) | def get_loss(pred, label):

FILE: dgcnn/tensorflow/sem_seg/train.py
  function log_string (line 95) | def log_string(out_str):
  function get_learning_rate (line 101) | def get_learning_rate(batch):
  function get_bn_decay (line 111) | def get_bn_decay(batch):
  function average_gradients (line 121) | def average_gradients(tower_grads):
  function train (line 155) | def train():
  function train_one_epoch (line 243) | def train_one_epoch(sess, ops, train_writer):

FILE: dgcnn/tensorflow/train.py
  function log_string (line 67) | def log_string(out_str):
  function get_learning_rate (line 73) | def get_learning_rate(batch):
  function get_bn_decay (line 83) | def get_bn_decay(batch):
  function train (line 93) | def train():
  function train_one_epoch (line 171) | def train_one_epoch(sess, ops, train_writer):
  function eval_one_epoch (line 220) | def eval_one_epoch(sess, ops, test_writer):

FILE: dgcnn/tensorflow/utils/data_prep_util.py
  function export_ply (line 15) | def export_ply(pc, filename):
  function get_sampling_command (line 23) | def get_sampling_command(obj_filename, ply_filename):
  function get_category_names (line 35) | def get_category_names():
  function get_obj_filenames (line 41) | def get_obj_filenames():
  function batch_mkdir (line 48) | def batch_mkdir(output_folder, subdir_list):
  function save_h5_data_label_normal (line 60) | def save_h5_data_label_normal(h5_filename, data, label, normal,
  function save_h5 (line 79) | def save_h5(h5_filename, data, label, data_dtype='uint8', label_dtype='u...
  function load_h5_data_label_normal (line 92) | def load_h5_data_label_normal(h5_filename):
  function load_h5_data_label_seg (line 100) | def load_h5_data_label_seg(h5_filename):
  function load_h5 (line 108) | def load_h5(h5_filename):
  function load_ply_data (line 119) | def load_ply_data(filename, point_num):
  function load_ply_normal (line 126) | def load_ply_normal(filename, point_num):
  function pad_arr_rows (line 134) | def pad_arr_rows(arr, row, pad='edge'):

FILE: dgcnn/tensorflow/utils/eulerangles.py
  function euler2mat (line 98) | def euler2mat(z=0, y=0, x=0):
  function mat2euler (line 198) | def mat2euler(M, cy_thresh=None):
  function euler2quat (line 271) | def euler2quat(z=0, y=0, x=0):
  function quat2euler (line 319) | def quat2euler(q):
  function euler2angle_axis (line 348) | def euler2angle_axis(z=0, y=0, x=0):
  function angle_axis2euler (line 382) | def angle_axis2euler(theta, vector, is_normalized=False):

FILE: dgcnn/tensorflow/utils/pc_util.py
  function point_cloud_to_volume_batch (line 24) | def point_cloud_to_volume_batch(point_clouds, vsize=12, radius=1.0, flat...
  function point_cloud_to_volume (line 41) | def point_cloud_to_volume(points, vsize, radius=1.0):
  function volume_to_point_cloud (line 56) | def volume_to_point_cloud(vol):
  function read_ply (line 77) | def read_ply(filename):
  function write_ply (line 85) | def write_ply(points, filename, text=True):
  function draw_point_cloud (line 97) | def draw_point_cloud(input_points, canvasSize=500, space=200, diameter=25,
  function point_cloud_three_views (line 156) | def point_cloud_three_views(points):
  function point_cloud_three_views_demo (line 171) | def point_cloud_three_views_demo():
  function pyplot_draw_point_cloud (line 183) | def pyplot_draw_point_cloud(points, output_filename):
  function pyplot_draw_volume (line 193) | def pyplot_draw_volume(vol, output_filename):

FILE: dgcnn/tensorflow/utils/plyfile.py
  function _lookup_type (line 80) | def _lookup_type(type_str):
  function _split_line (line 91) | def _split_line(line, n):
  function make2d (line 101) | def make2d(array, cols=None, dtype=None):
  class PlyParseError (line 121) | class PlyParseError(Exception):
    method __init__ (line 131) | def __init__(self, message, element=None, row=None, prop=None):
    method __repr__ (line 148) | def __repr__(self):
  class PlyData (line 153) | class PlyData(object):
    method __init__ (line 165) | def __init__(self, elements=[], text=False, byte_order='=',
    method _get_elements (line 193) | def _get_elements(self):
    method _set_elements (line 196) | def _set_elements(self, elements):
    method _get_byte_order (line 202) | def _get_byte_order(self):
    method _set_byte_order (line 205) | def _set_byte_order(self, byte_order):
    method _index (line 213) | def _index(self):
    method _parse_header (line 220) | def _parse_header(stream):
    method read (line 275) | def read(stream):
    method write (line 291) | def write(self, stream):
    method header (line 307) | def header(self):
    method __iter__ (line 333) | def __iter__(self):
    method __len__ (line 336) | def __len__(self):
    method __contains__ (line 339) | def __contains__(self, name):
    method __getitem__ (line 342) | def __getitem__(self, name):
    method __str__ (line 345) | def __str__(self):
    method __repr__ (line 348) | def __repr__(self):
  function _open_stream (line 355) | def _open_stream(stream, read_or_write):
  class PlyElement (line 364) | class PlyElement(object):
    method __init__ (line 379) | def __init__(self, name, properties, count, comments=[]):
    method count (line 400) | def count(self):
    method _get_data (line 403) | def _get_data(self):
    method _set_data (line 406) | def _set_data(self, data):
    method _check_sanity (line 413) | def _check_sanity(self):
    method _get_properties (line 418) | def _get_properties(self):
    method _set_properties (line 421) | def _set_properties(self, properties):
    method _index (line 428) | def _index(self):
    method ply_property (line 434) | def ply_property(self, name):
    method name (line 438) | def name(self):
    method _check_name (line 441) | def _check_name(self):
    method dtype (line 446) | def dtype(self, byte_order='='):
    method _parse_multi (line 458) | def _parse_multi(header_lines):
    method _parse_one (line 471) | def _parse_one(lines):
    method describe (line 507) | def describe(data, name, len_types={}, val_types={},
    method _read (line 567) | def _read(self, stream, text, byte_order):
    method _write (line 593) | def _write(self, stream, text, byte_order):
    method _read_txt (line 611) | def _read_txt(self, stream):
    method _write_txt (line 643) | def _write_txt(self, stream):
    method _read_bin (line 656) | def _read_bin(self, stream, byte_order):
    method _write_bin (line 673) | def _write_bin(self, stream, byte_order):
    method header (line 684) | def header(self):
    method __getitem__ (line 701) | def __getitem__(self, key):
    method __setitem__ (line 704) | def __setitem__(self, key, value):
    method __str__ (line 707) | def __str__(self):
    method __repr__ (line 710) | def __repr__(self):
  class PlyProperty (line 716) | class PlyProperty(object):
    method __init__ (line 724) | def __init__(self, name, val_dtype):
    method _get_val_dtype (line 729) | def _get_val_dtype(self):
    method _set_val_dtype (line 732) | def _set_val_dtype(self, val_dtype):
    method name (line 738) | def name(self):
    method _check_name (line 741) | def _check_name(self):
    method _parse_one (line 747) | def _parse_one(line):
    method dtype (line 770) | def dtype(self, byte_order='='):
    method _from_fields (line 778) | def _from_fields(self, fields):
    method _to_fields (line 786) | def _to_fields(self, data):
    method _read_bin (line 793) | def _read_bin(self, stream, byte_order):
    method _write_bin (line 804) | def _write_bin(self, data, stream, byte_order):
    method __str__ (line 811) | def __str__(self):
    method __repr__ (line 815) | def __repr__(self):
  class PlyListProperty (line 820) | class PlyListProperty(PlyProperty):
    method __init__ (line 827) | def __init__(self, name, len_dtype, val_dtype):
    method _get_len_dtype (line 832) | def _get_len_dtype(self):
    method _set_len_dtype (line 835) | def _set_len_dtype(self, len_dtype):
    method dtype (line 840) | def dtype(self, byte_order='='):
    method list_dtype (line 847) | def list_dtype(self, byte_order='='):
    method _from_fields (line 856) | def _from_fields(self, fields):
    method _to_fields (line 867) | def _to_fields(self, data):
    method _read_bin (line 881) | def _read_bin(self, stream, byte_order):
    method _write_bin (line 895) | def _write_bin(self, data, stream, byte_order):
    method __str__ (line 907) | def __str__(self):
    method __repr__ (line 912) | def __repr__(self):

FILE: dgcnn/tensorflow/utils/tf_util.py
  function _variable_on_cpu (line 12) | def _variable_on_cpu(name, shape, initializer, use_fp16=False, trainable...
  function _variable_with_weight_decay (line 26) | def _variable_with_weight_decay(name, shape, stddev, wd, use_xavier=True):
  function conv1d (line 54) | def conv1d(inputs,
  function conv2d (line 115) | def conv2d(inputs,
  function conv2d_transpose (line 176) | def conv2d_transpose(inputs,
  function conv3d (line 257) | def conv3d(inputs,
  function fully_connected (line 317) | def fully_connected(inputs,
  function max_pool2d (line 357) | def max_pool2d(inputs,
  function avg_pool2d (line 382) | def avg_pool2d(inputs,
  function max_pool3d (line 408) | def max_pool3d(inputs,
  function avg_pool3d (line 433) | def avg_pool3d(inputs,
  function batch_norm_template (line 462) | def batch_norm_template(inputs, is_training, scope, moments_dims, bn_dec...
  function batch_norm_dist_template (line 502) | def batch_norm_dist_template(inputs, is_training, scope, moments_dims, b...
  function batch_norm_for_fc (line 539) | def batch_norm_for_fc(inputs, is_training, bn_decay, scope, is_dist=False):
  function batch_norm_for_conv1d (line 557) | def batch_norm_for_conv1d(inputs, is_training, bn_decay, scope, is_dist=...
  function batch_norm_for_conv2d (line 577) | def batch_norm_for_conv2d(inputs, is_training, bn_decay, scope, is_dist=...
  function batch_norm_for_conv3d (line 596) | def batch_norm_for_conv3d(inputs, is_training, bn_decay, scope, is_dist=...
  function dropout (line 614) | def dropout(inputs,
  function pairwise_distance (line 638) | def pairwise_distance(point_cloud):
  function knn (line 660) | def knn(adj_matrix, k=20):
  function get_edge_feature (line 674) | def get_edge_feature(point_cloud, nn_idx, k=20):

FILE: emd/emd.cpp
  function emd_forward (line 14) | int emd_forward(at::Tensor xyz1, at::Tensor xyz2, at::Tensor dist, at::T...
  function emd_backward (line 20) | int emd_backward(at::Tensor xyz1, at::Tensor xyz2, at::Tensor gradxyz, a...
  function PYBIND11_MODULE (line 28) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: emd/emd_module.py
  class emdFunction (line 31) | class emdFunction(Function):
    method forward (line 33) | def forward(ctx, xyz1, xyz2, eps, iters):
    method backward (line 64) | def backward(ctx, graddist, gradidx):
  class emdModule (line 74) | class emdModule(nn.Module):
    method __init__ (line 75) | def __init__(self):
    method forward (line 78) | def forward(self, input1, input2, eps, iters):
  function test_emd (line 81) | def test_emd():

FILE: gdrivedl.py
  function output (line 39) | def output(text):
  function sanitize (line 47) | def sanitize(filename):
  function url_to_id (line 87) | def url_to_id(url):
  class GDriveDL (line 96) | class GDriveDL(object):
    method __init__ (line 97) | def __init__(self, quiet=False, overwrite=False):
    method _request (line 103) | def _request(self, url):
    method process_url (line 108) | def process_url(self, url, directory, filename=None):
    method process_folder (line 126) | def process_folder(self, id, directory):
    method process_file (line 150) | def process_file(self, id, directory, filename=None, confirm=''):
  function main (line 214) | def main(args=None):

FILE: main.py
  function adapt_bn (line 30) | def adapt_bn(data,model,cfg):
  function adapt_tent (line 38) | def adapt_tent(data,model,cfg):
  function check_inp_fmt (line 51) | def check_inp_fmt(task, data_batch, dataset_name):
  function check_out_fmt (line 77) | def check_out_fmt(task, out, dataset_name):
  function get_inp (line 100) | def get_inp(task, model, data_batch, batch_proc, dataset_name):
  function get_loss (line 120) | def get_loss(task, loss_name, data_batch, out, dataset_name):
  function validate (line 202) | def validate(task, loader, model, dataset_name, adapt = None, confusion ...
  function train (line 258) | def train(task, loader, model, optimizer, loss_name, dataset_name, cfg):
  function save_checkpoint (line 327) | def save_checkpoint(id, epoch, model, optimizer,  lr_sched, bnm_sched, t...
  function load_best_checkpoint (line 343) | def load_best_checkpoint(model, cfg):
  function load_model_opt_sched (line 350) | def load_model_opt_sched(model, optimizer, lr_sched, bnm_sched, model_pa...
  function get_model (line 375) | def get_model(cfg):
  function get_metric_from_perf (line 425) | def get_metric_from_perf(task, perf, metric_name):
  function get_optimizer (line 434) | def get_optimizer(optim_name, tr_arg, model):
  function entry_train (line 465) | def entry_train(cfg, resume=False, model_path=""):
  function entry_test (line 551) | def entry_test(cfg, test_or_valid, model_path="", confusion = False):
  function rscnn_vote_evaluation (line 578) | def rscnn_vote_evaluation(cfg, model_path, log_file):
  function pn2_vote_evaluation (line 604) | def pn2_vote_evaluation(cfg, model_path, log_file):

FILE: models/curvenet.py
  class CurveNet (line 13) | class CurveNet(nn.Module):
    method __init__ (line 15) | def __init__(self, task, dataset):
    method forward (line 27) | def forward(self, pc, cls=None):

FILE: models/dgcnn.py
  class DGCNN (line 7) | class DGCNN(nn.Module):
    method __init__ (line 9) | def __init__(self, task, dataset):
    method forward (line 29) | def forward(self, pc, cls=None):

FILE: models/gdanet.py
  class GDANET (line 13) | class GDANET(nn.Module):
    method __init__ (line 15) | def __init__(self, task, dataset):
    method forward (line 24) | def forward(self, pc, normal=None, cls=None):

FILE: models/model_utils.py
  class Squeeze (line 4) | class Squeeze(nn.Module):
    method __init__ (line 5) | def __init__(self):
    method forward (line 8) | def forward(self, inp):
  class BatchNormPoint (line 11) | class BatchNormPoint(nn.Module):
    method __init__ (line 12) | def __init__(self, feat_size, sync_bn=False):
    method forward (line 21) | def forward(self, x):

FILE: models/mv.py
  class MVModel (line 8) | class MVModel(nn.Module):
    method __init__ (line 9) | def __init__(self, task, dataset, backbone,
    method forward (line 33) | def forward(self, pc):
    method get_img (line 46) | def get_img(self, pc):
    method get_img_layers (line 58) | def get_img_layers(backbone, feat_size):
  class MVFC (line 95) | class MVFC(nn.Module):
    method __init__ (line 100) | def __init__(self, num_views, in_features, out_features, dropout_p):
    method forward (line 117) | def forward(self, feat):

FILE: models/mv_utils.py
  function euler2mat (line 7) | def euler2mat(angle):
  function distribute (line 59) | def distribute(depth, _x, _y, size_x, size_y, image_height, image_width):
  function points2depth (line 135) | def points2depth(points, image_height, image_width, size_x=4, size_y=4):
  function batched_index_select (line 174) | def batched_index_select(inp, dim, index):
  function point_fea_img_fea (line 189) | def point_fea_img_fea(point_fea, point_coo, h, w):
  function distribute_img_fea_points (line 212) | def distribute_img_fea_points(img_fea, point_coord):
  class PCViews (line 234) | class PCViews:
    method __init__ (line 239) | def __init__(self):
    method get_img (line 253) | def get_img(self, points):
    method point_transform (line 280) | def point_transform(points, rot_mat, translation):

FILE: models/pct.py
  class Pct (line 5) | class Pct(nn.Module):
    method __init__ (line 7) | def __init__(self, task, dataset):
    method forward (line 24) | def forward(self, pc, cls=None):

FILE: models/pointmlp.py
  class pointMLP (line 13) | class pointMLP(nn.Module):
    method __init__ (line 15) | def __init__(self, task, dataset):
    method forward (line 27) | def forward(self, pc, cls=None):

FILE: models/pointmlp2.py
  class pointMLP2 (line 12) | class pointMLP2(nn.Module):
    method __init__ (line 14) | def __init__(self, task, dataset):
    method forward (line 26) | def forward(self, pc, cls=None):

FILE: models/pointnet.py
  class PointNet (line 6) | class PointNet(nn.Module):
    method __init__ (line 8) | def __init__(self, dataset, task):
    method forward (line 17) | def forward(self, pc, cls=None):

FILE: models/pointnet2.py
  class PointNet2 (line 13) | class PointNet2(nn.Module):
    method __init__ (line 15) | def __init__(self, task, dataset, version_cls):
    method forward (line 24) | def forward(self, pc, normal=None, cls=None):

FILE: models/resnet.py
  function conv3x3 (line 24) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 30) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 35) | class BasicBlock(nn.Module):
    method __init__ (line 38) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 56) | def forward(self, x):
  class Bottleneck (line 75) | class Bottleneck(nn.Module):
    method __init__ (line 84) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 101) | def forward(self, x):
  class ResNet (line 124) | class ResNet(nn.Module):
    method __init__ (line 126) | def __init__(self, block, layers, num_classes=1000, zero_init_residual...
    method _make_layer (line 177) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method _forward_impl (line 201) | def _forward_impl(self, x):
    method forward (line 219) | def forward(self, x):
  function _resnet (line 223) | def _resnet(arch, block, layers, pretrained, progress, **kwargs):
  function resnet18 (line 232) | def resnet18(pretrained=False, progress=True, **kwargs):
  function resnet34 (line 243) | def resnet34(pretrained=False, progress=True, **kwargs):
  function resnet50 (line 254) | def resnet50(pretrained=False, progress=True, **kwargs):
  function resnet101 (line 265) | def resnet101(pretrained=False, progress=True, **kwargs):
  function resnet152 (line 276) | def resnet152(pretrained=False, progress=True, **kwargs):
  function resnext50_32x4d (line 287) | def resnext50_32x4d(pretrained=False, progress=True, **kwargs):
  function resnext101_32x8d (line 300) | def resnext101_32x8d(pretrained=False, progress=True, **kwargs):
  function wide_resnet50_2 (line 313) | def wide_resnet50_2(pretrained=False, progress=True, **kwargs):
  function wide_resnet101_2 (line 329) | def wide_resnet101_2(pretrained=False, progress=True, **kwargs):

FILE: models/rscnn.py
  class RSCNN (line 9) | class RSCNN(nn.Module):
    method __init__ (line 11) | def __init__(self, task, dataset, ssn_or_msn):
    method forward (line 35) | def forward(self, pc, cls=None):

FILE: pc_utils.py
  function jitter_point_cloud (line 5) | def jitter_point_cloud(batch_data, sigma=0.01, clip=0.05):
  function rotate_point_cloud (line 19) | def rotate_point_cloud(batch_data):
  function translate_pointcloud (line 40) | def translate_pointcloud(pointcloud):
  class PointcloudScaleAndTranslate (line 48) | class PointcloudScaleAndTranslate(object):
    method __init__ (line 49) | def __init__(self, scale_low=2. / 3., scale_high=3. / 2., translate_ra...
    method __call__ (line 61) | def __call__(self, pc):

FILE: pointMLP/classification_ModelNet40/data.py
  function download (line 8) | def download():
  function load_data (line 20) | def load_data(partition):
  function random_point_dropout (line 38) | def random_point_dropout(pc, max_dropout_ratio=0.875):
  function translate_pointcloud (line 49) | def translate_pointcloud(pointcloud):
  function jitter_pointcloud (line 56) | def jitter_pointcloud(pointcloud, sigma=0.01, clip=0.02):
  class ModelNet40 (line 62) | class ModelNet40(Dataset):
    method __init__ (line 63) | def __init__(self, num_points, partition='train'):
    method __getitem__ (line 68) | def __getitem__(self, item):
    method __len__ (line 77) | def __len__(self):

FILE: pointMLP/classification_ModelNet40/helper.py
  function cal_loss (line 4) | def cal_loss(pred, gold, smoothing=True):

FILE: pointMLP/classification_ModelNet40/main.py
  function parse_args (line 24) | def parse_args():
  function main (line 42) | def main():
  function train (line 179) | def train(net, trainloader, optimizer, criterion, device):
  function validate (line 219) | def validate(net, testloader, criterion, device):

FILE: pointMLP/classification_ModelNet40/models/pointmlp.py
  function get_activation (line 12) | def get_activation(activation):
  function square_distance (line 29) | def square_distance(src, dst):
  function index_points (line 51) | def index_points(points, idx):
  function farthest_point_sample (line 70) | def farthest_point_sample(xyz, npoint):
  function query_ball_point (line 93) | def query_ball_point(radius, nsample, xyz, new_xyz):
  function knn_point (line 116) | def knn_point(nsample, xyz, new_xyz):
  class LocalGrouper (line 130) | class LocalGrouper(nn.Module):
    method __init__ (line 131) | def __init__(self, channel, groups, kneighbors, use_xyz=True, normaliz...
    method forward (line 154) | def forward(self, xyz, points):
  class ConvBNReLU1D (line 185) | class ConvBNReLU1D(nn.Module):
    method __init__ (line 186) | def __init__(self, in_channels, out_channels, kernel_size=1, bias=True...
    method forward (line 195) | def forward(self, x):
  class ConvBNReLURes1D (line 199) | class ConvBNReLURes1D(nn.Module):
    method __init__ (line 200) | def __init__(self, channel, kernel_size=1, groups=1, res_expansion=1.0...
    method forward (line 226) | def forward(self, x):
  class PreExtraction (line 230) | class PreExtraction(nn.Module):
    method __init__ (line 231) | def __init__(self, channels, out_channels,  blocks=1, groups=1, res_ex...
    method forward (line 249) | def forward(self, x):
  class PosExtraction (line 261) | class PosExtraction(nn.Module):
    method __init__ (line 262) | def __init__(self, channels, blocks=1, groups=1, res_expansion=1, bias...
    method forward (line 276) | def forward(self, x):  # [b, d, g]
  class Model (line 280) | class Model(nn.Module):
    method __init__ (line 281) | def __init__(self, points=1024, class_num=40, embed_dim=64, groups=1, ...
    method forward (line 332) | def forward(self, x):
  function pointMLP (line 349) | def pointMLP(num_classes=40, **kwargs) -> Model:
  function pointMLPElite (line 356) | def pointMLPElite(num_classes=40, **kwargs) -> Model:

FILE: pointMLP/classification_ModelNet40/utils/logger.py
  function savefig (line 11) | def savefig(fname, dpi=None):
  function plot_overlap (line 15) | def plot_overlap(logger, names=None):
  class Logger (line 23) | class Logger(object):
    method __init__ (line 25) | def __init__(self, fpath, title=None, resume=False):
    method set_names (line 47) | def set_names(self, names):
    method append (line 61) | def append(self, numbers):
    method plot (line 70) | def plot(self, names=None):
    method close (line 79) | def close(self):
  class LoggerMonitor (line 83) | class LoggerMonitor(object):
    method __init__ (line 85) | def __init__ (self, paths):
    method plot (line 92) | def plot(self, names=None):

FILE: pointMLP/classification_ModelNet40/utils/misc.py
  function get_mean_and_std (line 26) | def get_mean_and_std(dataset):
  function init_params (line 41) | def init_params(net):
  function mkdir_p (line 56) | def mkdir_p(path):
  class AverageMeter (line 66) | class AverageMeter(object):
    method __init__ (line 70) | def __init__(self):
    method reset (line 73) | def reset(self):
    method update (line 79) | def update(self, val, n=1):
  function progress_bar (line 90) | def progress_bar(current, total, msg=None):
  function format_time (line 134) | def format_time(seconds):
  function save_model (line 167) | def save_model(net, epoch, path, acc, is_best, **kwargs):
  function save_args (line 182) | def save_args(args):
  function set_seed (line 190) | def set_seed(seed=None):
  class IOStream (line 205) | class IOStream():
    method __init__ (line 206) | def __init__(self, path):
    method cprint (line 209) | def cprint(self, text):
    method close (line 214) | def close(self):
  function cal_loss (line 218) | def cal_loss(pred, gold, smoothing=True):

FILE: pointMLP/classification_ModelNet40/utils/progress/progress/__init__.py
  class Infinite (line 27) | class Infinite(object):
    method __init__ (line 31) | def __init__(self, *args, **kwargs):
    method __getitem__ (line 40) | def __getitem__(self, key):
    method elapsed (line 46) | def elapsed(self):
    method elapsed_td (line 50) | def elapsed_td(self):
    method update_avg (line 53) | def update_avg(self, n, dt):
    method update (line 58) | def update(self):
    method start (line 61) | def start(self):
    method finish (line 64) | def finish(self):
    method next (line 67) | def next(self, n=1):
    method iter (line 75) | def iter(self, it):
  class Progress (line 84) | class Progress(Infinite):
    method __init__ (line 85) | def __init__(self, *args, **kwargs):
    method eta (line 90) | def eta(self):
    method eta_td (line 94) | def eta_td(self):
    method percent (line 98) | def percent(self):
    method progress (line 102) | def progress(self):
    method remaining (line 106) | def remaining(self):
    method start (line 109) | def start(self):
    method goto (line 112) | def goto(self, index):
    method iter (line 116) | def iter(self, it):

FILE: pointMLP/classification_ModelNet40/utils/progress/progress/bar.py
  class Bar (line 22) | class Bar(WritelnMixin, Progress):
    method update (line 32) | def update(self):
  class ChargingBar (line 45) | class ChargingBar(Bar):
  class FillingSquaresBar (line 53) | class FillingSquaresBar(ChargingBar):
  class FillingCirclesBar (line 58) | class FillingCirclesBar(ChargingBar):
  class IncrementalBar (line 63) | class IncrementalBar(Bar):
    method update (line 66) | def update(self):
  class PixelBar (line 83) | class PixelBar(IncrementalBar):
  class ShadyBar (line 87) | class ShadyBar(IncrementalBar):

FILE: pointMLP/classification_ModelNet40/utils/progress/progress/counter.py
  class Counter (line 22) | class Counter(WriteMixin, Infinite):
    method update (line 26) | def update(self):
  class Countdown (line 30) | class Countdown(WriteMixin, Progress):
    method update (line 33) | def update(self):
  class Stack (line 37) | class Stack(WriteMixin, Progress):
    method update (line 41) | def update(self):
  class Pie (line 47) | class Pie(Stack):

FILE: pointMLP/classification_ModelNet40/utils/progress/progress/helpers.py
  class WriteMixin (line 22) | class WriteMixin(object):
    method __init__ (line 25) | def __init__(self, message=None, **kwargs):
    method write (line 37) | def write(self, s):
    method finish (line 45) | def finish(self):
  class WritelnMixin (line 50) | class WritelnMixin(object):
    method __init__ (line 53) | def __init__(self, message=None, **kwargs):
    method clearln (line 61) | def clearln(self):
    method writeln (line 65) | def writeln(self, line):
    method finish (line 71) | def finish(self):
  class SigIntMixin (line 82) | class SigIntMixin(object):
    method __init__ (line 85) | def __init__(self, *args, **kwargs):
    method _sigint_handler (line 89) | def _sigint_handler(self, signum, frame):

FILE: pointMLP/classification_ModelNet40/utils/progress/progress/spinner.py
  class Spinner (line 22) | class Spinner(WriteMixin, Infinite):
    method update (line 27) | def update(self):
  class PieSpinner (line 32) | class PieSpinner(Spinner):
  class MoonSpinner (line 36) | class MoonSpinner(Spinner):
  class LineSpinner (line 40) | class LineSpinner(Spinner):
  class PixelSpinner (line 43) | class PixelSpinner(Spinner):

FILE: pointMLP/classification_ModelNet40/utils/progress/test_progress.py
  function sleep (line 16) | def sleep():

FILE: pointMLP/classification_ModelNet40/voting.py
  function parse_args (line 23) | def parse_args():
  class PointcloudScale (line 43) | class PointcloudScale(object):  # input random scaling
    method __init__ (line 44) | def __init__(self, scale_low=2. / 3., scale_high=3. / 2.):
    method __call__ (line 48) | def __call__(self, pc):
  function main (line 57) | def main():
  function validate (line 113) | def validate(net, testloader, criterion, device):
  function voting (line 147) | def voting(net, testloader, device, args):

FILE: pointnet2_pyt/pointnet2/_ext-src/include/cuda_utils.h
  function opt_n_threads (line 15) | inline int opt_n_threads(int work_size) {
  function dim3 (line 21) | inline dim3 opt_block_config(int x, int y) {

FILE: pointnet2_pyt/pointnet2/_ext-src/src/ball_query.cpp
  function ball_query (line 8) | at::Tensor ball_query(at::Tensor new_xyz, at::Tensor xyz, const float ra...

FILE: pointnet2_pyt/pointnet2/_ext-src/src/bindings.cpp
  function PYBIND11_MODULE (line 6) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: pointnet2_pyt/pointnet2/_ext-src/src/group_points.cpp
  function group_points (line 12) | at::Tensor group_points(at::Tensor points, at::Tensor idx) {
  function group_points_grad (line 37) | at::Tensor group_points_grad(at::Tensor grad_out, at::Tensor idx, const ...

FILE: pointnet2_pyt/pointnet2/_ext-src/src/interpolate.cpp
  function three_nn (line 14) | std::vector<at::Tensor> three_nn(at::Tensor unknowns, at::Tensor knows) {
  function three_interpolate (line 42) | at::Tensor three_interpolate(at::Tensor points, at::Tensor idx,
  function three_interpolate_grad (line 71) | at::Tensor three_interpolate_grad(at::Tensor grad_out, at::Tensor idx,

FILE: pointnet2_pyt/pointnet2/_ext-src/src/sampling.cpp
  function gather_points (line 15) | at::Tensor gather_points(at::Tensor points, at::Tensor idx) {
  function gather_points_grad (line 40) | at::Tensor gather_points_grad(at::Tensor grad_out, at::Tensor idx,
  function furthest_point_sampling (line 65) | at::Tensor furthest_point_sampling(at::Tensor points, const int nsamples) {

FILE: pointnet2_pyt/pointnet2/data/Indoor3DSemSegLoader.py
  function _get_data_files (line 19) | def _get_data_files(list_filename):
  function _load_data_file (line 24) | def _load_data_file(name):
  class Indoor3DSemSeg (line 31) | class Indoor3DSemSeg(data.Dataset):
    method __init__ (line 32) | def __init__(self, num_points, train=True, download=True, data_precent...
    method __getitem__ (line 84) | def __getitem__(self, idx):
    method __len__ (line 97) | def __len__(self):
    method set_num_points (line 100) | def set_num_points(self, pts):
    method randomize (line 103) | def randomize(self):

FILE: pointnet2_pyt/pointnet2/data/ModelNet40Loader.py
  function _get_data_files (line 19) | def _get_data_files(list_filename):
  function _load_data_file (line 24) | def _load_data_file(name):
  class ModelNet40Cls (line 31) | class ModelNet40Cls(data.Dataset):
    method __init__ (line 32) | def __init__(self, num_points, transforms=None, train=True, download=T...
    method __getitem__ (line 69) | def __getitem__(self, idx):
    method __len__ (line 81) | def __len__(self):
    method set_num_points (line 84) | def set_num_points(self, pts):
    method randomize (line 87) | def randomize(self):

FILE: pointnet2_pyt/pointnet2/data/data_utils.py
  function angle_axis (line 12) | def angle_axis(angle, axis):
  class PointcloudScale (line 45) | class PointcloudScale(object):
    method __init__ (line 46) | def __init__(self, lo=0.8, hi=1.25):
    method __call__ (line 49) | def __call__(self, points):
  class PointcloudRotate (line 55) | class PointcloudRotate(object):
    method __init__ (line 56) | def __init__(self, axis=np.array([0.0, 1.0, 0.0])):
    method __call__ (line 59) | def __call__(self, points):
  class PointcloudRotatePerturbation (line 75) | class PointcloudRotatePerturbation(object):
    method __init__ (line 76) | def __init__(self, angle_sigma=0.06, angle_clip=0.18):
    method _get_angles (line 79) | def _get_angles(self):
    method __call__ (line 86) | def __call__(self, points):
  class PointcloudJitter (line 106) | class PointcloudJitter(object):
    method __init__ (line 107) | def __init__(self, std=0.01, clip=0.05):
    method __call__ (line 110) | def __call__(self, points):
  class PointcloudTranslate (line 120) | class PointcloudTranslate(object):
    method __init__ (line 121) | def __init__(self, translate_range=0.1):
    method __call__ (line 124) | def __call__(self, points):
  class PointcloudToTensor (line 130) | class PointcloudToTensor(object):
    method __call__ (line 131) | def __call__(self, points):
  class PointcloudRandomInputDropout (line 135) | class PointcloudRandomInputDropout(object):
    method __init__ (line 136) | def __init__(self, max_dropout_ratio=0.875):
    method __call__ (line 140) | def __call__(self, points):

FILE: pointnet2_pyt/pointnet2/models/pointnet2_msg_cls.py
  function model_fn_decorator (line 16) | def model_fn_decorator(criterion):
  class Pointnet2MSG (line 37) | class Pointnet2MSG(nn.Module):
    method __init__ (line 53) | def __init__(self, num_classes, input_channels=3, use_xyz=True, versio...
    method _break_up_pc (line 118) | def _break_up_pc(self, pc):
    method forward (line 124) | def forward(self, pointcloud):
  class Pointnet2MSG5K (line 147) | class Pointnet2MSG5K(nn.Module):
    method __init__ (line 163) | def __init__(self, num_classes, input_channels=3, use_xyz=True):
    method _break_up_pc (line 208) | def _break_up_pc(self, pc):
    method forward (line 214) | def forward(self, pointcloud):

FILE: pointnet2_pyt/pointnet2/models/pointnet2_msg_sem.py
  function model_fn_decorator (line 16) | def model_fn_decorator(criterion):
  class Pointnet2MSG (line 36) | class Pointnet2MSG(nn.Module):
    method __init__ (line 52) | def __init__(self, num_classes, input_channels=6, use_xyz=True):
    method _break_up_pc (line 117) | def _break_up_pc(self, pc):
    method forward (line 123) | def forward(self, pointcloud):

FILE: pointnet2_pyt/pointnet2/models/pointnet2_ssg_cls.py
  function model_fn_decorator (line 16) | def model_fn_decorator(criterion):
  class Pointnet2SSG (line 37) | class Pointnet2SSG(nn.Module):
    method __init__ (line 53) | def __init__(self, num_classes, input_channels=3, use_xyz=True):
    method _break_up_pc (line 88) | def _break_up_pc(self, pc):
    method forward (line 94) | def forward(self, pointcloud):

FILE: pointnet2_pyt/pointnet2/models/pointnet2_ssg_sem.py
  function model_fn_decorator (line 16) | def model_fn_decorator(criterion):
  class Pointnet2SSG (line 36) | class Pointnet2SSG(nn.Module):
    method __init__ (line 52) | def __init__(self, num_classes, input_channels=3, use_xyz=True):
    method _break_up_pc (line 108) | def _break_up_pc(self, pc):
    method forward (line 114) | def forward(self, pointcloud):

FILE: pointnet2_pyt/pointnet2/train/train_cls.py
  function parse_args (line 29) | def parse_args():

FILE: pointnet2_pyt/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_pyt/pointnet2/utils/pointnet2_modules.py
  class _PointnetSAModuleBase (line 20) | class _PointnetSAModuleBase(nn.Module):
    method __init__ (line 21) | def __init__(self):
    method forward (line 27) | def forward(self, xyz, features=None):
  class PointnetSAModuleMSG (line 74) | class PointnetSAModuleMSG(_PointnetSAModuleBase):
    method __init__ (line 91) | def __init__(self, npoint, radii, nsamples, mlps, bn=True, use_xyz=True):
  class PointnetSAModule (line 115) | class PointnetSAModule(PointnetSAModuleMSG):
    method __init__ (line 132) | def __init__(
  class PointnetFPModule (line 146) | class PointnetFPModule(nn.Module):
    method __init__ (line 157) | def __init__(self, mlp, bn=True):
    method forward (line 162) | def forward(self, unknown, known, unknow_feats, known_feats):

FILE: pointnet2_pyt/pointnet2/utils/pointnet2_utils.py
  class RandomDropout (line 34) | class RandomDropout(nn.Module):
    method __init__ (line 35) | def __init__(self, p=0.5, inplace=False):
    method forward (line 40) | def forward(self, X):
  class FurthestPointSampling (line 45) | class FurthestPointSampling(Function):
    method forward (line 47) | def forward(ctx, xyz, npoint):
    method backward (line 68) | def backward(xyz, a=None):
  class GatherOperation (line 75) | class GatherOperation(Function):
    method forward (line 77) | def forward(ctx, features, idx):
    method backward (line 102) | def backward(ctx, grad_out):
  class ThreeNN (line 112) | class ThreeNN(Function):
    method forward (line 114) | def forward(ctx, unknown, known):
    method backward (line 137) | def backward(ctx, a=None, b=None):
  class ThreeInterpolate (line 144) | class ThreeInterpolate(Function):
    method forward (line 146) | def forward(ctx, features, idx, weight):
    method backward (line 172) | def backward(ctx, grad_out):
  class GroupingOperation (line 201) | class GroupingOperation(Function):
    method forward (line 203) | def forward(ctx, features, idx):
    method backward (line 227) | def backward(ctx, grad_out):
  class BallQuery (line 252) | class BallQuery(Function):
    method forward (line 254) | def forward(ctx, radius, nsample, xyz, new_xyz):
    method backward (line 277) | def backward(ctx, a=None):
  class QueryAndGroup (line 284) | class QueryAndGroup(nn.Module):
    method __init__ (line 296) | def __init__(self, radius, nsample, use_xyz=True):
    method forward (line 301) | def forward(self, xyz, new_xyz, features=None):
  class GroupAll (line 341) | class GroupAll(nn.Module):
    method __init__ (line 349) | def __init__(self, use_xyz=True):
    method forward (line 354) | def forward(self, xyz, new_xyz, features=None):

FILE: pointnet2_pyt/tests/conftest.py
  function _test_loop (line 15) | def _test_loop(model, model_fn, inputs, labels):
  function cls_test_xyz (line 31) | def cls_test_xyz(model, model_fn):
  function cls_test_no_xyz (line 41) | def cls_test_no_xyz(model, model_fn):
  function semseg_test_xyz (line 51) | def semseg_test_xyz(model, model_fn):
  function semseg_test_no_xyz (line 61) | def semseg_test_no_xyz(model, model_fn):

FILE: pointnet2_pyt/tests/test_cls_msg.py
  function test_xyz (line 13) | def test_xyz():
  function test_no_xyz (line 18) | def test_no_xyz():

FILE: pointnet2_pyt/tests/test_cls_ssg.py
  function test_xyz (line 13) | def test_xyz():
  function test_no_xyz (line 18) | def test_no_xyz():

FILE: pointnet2_pyt/tests/test_semseg_msg.py
  function test_xyz (line 13) | def test_xyz():
  function test_no_xyz (line 18) | def test_no_xyz():

FILE: pointnet2_pyt/tests/test_semseg_ssg.py
  function test_xyz (line 13) | def test_xyz():
  function test_no_xyz (line 18) | def test_no_xyz():

FILE: pointnet2_tf/evaluate.py
  function log_string (line 62) | def log_string(out_str):
  function evaluate (line 67) | def evaluate(num_votes):
  function eval_one_epoch (line 102) | def eval_one_epoch(sess, ops, num_votes=1, topk=1):

FILE: pointnet2_tf/modelnet_dataset.py
  function pc_normalize (line 15) | def pc_normalize(pc):
  class ModelNetDataset (line 23) | class ModelNetDataset():
    method __init__ (line 24) | def __init__(self, root, batch_size = 32, npoints = 1024, split='train...
    method _augment_batch_data (line 60) | def _augment_batch_data(self, batch_data):
    method _get_item (line 75) | def _get_item(self, index):
    method __getitem__ (line 93) | def __getitem__(self, index):
    method __len__ (line 96) | def __len__(self):
    method num_channel (line 99) | def num_channel(self):
    method reset (line 105) | def reset(self):
    method has_next_batch (line 112) | def has_next_batch(self):
    method next_batch (line 115) | def next_batch(self, augment=False):

FILE: pointnet2_tf/modelnet_h5_dataset.py
  function shuffle_data (line 24) | def shuffle_data(data, labels):
  function getDataFiles (line 36) | def getDataFiles(list_filename):
  function load_h5 (line 39) | def load_h5(h5_filename):
  function loadDataFile (line 45) | def loadDataFile(filename):
  class ModelNetH5Dataset (line 49) | class ModelNetH5Dataset(object):
    method __init__ (line 50) | def __init__(self, list_filename, batch_size = 32, npoints = 1024, shu...
    method reset (line 58) | def reset(self):
    method _augment_batch_data (line 67) | def _augment_batch_data(self, batch_data):
    method _get_data_filename (line 77) | def _get_data_filename(self):
    method _load_data_file (line 80) | def _load_data_file(self, filename):
    method _has_next_batch_in_file (line 87) | def _has_next_batch_in_file(self):
    method num_channel (line 90) | def num_channel(self):
    method has_next_batch (line 93) | def has_next_batch(self):
    method next_batch (line 103) | def next_batch(self, augment=False):

FILE: pointnet2_tf/models/pointnet2_cls_msg.py
  function placeholder_inputs (line 11) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 17) | def get_model(point_cloud, is_training, bn_decay=None):
  function get_loss (line 42) | def get_loss(pred, label, end_points):

FILE: pointnet2_tf/models/pointnet2_cls_ssg.py
  function placeholder_inputs (line 15) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 20) | def get_model(point_cloud, is_training, bn_decay=None):
  function get_loss (line 47) | def get_loss(pred, label, end_points):

FILE: pointnet2_tf/models/pointnet2_part_seg.py
  function placeholder_inputs (line 11) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 17) | def get_model(point_cloud, is_training, bn_decay=None):
  function get_loss (line 44) | def get_loss(pred, label):

FILE: pointnet2_tf/models/pointnet2_part_seg_msg_one_hot.py
  function placeholder_inputs (line 11) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 19) | def get_model(point_cloud, cls_label, is_training, bn_decay=None):
  function get_loss (line 50) | def get_loss(pred, label):

FILE: pointnet2_tf/models/pointnet2_sem_seg.py
  function placeholder_inputs (line 11) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 18) | def get_model(point_cloud, is_training, num_class, bn_decay=None):
  function get_loss (line 48) | def get_loss(pred, label, smpw):

FILE: pointnet2_tf/models/pointnet_cls_basic.py
  function placeholder_inputs (line 15) | def placeholder_inputs(batch_size, num_point):
  function get_model (line 21) | def get_model(point_cloud, is_training, bn_decay=None):
  function get_loss (line 67) | def get_loss(pred, label, end_points):

FILE: pointnet2_tf/part_seg/evaluate.py
  function log_string (line 53) | def log_string(out_str):
  function evaluate (line 58) | def evaluate():
  function get_batch (line 85) | def get_batch(dataset, idxs, start_idx, end_idx):
  function eval_one_epoch (line 96) | def eval_one_epoch(sess, ops):

FILE: pointnet2_tf/part_seg/part_dataset.py
  function pc_normalize (line 11) | def pc_normalize(pc):
  class PartDataset (line 19) | class PartDataset():
    method __init__ (line 20) | def __init__(self, root, npoints = 2500, classification = False, class...
    method __getitem__ (line 87) | def __getitem__(self, index):
    method __len__ (line 112) | def __len__(self):

FILE: pointnet2_tf/part_seg/part_dataset_all_normal.py
  function pc_normalize (line 11) | def pc_normalize(pc):
  class PartNormalDataset (line 19) | class PartNormalDataset():
    method __init__ (line 20) | def __init__(self, root, npoints = 2500, classification = False, split...
    method __getitem__ (line 83) | def __getitem__(self, index):
    method __len__ (line 114) | def __len__(self):

FILE: pointnet2_tf/part_seg/test.py
  function get_model (line 37) | def get_model(batch_size, num_point):
  function inference (line 59) | def inference(sess, ops, pc, batch_size):

FILE: pointnet2_tf/part_seg/train.py
  function log_string (line 69) | def log_string(out_str):
  function get_learning_rate (line 74) | def get_learning_rate(batch):
  function get_bn_decay (line 84) | def get_bn_decay(batch):
  function train (line 94) | def train():
  function get_batch (line 168) | def get_batch(dataset, idxs, start_idx, end_idx):
  function train_one_epoch (line 179) | def train_one_epoch(sess, ops, train_writer):
  function eval_one_epoch (line 223) | def eval_one_epoch(sess, ops, test_writer):

FILE: pointnet2_tf/part_seg/train_one_hot.py
  function log_string (line 69) | def log_string(out_str):
  function get_learning_rate (line 74) | def get_learning_rate(batch):
  function get_bn_decay (line 84) | def get_bn_decay(batch):
  function train (line 94) | def train():
  function get_batch (line 171) | def get_batch(dataset, idxs, start_idx, end_idx):
  function train_one_epoch (line 184) | def train_one_epoch(sess, ops, train_writer):
  function eval_one_epoch (line 229) | def eval_one_epoch(sess, ops, test_writer):

FILE: pointnet2_tf/scannet/pc_util.py
  function point_cloud_label_to_surface_voxel_label (line 23) | def point_cloud_label_to_surface_voxel_label(point_cloud, label, res=0.0...
  function point_cloud_label_to_surface_voxel_label_fast (line 39) | def point_cloud_label_to_surface_voxel_label_fast(point_cloud, label, re...
  function point_cloud_to_volume_batch (line 53) | def point_cloud_to_volume_batch(point_clouds, vsize=12, radius=1.0, flat...
  function point_cloud_to_volume (line 70) | def point_cloud_to_volume(points, vsize, radius=1.0):
  function volume_to_point_cloud (line 85) | def volume_to_point_cloud(vol):
  function point_cloud_to_volume_v2_batch (line 102) | def point_cloud_to_volume_v2_batch(point_clouds, vsize=12, radius=1.0, n...
  function point_cloud_to_volume_v2 (line 113) | def point_cloud_to_volume_v2(points, vsize, radius=1.0, num_sample=128):
  function point_cloud_to_image_batch (line 155) | def point_cloud_to_image_batch(point_clouds, imgsize, radius=1.0, num_sa...
  function point_cloud_to_image (line 167) | def point_cloud_to_image(points, imgsize, radius=1.0, num_sample=128):
  function read_ply (line 205) | def read_ply(filename):
  function read_ply_xyz (line 212) | def read_ply_xyz(filename):
  function read_ply_xyzrgb (line 224) | def read_ply_xyzrgb(filename):
  function write_ply (line 239) | def write_ply(points, filename, text=True):
  function draw_point_cloud (line 251) | def draw_point_cloud(input_points, canvasSize=500, space=200, diameter=25,
  function point_cloud_three_views (line 310) | def point_cloud_three_views(points):
  function point_cloud_three_views_demo (line 324) | def point_cloud_three_views_demo():
  function pyplot_draw_point_cloud (line 336) | def pyplot_draw_point_cloud(points, output_filename):
  function pyplot_draw_volume (line 347) | def pyplot_draw_volume(vol, output_filename):
  function write_ply_color (line 354) | def write_ply_color(points, labels, out_filename, num_classes=None):
  function write_ply_rgb (line 371) | def write_ply_rgb(points, colors, out_filename, num_classes=None):

FILE: pointnet2_tf/scannet/preprocessing/collect_scannet_scenes.py
  function collect_one_scene_data_label (line 19) | def collect_one_scene_data_label(scene_name, out_filename):
  function log_string (line 82) | def log_string(out_str):

FILE: pointnet2_tf/scannet/preprocessing/scannet_util.py
  function get_raw2scannet_label_map (line 5) | def get_raw2scannet_label_map():

FILE: pointnet2_tf/scannet/scannet_dataset.py
  class ScannetDataset (line 8) | class ScannetDataset():
    method __init__ (line 9) | def __init__(self, root, npoints=8192, split='train'):
    method __getitem__ (line 27) | def __getitem__(self, index):
    method __len__ (line 61) | def __len__(self):
  class ScannetDatasetWholeScene (line 64) | class ScannetDatasetWholeScene():
    method __init__ (line 65) | def __init__(self, root, npoints=8192, split='train'):
    method __getitem__ (line 83) | def __getitem__(self, index):
    method __len__ (line 119) | def __len__(self):
  class ScannetDatasetVirtualScan (line 122) | class ScannetDatasetVirtualScan():
    method __init__ (line 123) | def __init__(self, root, npoints=8192, split='train'):
    method __getitem__ (line 141) | def __getitem__(self, index):
    method __len__ (line 166) | def __len__(self):

FILE: pointnet2_tf/scannet/scene_util.py
  function cart2sph (line 11) | def cart2sph(xyz):
  function virtual_scan (line 20) | def virtual_scan(xyz, mode=-1):

FILE: pointnet2_tf/scannet/train.py
  function log_string (line 73) | def log_string(out_str):
  function get_learning_rate (line 78) | def get_learning_rate(batch):
  function get_bn_decay (line 88) | def get_bn_decay(batch):
  function train (line 98) | def train():
  function get_batch_wdp (line 181) | def get_batch_wdp(dataset, idxs, start_idx, end_idx):
  function get_batch (line 199) | def get_batch(dataset, idxs, start_idx, end_idx):
  function train_one_epoch (line 211) | def train_one_epoch(sess, ops, train_writer):
  function eval_one_epoch (line 252) | def eval_one_epoch(sess, ops, test_writer):
  function eval_whole_scene_one_epoch (line 326) | def eval_whole_scene_one_epoch(sess, ops, test_writer):

FILE: pointnet2_tf/tf_ops/3d_interpolation/interpolate.cpp
  function randomf (line 9) | float randomf(){
  function get_time (line 12) | static double get_time(){
  function threenn_cpu (line 21) | void threenn_cpu(int b, int n, int m, const float *xyz1, const float *xy...
  function get_weights_cpu (line 69) | void get_weights_cpu(int b, int n, const float *dist, float *weight) {
  function interpolate_cpu (line 84) | void interpolate_cpu(int b, int m, int c, int n, const float *points, co...
  function interpolate_grad_cpu (line 108) | void interpolate_grad_cpu(int b, int n, int c, int m, const float *grad_...
  function main (line 132) | int main()

FILE: pointnet2_tf/tf_ops/3d_interpolation/tf_interpolate.cpp
  function randomf (line 48) | float randomf(){
  function get_time (line 51) | static double get_time(){
  function threenn_cpu (line 60) | void threenn_cpu(int b, int n, int m, const float *xyz1, const float *xy...
  function threeinterpolate_cpu (line 107) | void threeinterpolate_cpu(int b, int m, int c, int n, const float *point...
  function threeinterpolate_grad_cpu (line 131) | void threeinterpolate_grad_cpu(int b, int n, int c, int m, const float *...
  class ThreeNNOp (line 157) | class ThreeNNOp : public OpKernel {
    method ThreeNNOp (line 159) | explicit ThreeNNOp(OpKernelConstruction* context) : OpKernel(context) {}
    method Compute (line 161) | void Compute(OpKernelContext* context) override {
  class ThreeInterpolateOp (line 191) | class ThreeInterpolateOp: public OpKernel{
    method ThreeInterpolateOp (line 193) | explicit ThreeInterpolateOp(OpKernelConstruction * context):OpKernel(c...
    method Compute (line 195) | void Compute(OpKernelContext * context) override {
  class ThreeInterpolateGradOp (line 225) | class ThreeInterpolateGradOp: public OpKernel{
    method ThreeInterpolateGradOp (line 227) | explicit ThreeInterpolateGradOp(OpKernelConstruction * context):OpKern...
    method Compute (line 229) | void Compute(OpKernelContext * context) override {

FILE: pointnet2_tf/tf_ops/3d_interpolation/tf_interpolate.py
  function three_nn (line 8) | def three_nn(xyz1, xyz2):
  function three_interpolate (line 19) | def three_interpolate(points, idx, weight):
  function _three_interpolate_grad (line 30) | def _three_interpolate_grad(op, grad_out):

FILE: pointnet2_tf/tf_ops/3d_interpolation/tf_interpolate_op_test.py
  class GroupPointTest (line 5) | class GroupPointTest(tf.test.TestCase):
    method test (line 6) | def test(self):
    method test_grad (line 9) | def test_grad(self):

FILE: pointnet2_tf/tf_ops/3d_interpolation/visu_interpolation.py
  function fun (line 16) | def fun(xyz1,xyz2,pts2):

FILE: pointnet2_tf/tf_ops/grouping/test/query_ball_point.cpp
  function randomf (line 9) | float randomf(){
  function get_time (line 12) | static double get_time(){
  function query_ball_point_cpu (line 19) | void query_ball_point_cpu(int b, int n, int m, float radius, int nsample...
  function group_point_cpu (line 52) | void group_point_cpu(int b, int n, int c, int m, int nsample, const floa...
  function group_point_grad_cpu (line 70) | void group_point_grad_cpu(int b, int n, int c, int m, int nsample, const...
  function main (line 86) | int main()

FILE: pointnet2_tf/tf_ops/grouping/test/selection_sort.cpp
  function randomf (line 9) | float randomf(){
  function get_time (line 12) | static double get_time(){
  function selection_sort_cpu (line 20) | void selection_sort_cpu(int b, int n, int m, int k, const float *dist, i...
  function main (line 65) | int main()

FILE: pointnet2_tf/tf_ops/grouping/tf_grouping.cpp
  class QueryBallPointGpuOp (line 67) | class QueryBallPointGpuOp : public OpKernel {
    method QueryBallPointGpuOp (line 69) | explicit QueryBallPointGpuOp(OpKernelConstruction* context) : OpKernel...
    method Compute (line 77) | void Compute(OpKernelContext* context) override {
  class SelectionSortGpuOp (line 109) | class SelectionSortGpuOp : public OpKernel {
    method SelectionSortGpuOp (line 111) | explicit SelectionSortGpuOp(OpKernelConstruction* context) : OpKernel(...
    method Compute (line 116) | void Compute(OpKernelContext* context) override {
  class GroupPointGpuOp (line 143) | class GroupPointGpuOp: public OpKernel{
    method GroupPointGpuOp (line 145) | explicit GroupPointGpuOp(OpKernelConstruction * context):OpKernel(cont...
    method Compute (line 147) | void Compute(OpKernelContext * context) override {
  class GroupPointGradGpuOp (line 174) | class GroupPointGradGpuOp: public OpKernel{
    method GroupPointGradGpuOp (line 176) | explicit GroupPointGradGpuOp(OpKernelConstruction * context):OpKernel(...
    method Compute (line 178) | void Compute(OpKernelContext * context) override {

FILE: pointnet2_tf/tf_ops/grouping/tf_grouping.py
  function query_ball_point (line 8) | def query_ball_point(radius, nsample, xyz1, xyz2):
  function select_top_k (line 22) | def select_top_k(k, dist):
  function group_point (line 33) | def group_point(points, idx):
  function _group_point_grad (line 43) | def _group_point_grad(op, grad_out):
  function knn_point (line 48) | def knn_point(k, xyz1, xyz2):

FILE: pointnet2_tf/tf_ops/grouping/tf_grouping_op_test.py
  class GroupPointTest (line 5) | class GroupPointTest(tf.test.TestCase):
    method test (line 6) | def test(self):
    method test_grad (line 9) | def test_grad(self):

FILE: pointnet2_tf/tf_ops/sampling/tf_sampling.cpp
  class ProbSampleGpuOp (line 66) | class ProbSampleGpuOp: public OpKernel{
    method ProbSampleGpuOp (line 68) | explicit ProbSampleGpuOp(OpKernelConstruction* context):OpKernel(conte...
    method Compute (line 69) | void Compute(OpKernelContext * context)override{
  class FarthestPointSampleGpuOp (line 95) | class FarthestPointSampleGpuOp: public OpKernel{
    method FarthestPointSampleGpuOp (line 97) | explicit FarthestPointSampleGpuOp(OpKernelConstruction* context):OpKer...
    method Compute (line 101) | void Compute(OpKernelContext * context)override{
  class GatherPointGpuOp (line 126) | class GatherPointGpuOp: public OpKernel{
    method GatherPointGpuOp (line 128) | explicit GatherPointGpuOp(OpKernelConstruction * context):OpKernel(con...
    method Compute (line 129) | void Compute(OpKernelContext * context)override{
  class GatherPointGradGpuOp (line 151) | class GatherPointGradGpuOp: public OpKernel{
    method GatherPointGradGpuOp (line 153) | explicit GatherPointGradGpuOp(OpKernelConstruction * context):OpKernel...
    method Compute (line 154) | void Compute(OpKernelContext * context)override{

FILE: pointnet2_tf/tf_ops/sampling/tf_sampling.py
  function prob_sample (line 13) | def prob_sample(inp,inpr):
  function gather_point (line 29) | def gather_point(inp,idx):
  function _gather_point_grad (line 44) | def _gather_point_grad(op,out_g):
  function farthest_point_sample (line 48) | def farthest_point_sample(npoint,inp):

FILE: pointnet2_tf/train.py
  function log_string (line 81) | def log_string(out_str):
  function get_learning_rate (line 86) | def get_learning_rate(batch):
  function get_bn_decay (line 96) | def get_bn_decay(batch):
  function train (line 106) | def train():
  function train_one_epoch (line 186) | def train_one_epoch(sess, ops, train_writer):
  function eval_one_epoch (line 229) | def eval_one_epoch(sess, ops, test_writer):

FILE: pointnet2_tf/train_multi_gpu.py
  function log_string (line 86) | def log_string(out_str):
  function average_gradients (line 91) | def average_gradients(tower_grads):
  function get_learning_rate (line 129) | def get_learning_rate(batch):
  function get_bn_decay (line 139) | def get_bn_decay(batch):
  function train (line 149) | def train():
  function train_one_epoch (line 260) | def train_one_epoch(sess, ops, train_writer):
  function eval_one_epoch (line 303) | def eval_one_epoch(sess, ops, test_writer):

FILE: pointnet2_tf/utils/pc_util.py
  function point_cloud_to_volume_batch (line 24) | def point_cloud_to_volume_batch(point_clouds, vsize=12, radius=1.0, flat...
  function point_cloud_to_volume (line 41) | def point_cloud_to_volume(points, vsize, radius=1.0):
  function volume_to_point_cloud (line 56) | def volume_to_point_cloud(vol):
  function point_cloud_to_volume_v2_batch (line 73) | def point_cloud_to_volume_v2_batch(point_clouds, vsize=12, radius=1.0, n...
  function point_cloud_to_volume_v2 (line 84) | def point_cloud_to_volume_v2(points, vsize, radius=1.0, num_sample=128):
  function point_cloud_to_image_batch (line 126) | def point_cloud_to_image_batch(point_clouds, imgsize, radius=1.0, num_sa...
  function point_cloud_to_image (line 138) | def point_cloud_to_image(points, imgsize, radius=1.0, num_sample=128):
  function read_ply (line 176) | def read_ply(filename):
  function write_ply (line 184) | def write_ply(points, filename, text=True):
  function draw_point_cloud (line 196) | def draw_point_cloud(input_points, canvasSize=500, space=200, diameter=25,
  function point_cloud_three_views (line 255) | def point_cloud_three_views(points):
  function point_cloud_three_views_demo (line 269) | def point_cloud_three_views_demo():
  function pyplot_draw_point_cloud (line 281) | def pyplot_draw_point_cloud(points, output_filename):
  function pyplot_draw_volume (line 292) | def pyplot_draw_volume(vol, output_filename):
  function write_ply_color (line 299) | def write_ply_color(points, labels, out_filename, num_classes=None):

FILE: pointnet2_tf/utils/pointnet_util.py
  function sample_and_group (line 22) | def sample_and_group(npoint, radius, nsample, xyz, points, knn=False, us...
  function sample_and_group_all (line 59) | def sample_and_group_all(xyz, points, use_xyz=True):
  function pointnet_sa_module (line 87) | def pointnet_sa_module(xyz, points, npoint, radius, nsample, mlp, mlp2, ...
  function pointnet_sa_module_msg (line 156) | def pointnet_sa_module_msg(xyz, points, npoint, radius_list, nsample_lis...
  function pointnet_fp_module (line 199) | def pointnet_fp_module(xyz1, xyz2, points1, points2, mlp, is_training, b...

FILE: pointnet2_tf/utils/provider.py
  function shuffle_data (line 8) | def shuffle_data(data, labels):
  function shuffle_points (line 20) | def shuffle_points(batch_data):
  function rotate_point_cloud (line 32) | def rotate_point_cloud(batch_data):
  function rotate_point_cloud_z (line 52) | def rotate_point_cloud_z(batch_data):
  function rotate_point_cloud_with_normal (line 72) | def rotate_point_cloud_with_normal(batch_xyz_normal):
  function rotate_perturbation_point_cloud_with_normal (line 92) | def rotate_perturbation_point_cloud_with_normal(batch_data, angle_sigma=...
  function rotate_point_cloud_by_angle (line 119) | def rotate_point_cloud_by_angle(batch_data, rotation_angle):
  function rotate_point_cloud_by_angle_with_normal (line 138) | def rotate_point_cloud_by_angle_with_normal(batch_data, rotation_angle):
  function rotate_perturbation_point_cloud (line 162) | def rotate_perturbation_point_cloud(batch_data, angle_sigma=0.06, angle_...
  function jitter_point_cloud (line 187) | def jitter_point_cloud(batch_data, sigma=0.01, clip=0.05):
  function shift_point_cloud (line 200) | def shift_point_cloud(batch_data, shift_range=0.1):
  function random_scale_point_cloud (line 214) | def random_scale_point_cloud(batch_data, scale_low=0.8, scale_high=1.25):
  function random_point_dropout (line 227) | def random_point_dropout(batch_pc, max_dropout_ratio=0.875):
  function getDataFiles (line 237) | def getDataFiles(list_filename):
  function load_h5 (line 240) | def load_h5(h5_filename):
  function loadDataFile (line 246) | def loadDataFile(filename):

FILE: pointnet2_tf/utils/render_balls_so.cpp
  type PointInfo (line 7) | struct PointInfo{
  function render_ball (line 14) | void render_ball(int h,int w,unsigned char * show,int n,int * xyzs,float...

FILE: pointnet2_tf/utils/show3d_balls.py
  function onmouse (line 12) | def onmouse(*args):
  function showpoints (line 25) | def showpoints(xyz,c_gt=None, c_pred = None ,waittime=0,showrot=False,ma...

FILE: pointnet2_tf/utils/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: pointnet_pyt/pointnet/dataset.py
  function get_segmentation_classes (line 12) | def get_segmentation_classes(root):
  function gen_modelnet_id (line 46) | def gen_modelnet_id(root):
  class ShapeNetDataset (line 56) | class ShapeNetDataset(data.Dataset):
    method __init__ (line 57) | def __init__(self,
    method __getitem__ (line 109) | def __getitem__(self, index):
    method __len__ (line 140) | def __len__(self):
  class ModelNetDataset (line 143) | class ModelNetDataset(data.Dataset):
    method __init__ (line 144) | def __init__(self,
    method __getitem__ (line 167) | def __getitem__(self, index):
    method __len__ (line 191) | def __len__(self):

FILE: pointnet_pyt/pointnet/model.py
  class STN3d (line 11) | class STN3d(nn.Module):
    method __init__ (line 12) | def __init__(self):
    method forward (line 29) | def forward(self, x):
  class STNkd (line 49) | class STNkd(nn.Module):
    method __init__ (line 50) | def __init__(self, k=64):
    method forward (line 68) | def forward(self, x):
  class PointNetfeat (line 87) | class PointNetfeat(nn.Module):
    method __init__ (line 88) | def __init__(self, global_feat = True, feature_transform = False):
    method forward (line 102) | def forward(self, x):
  class PointNetCls (line 129) | class PointNetCls(nn.Module):
    method __init__ (line 130) | def __init__(self, k=2, feature_transform=False):
    method forward (line 142) | def forward(self, x):
  class PointNetDenseCls (line 150) | class PointNetDenseCls(nn.Module):
    method __init__ (line 151) | def __init__(self, k = 2, feature_transform=False):
    method forward (line 164) | def forward(self, x):
  function feature_transform_regularizer (line 177) | def feature_transform_regularizer(trans):

FILE: pointnet_pyt/utils/render_balls_so.cpp
  type PointInfo (line 7) | struct PointInfo{
  function render_ball (line 14) | void render_ball(int h,int w,unsigned char * show,int n,int * xyzs,float...

FILE: pointnet_pyt/utils/show3d_balls.py
  function onmouse (line 10) | def onmouse(*args):
  function showpoints (line 24) | def showpoints(xyz,c_gt=None, c_pred = None, waittime=0,

FILE: rs_cnn/data/ModelNet40Loader.py
  function _get_data_files (line 9) | def _get_data_files(list_filename):
  function _load_data_file (line 13) | def _load_data_file(name):
  class ModelNet40Cls (line 19) | class ModelNet40Cls(data.Dataset):
    method __init__ (line 20) | def __init__(self, num_points, root, data_file, transforms=None, train...
    method __getitem__ (line 47) | def __getitem__(self, idx):
    method __len__ (line 60) | def __len__(self):

FILE: rs_cnn/data/ShapeNetPartLoader.py
  function pc_normalize (line 12) | def pc_normalize(pc):
  class ShapeNetPart (line 20) | class ShapeNetPart():
    method __init__ (line 21) | def __init__(self, root, num_points = 2048, split='train', normalize=T...
    method __getitem__ (line 87) | def __getitem__(self, index):
    method __len__ (line 102) | def __len__(self):
    method preload (line 105) | def preload(self):

FILE: rs_cnn/data/data_utils.py
  class PointcloudToTensor (line 4) | class PointcloudToTensor(object):
    method __call__ (line 5) | def __call__(self, points):
  function angle_axis (line 8) | def angle_axis(angle: float, axis: np.ndarray):
  class PointcloudRotatebyAngle (line 39) | class PointcloudRotatebyAngle(object):
    method __init__ (line 40) | def __init__(self, rotation_angle = 0.0):
    method __call__ (line 43) | def __call__(self, pc):
  class PointcloudJitter (line 67) | class PointcloudJitter(object):
    method __init__ (line 68) | def __init__(self, std=0.01, clip=0.05):
    method __call__ (line 71) | def __call__(self, pc):
  class PointcloudScaleAndTranslate (line 81) | class PointcloudScaleAndTranslate(object):
    method __init__ (line 82) | def __init__(self, scale_low=2. / 3., scale_high=3. / 2., translate_ra...
    method __call__ (line 87) | def __call__(self, pc):
  class PointcloudScale (line 97) | class PointcloudScale(object):
    method __init__ (line 98) | def __init__(self, scale_low=2. / 3., scale_high=3. / 2.):
    method __call__ (line 102) | def __call__(self, pc):
  class PointcloudTranslate (line 111) | class PointcloudTranslate(object):
    method __init__ (line 112) | def __init__(self, translate_range=0.2):
    method __call__ (line 115) | def __call__(self, pc):
  class PointcloudRandomInputDropout (line 124) | class PointcloudRandomInputDropout(object):
    method __init__ (line 125) | def __init__(self, max_dropout_ratio=0.875):
    method __call__ (line 129) | def __call__(self, pc):

FILE: rs_cnn/models/rscnn_msn_seg.py
  class RSCNN_MSN (line 12) | class RSCNN_MSN(nn.Module):
    method __init__ (line 28) | def __init__(self, num_classes, input_channels=0, relation_prior=1, us...
    method _break_up_pc (line 116) | def _break_up_pc(self, pc):
    method forward (line 125) | def forward(self, pointcloud: torch.cuda.FloatTensor, cls):

FILE: rs_cnn/models/rscnn_ssn_cls.py
  class RSCNN_SSN (line 13) | class RSCNN_SSN(nn.Module):
    method __init__ (line 29) | def __init__(self, num_classes, input_channels=0, relation_prior=1, us...
    method _break_up_pc (line 74) | def _break_up_pc(self, pc):
    method forward (line 82) | def forward(self, pointcloud: torch.cuda.FloatTensor):

FILE: rs_cnn/train_cls.py
  function main (line 34) | def main():
  function train (line 95) | def train(train_dataloader, test_dataloader, model, criterion, optimizer...
  function validate (line 135) | def validate(test_dataloader, model, criterion, args, iter):

FILE: rs_cnn/train_partseg.py
  function main (line 33) | def main():
  function train (line 95) | def train(train_dataloader, test_dataloader, model, criterion, optimizer...
  function validate (line 138) | def validate(test_dataloader, model, criterion, args, iter):

FILE: rs_cnn/utils/_ext/pointnet2/__init__.py
  function _import_symbols (line 6) | def _import_symbols(locals):

FILE: rs_cnn/utils/build_ffi.py
  function parse_args (line 10) | def parse_args():
  function build (line 26) | def build(args):
  function clean (line 45) | def clean(args):

FILE: rs_cnn/utils/cinclude/cuda_utils.h
  function opt_n_threads (line 8) | inline int opt_n_threads(int work_size) {
  function dim3 (line 14) | inline dim3 opt_block_config(int x, int y) {

FILE: rs_cnn/utils/csrc/ball_query.c
  function ball_query_wrapper (line 7) | int ball_query_wrapper(int b, int n, int m, float radius, int nsample,

FILE: rs_cnn/utils/csrc/group_points.c
  function group_points_wrapper (line 7) | int group_points_wrapper(int b, int c, int n, int npoints, int nsample,
  function group_points_grad_wrapper (line 23) | int group_points_grad_wrapper(int b, int c, int n, int npoints, int nsam...

FILE: rs_cnn/utils/csrc/interpolate.c
  function three_nn_wrapper (line 10) | void three_nn_wrapper(int b, int n, int m, THCudaTensor *unknown_tensor,
  function three_interpolate_wrapper (line 22) | void three_interpolate_wrapper(int b, int c, int m, int n,
  function three_interpolate_grad_wrapper (line 38) | void three_interpolate_grad_wrapper(int b, int c, int n, int m,

FILE: rs_cnn/utils/csrc/sampling.c
  function gather_points_wrapper (line 7) | int gather_points_wrapper(int b, int c, int n, int npoints,
  function gather_points_grad_wrapper (line 22) | int gather_points_grad_wrapper(int b, int c, int n, int npoints,
  function furthest_point_sampling_wrapper (line 38) | int furthest_point_sampling_wrapper(int b, int n, int m,

FILE: rs_cnn/utils/linalg_utils.py
  function pdist2 (line 7) | def pdist2(
  function pdist2_slow (line 61) | def pdist2_slow(X, Z=None):

FILE: rs_cnn/utils/pointnet2_modules.py
  class _PointnetSAModuleBase (line 12) | class _PointnetSAModuleBase(nn.Module):
    method __init__ (line 14) | def __init__(self):
    method forward (line 20) | def forward(self, xyz: torch.Tensor,
  class PointnetSAModuleMSG (line 59) | class PointnetSAModuleMSG(_PointnetSAModuleBase):
    method __init__ (line 76) | def __init__(
  class PointnetSAModule (line 155) | class PointnetSAModule(PointnetSAModuleMSG):
    method __init__ (line 172) | def __init__(
  class PointnetFPModule (line 190) | class PointnetFPModule(nn.Module):
    method __init__ (line 201) | def __init__(self, *, mlp: List[int], bn: bool = True):
    method forward (line 205) | def forward(

FILE: rs_cnn/utils/pointnet2_modules_updated.py
  class QueryAndGroup (line 13) | class QueryAndGroup(nn.Module):
    method __init__ (line 24) | def __init__(self, radius: float, nsample: int, use_xyz: bool = True):
    method forward (line 28) | def forward(
  class GroupAll (line 73) | class GroupAll(nn.Module):
    method __init__ (line 80) | def __init__(self, use_xyz: bool = True):
    method forward (line 84) | def forward(
  class _PointnetSAModuleBase (line 118) | class _PointnetSAModuleBase(nn.Module):
    method __init__ (line 120) | def __init__(self):
    method forward (line 126) | def forward(self, xyz: torch.Tensor,
  class PointnetSAModuleMSG (line 164) | class PointnetSAModuleMSG(_PointnetSAModuleBase):
    method __init__ (line 180) | def __init__(
  class PointnetSAModule (line 259) | class PointnetSAModule(PointnetSAModuleMSG):
    method __init__ (line 275) | def __init__(
  class PointnetFPModule (line 293) | class PointnetFPModule(nn.Module):
    method __init__ (line 303) | def __init__(self, *, mlp: List[int], bn: bool = True):
    method forward (line 307) | def forward(

FILE: rs_cnn/utils/pointnet2_utils.py
  class RandomDropout (line 14) | class RandomDropout(nn.Module):
    method __init__ (line 16) | def __init__(self, p=0.5, inplace=False):
    method forward (line 21) | def forward(self, X):
  class FurthestPointSampling (line 28) | class FurthestPointSampling(Function):
    method forward (line 31) | def forward(ctx, xyz: torch.Tensor, npoint: int) -> torch.Tensor:
    method backward (line 60) | def backward(xyz, a=None):
  class GatherOperation (line 67) | class GatherOperation(Function):
    method forward (line 70) | def forward(ctx, features: torch.Tensor, idx: torch.Tensor) -> torch.T...
    method backward (line 103) | def backward(ctx, grad_out):
  class ThreeNN (line 119) | class ThreeNN(Function):
    method forward (line 122) | def forward(ctx, unknown: torch.Tensor,
    method backward (line 153) | def backward(ctx, a=None, b=None):
  class ThreeInterpolate (line 160) | class ThreeInterpolate(Function):
    method forward (line 163) | def forward(
    method backward (line 200) | def backward(ctx, grad_out: torch.Tensor
  class GroupingOperation (line 233) | class GroupingOperation(Function):
    method forward (line 236) | def forward(ctx, features: torch.Tensor, idx: torch.Tensor) -> torch.T...
    method backward (line 267) | def backward(ctx,
  class BallQuery (line 298) | class BallQuery(Function):
    method forward (line 301) | def forward(
    method backward (line 337) | def backward(ctx, a=None):
  class QueryAndGroup (line 344) | class QueryAndGroup(nn.Module):
    method __init__ (line 356) | def __init__(self, radius: float, nsample: int, use_xyz: bool = True):
    method forward (line 360) | def forward(
  class GroupAll (line 405) | class GroupAll(nn.Module):
    method __init__ (line 413) | def __init__(self, use_xyz: bool = True):
    method forward (line 417) | def forward(

FILE: rs_cnn/utils/pytorch_utils/pytorch_utils.py
  class RSConv (line 15) | class RSConv(nn.Module):
    method __init__ (line 20) | def __init__(
    method forward (line 46) | def forward(self, input): # input: (B, 3 + 3 + C_in, npoint, centroid ...
  class RSConvLayer (line 75) | class RSConvLayer(nn.Sequential):
    method __init__ (line 77) | def __init__(
  class SharedRSConv (line 100) | class SharedRSConv(nn.Sequential):
    method __init__ (line 102) | def __init__(
  class GloAvgConv (line 132) | class GloAvgConv(nn.Module):
    method __init__ (line 137) | def __init__(
    method forward (line 156) | def forward(self, x):
  class SharedMLP (line 166) | class SharedMLP(nn.Sequential):
    method __init__ (line 168) | def __init__(
  class _BNBase (line 194) | class _BNBase(nn.Sequential):
    method __init__ (line 196) | def __init__(self, in_size, batch_norm=None, name=""):
  class BatchNorm1d (line 204) | class BatchNorm1d(_BNBase):
    method __init__ (line 206) | def __init__(self, in_size: int, *, name: str = ""):
  class BatchNorm2d (line 210) | class BatchNorm2d(_BNBase):
    method __init__ (line 212) | def __init__(self, in_size: int, name: str = ""):
  class BatchNorm3d (line 216) | class BatchNorm3d(_BNBase):
    method __init__ (line 218) | def __init__(self, in_size: int, name: str = ""):
  class _ConvBase (line 222) | class _ConvBase(nn.Sequential):
    method __init__ (line 224) | def __init__(
  class Conv1d (line 278) | class Conv1d(_ConvBase):
    method __init__ (line 280) | def __init__(
  class Conv2d (line 312) | class Conv2d(_ConvBase):
    method __init__ (line 314) | def __init__(
  class Conv3d (line 346) | class Conv3d(_ConvBase):
    method __init__ (line 348) | def __init__(
  class FC (line 380) | class FC(nn.Sequential):
    method __init__ (line 382) | def __init__(
  class _DropoutNoScaling (line 418) | class _DropoutNoScaling(InplaceFunction):
    method _make_noise (line 421) | def _make_noise(input):
    method symbolic (line 425) | def symbolic(g, input, p=0.5, train=False, inplace=False):
    method forward (line 437) | def forward(cls, ctx, input, p=0.5, train=False, inplace=False):
    method backward (line 465) | def backward(ctx, grad_output):
  class _FeatureDropoutNoScaling (line 475) | class _FeatureDropoutNoScaling(_DropoutNoScaling):
    method symbolic (line 478) | def symbolic(input, p=0.5, train=False, inplace=False):
    method _make_noise (line 482) | def _make_noise(input):
  function group_model_params (line 492) | def group_model_params(model: nn.Module):
  function checkpoint_state (line 511) | def checkpoint_state(model=None, optimizer=None, best_prec=None, epoch=N...
  function save_checkpoint (line 529) | def save_checkpoint(
  function load_checkpoint (line 538) | def load_checkpoint(model=None, optimizer=None, filename='checkpoint'):
  function variable_size_collate (line 556) | def variable_size_collate(pad_val=0, use_shared_memory=True):
  class TrainValSplitter (line 626) | class TrainValSplitter():
    method __init__ (line 639) | def __init__(
  class CrossValSplitter (line 654) | class CrossValSplitter():
    method __init__ (line 670) | def __init__(self, *, numel: int, k_folds: int, shuffled: bool = False):
    method __iter__ (line 685) | def __iter__(self):
    method __len__ (line 689) | def __len__(self):
    method __getitem__ (line 692) | def __getitem__(self, idx):
    method __next__ (line 699) | def __next__(self):
    method update_metrics (line 706) | def update_metrics(self, to_post: dict):
    method print_metrics (line 713) | def print_metrics(self):
  function set_bn_momentum_default (line 722) | def set_bn_momentum_default(bn_momentum):
  class BNMomentumScheduler (line 731) | class BNMomentumScheduler(object):
    method __init__ (line 733) | def __init__(
    method step (line 751) | def step(self, epoch=None):
    method get_momentum (line 758) | def get_momentum(self, epoch=None):

FILE: rs_cnn/voting_evaluate_cls.py
  function main (line 38) | def main():

FILE: rs_cnn/voting_evaluate_partseg.py
  function main (line 37) | def main():

FILE: third_party/bn_helper.py
  function configure_model (line 4) | def configure_model(model, eps, momentum, reset_stats, no_stats):

FILE: third_party/tent_helper.py
  function collect_params (line 6) | def collect_params(model):
  function softmax_entropy (line 23) | def softmax_entropy(x: torch.Tensor) -> torch.Tensor:
  function configure_model (line 27) | def configure_model(model,eps, momentum):
  function forward_and_adapt (line 47) | def forward_and_adapt(x, model, optimizer):

FILE: visualize/examples.py
  function build_examples (line 14) | def build_examples(example_ids, severity):
  function load_examples (line 30) | def load_examples():
  function rotation_matrix (line 36) | def rotation_matrix(pitch, yaw, roll):
  function draw_one_example (line 49) | def draw_one_example(example, rotate=[0, 0], scale=1, window_width=1080,...
  function draw_one_example_colorful (line 88) | def draw_one_example_colorful(example, save="test.png"):
  function draw_examples (line 106) | def draw_examples(tag, examples, colorful=False):

FILE: visualize/main_results.py
  function format_data (line 17) | def format_data():
  function update_font (line 79) | def update_font(font):
  function load_data (line 88) | def load_data():
  function draw_train_mode_comparison (line 92) | def draw_train_mode_comparison(df=None, figure_path=None):
  function draw_model_comparison (line 129) | def draw_model_comparison(df=None, figure_path=None, mode="train", metri...
  function draw_corruption_comparison (line 178) | def draw_corruption_comparison(df=None, figure_path=None):
  function get_best_model (line 207) | def get_best_model(df=None):
  function get_best_train_mode (line 234) | def get_best_train_mode(df=None):
  function get_corruption_tables (line 264) | def get_corruption_tables(df=None, metric="acc"):
  function draw_teaser (line 294) | def draw_teaser(df=None):
  function get_table_1 (line 334) | def get_table_1(df=None):
  function get_table_2 (line 349) | def get_table_2():
  function get_table_3 (line 372) | def get_table_3():
  function get_table_4 (line 405) | def get_table_4():
  function draw_severity_comparison (line 437) | def draw_severity_comparison():
  function draw_test_adaptation (line 498) | def draw_test_adaptation():

FILE: visualize/pointflow_fig_colorful.py
  function standardize_bbox (line 3) | def standardize_bbox(pcl, points_per_object):
  function colormap (line 84) | def colormap(x,y,z):
  function colorful_pcd (line 92) | def colorful_pcd(pcd_data, output_file):