SYMBOL INDEX (185 symbols across 17 files)

FILE: dataset.py
  function eyecandies_classes (line 10) | def eyecandies_classes():
  function mvtec3d_classes (line 24) | def mvtec3d_classes():
  class BaseAnomalyDetectionDataset (line 40) | class BaseAnomalyDetectionDataset(Dataset):
    method __init__ (line 42) | def __init__(self, split, class_name, img_size, dataset_path='datasets...
  class PreTrainTensorDataset (line 53) | class PreTrainTensorDataset(Dataset):
    method __init__ (line 54) | def __init__(self, root_path):
    method __len__ (line 60) | def __len__(self):
    method __getitem__ (line 63) | def __getitem__(self, idx):
  class TrainDataset (line 72) | class TrainDataset(BaseAnomalyDetectionDataset):
    method __init__ (line 73) | def __init__(self, class_name, img_size, dataset_path='datasets/eyecan...
    method load_dataset (line 77) | def load_dataset(self):
    method __len__ (line 89) | def __len__(self):
    method __getitem__ (line 92) | def __getitem__(self, idx):
  class TestDataset (line 109) | class TestDataset(BaseAnomalyDetectionDataset):
    method __init__ (line 110) | def __init__(self, class_name, img_size, dataset_path='datasets/eyecan...
    method load_dataset (line 117) | def load_dataset(self):
    method __len__ (line 150) | def __len__(self):
    method __getitem__ (line 153) | def __getitem__(self, idx):
  function get_data_loader (line 180) | def get_data_loader(split, class_name, img_size, args):

FILE: engine_fusion_pretrain.py
  function train_one_epoch (line 11) | def train_one_epoch(model: torch.nn.Module,

FILE: feature_extractors/features.py
  class Features (line 28) | class Features(torch.nn.Module):
    method __init__ (line 30) | def __init__(self, args, image_size=224, f_coreset=0.1, coreset_eps=0.9):
    method __call__ (line 97) | def __call__(self, rgb, xyz):
    method add_sample_to_mem_bank (line 116) | def add_sample_to_mem_bank(self, sample):
    method predict (line 119) | def predict(self, sample, mask, label):
    method add_sample_to_late_fusion_mem_bank (line 122) | def add_sample_to_late_fusion_mem_bank(self, sample):
    method interpolate_points (line 125) | def interpolate_points(self, rgb, xyz):
    method compute_s_s_map (line 130) | def compute_s_s_map(self, xyz_patch, rgb_patch, fusion_patch, feature_...
    method compute_single_s_s_map (line 133) | def compute_single_s_s_map(self, patch, dist, feature_map_dims, modal=...
    method run_coreset (line 136) | def run_coreset(self):
    method calculate_metrics (line 139) | def calculate_metrics(self):
    method save_prediction_maps (line 148) | def save_prediction_maps(self, output_path, rgb_path, save_num=5):
    method run_late_fusion (line 173) | def run_late_fusion(self):
    method get_coreset_idx_randomp (line 179) | def get_coreset_idx_randomp(self, z_lib, n=1000, eps=0.90, float16=Tru...

FILE: feature_extractors/multiple_features.py
  class RGBFeatures (line 8) | class RGBFeatures(Features):
    method add_sample_to_mem_bank (line 10) | def add_sample_to_mem_bank(self, sample):
    method predict (line 24) | def predict(self, sample, mask, label):
    method run_coreset (line 38) | def run_coreset(self):
    method compute_s_s_map (line 54) | def compute_s_s_map(self, patch, feature_map_dims, mask, label, center...
  class PointFeatures (line 96) | class PointFeatures(Features):
    method add_sample_to_mem_bank (line 98) | def add_sample_to_mem_bank(self, sample):
    method predict (line 118) | def predict(self, sample, mask, label):
    method run_coreset (line 137) | def run_coreset(self):
    method compute_s_s_map (line 156) | def compute_s_s_map(self, patch, feature_map_dims, mask, label, center...
  class FusionFeatures (line 198) | class FusionFeatures(Features):
    method add_sample_to_mem_bank (line 200) | def add_sample_to_mem_bank(self, sample, class_name=None):
    method predict (line 238) | def predict(self, sample, mask, label):
    method compute_s_s_map (line 272) | def compute_s_s_map(self, patch, feature_map_dims, mask, label, center...
    method run_coreset (line 310) | def run_coreset(self):
  class DoubleRGBPointFeatures (line 319) | class DoubleRGBPointFeatures(Features):
    method add_sample_to_mem_bank (line 321) | def add_sample_to_mem_bank(self, sample, class_name=None):
    method predict (line 351) | def predict(self, sample, mask, label):
    method add_sample_to_late_fusion_mem_bank (line 372) | def add_sample_to_late_fusion_mem_bank(self, sample):
    method compute_s_s_map (line 413) | def compute_s_s_map(self, xyz_patch, rgb_patch, feature_map_dims, mask...
    method compute_single_s_s_map (line 449) | def compute_single_s_s_map(self, patch, dist, feature_map_dims, modal=...
    method run_coreset (line 484) | def run_coreset(self):
  class DoubleRGBPointFeatures_add (line 507) | class DoubleRGBPointFeatures_add(Features):
    method add_sample_to_mem_bank (line 509) | def add_sample_to_mem_bank(self, sample, class_name=None):
    method predict (line 540) | def predict(self, sample, mask, label):
    method add_sample_to_late_fusion_mem_bank (line 561) | def add_sample_to_late_fusion_mem_bank(self, sample):
    method run_coreset (line 601) | def run_coreset(self):
    method compute_s_s_map (line 624) | def compute_s_s_map(self, xyz_patch, rgb_patch, feature_map_dims, mask...
    method compute_single_s_s_map (line 655) | def compute_single_s_s_map(self, patch, dist, feature_map_dims, modal=...
  class TripleFeatures (line 691) | class TripleFeatures(Features):
    method add_sample_to_mem_bank (line 693) | def add_sample_to_mem_bank(self, sample, class_name=None):
    method predict (line 739) | def predict(self, sample, mask, label):
    method add_sample_to_late_fusion_mem_bank (line 774) | def add_sample_to_late_fusion_mem_bank(self, sample):
    method run_coreset (line 836) | def run_coreset(self):
    method compute_s_s_map (line 871) | def compute_s_s_map(self, xyz_patch, rgb_patch, fusion_patch, feature_...
    method compute_single_s_s_map (line 915) | def compute_single_s_s_map(self, patch, dist, feature_map_dims, modal=...

FILE: fusion_pretrain.py
  function get_args_parser (line 32) | def get_args_parser():
  function main (line 94) | def main(args):

FILE: m3dm_runner.py
  class M3DM (line 9) | class M3DM():
    method __init__ (line 10) | def __init__(self, args):
    method fit (line 40) | def fit(self, class_name):
    method evaluate (line 74) | def evaluate(self, class_name):

FILE: main.py
  function run_3d_ads (line 7) | def run_3d_ads(args):

FILE: models/feature_fusion.py
  class Mlp (line 5) | class Mlp(nn.Module):
    method __init__ (line 6) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 15) | def forward(self, x):
  class FeatureFusionBlock (line 23) | class FeatureFusionBlock(nn.Module):
    method __init__ (line 24) | def __init__(self, xyz_dim, rgb_dim, mlp_ratio=4.):
    method feature_fusion (line 41) | def feature_fusion(self, xyz_feature, rgb_feature):
    method contrastive_loss (line 50) | def contrastive_loss(self, q, k):
    method reparameterize (line 61) | def reparameterize(self, mu, logvar):
    method forward (line 74) | def forward(self, xyz_feature, rgb_feature):

FILE: models/models.py
  class Model (line 8) | class Model(torch.nn.Module):
    method __init__ (line 10) | def __init__(self, device, rgb_backbone_name='vit_base_patch8_224_dino...
    method forward_rgb_features (line 36) | def forward_rgb_features(self, x):
    method forward (line 50) | def forward(self, rgb, xyz):
  function fps (line 60) | def fps(data, number):
  class Group (line 69) | class Group(nn.Module):
    method __init__ (line 70) | def __init__(self, num_group, group_size):
    method forward (line 76) | def forward(self, xyz):
  class Encoder (line 101) | class Encoder(nn.Module):
    method __init__ (line 102) | def __init__(self, encoder_channel):
    method forward (line 118) | def forward(self, point_groups):
  class Mlp (line 135) | class Mlp(nn.Module):
    method __init__ (line 136) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 145) | def forward(self, x):
  class Attention (line 154) | class Attention(nn.Module):
    method __init__ (line 155) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method forward (line 167) | def forward(self, x):
  class Block (line 182) | class Block(nn.Module):
    method __init__ (line 183) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
    method forward (line 195) | def forward(self, x):
  class TransformerEncoder (line 201) | class TransformerEncoder(nn.Module):
    method __init__ (line 205) | def __init__(self, embed_dim=768, depth=4, num_heads=12, mlp_ratio=4.,...
    method forward (line 217) | def forward(self, x, pos):
  class PointTransformer (line 227) | class PointTransformer(nn.Module):
    method __init__ (line 228) | def __init__(self, group_size=128, num_group=1024, encoder_dims=384):
    method load_model_from_ckpt (line 265) | def load_model_from_ckpt(self, bert_ckpt_path):
    method load_model_from_pb_ckpt (line 294) | def load_model_from_pb_ckpt(self, bert_ckpt_path):
    method forward (line 321) | def forward(self, pts):

FILE: models/pointnet2_utils.py
  function timeit (line 7) | def timeit(tag, t):
  function pc_normalize (line 11) | def pc_normalize(pc):
  function square_distance (line 19) | def square_distance(src, dst):
  function index_points (line 41) | def index_points(points, idx):
  function farthest_point_sample (line 60) | def farthest_point_sample(xyz, npoint):
  function query_ball_point (line 84) | def query_ball_point(radius, nsample, xyz, new_xyz):
  function sample_and_group (line 107) | def sample_and_group(npoint, radius, nsample, xyz, points, returnfps=Fal...
  function sample_and_group_all (line 138) | def sample_and_group_all(xyz, points):
  function interpolating_points (line 157) | def interpolating_points(xyz1, xyz2, points2):

FILE: utils/au_pro_util.py
  class GroundTruthComponent (line 15) | class GroundTruthComponent:
    method __init__ (line 21) | def __init__(self, anomaly_scores):
    method compute_overlap (line 39) | def compute_overlap(self, threshold):
  function trapezoid (line 61) | def trapezoid(x, y, x_max=None):
  function collect_anomaly_scores (line 113) | def collect_anomaly_scores(anomaly_maps, ground_truth_maps):
  function compute_pro (line 166) | def compute_pro(anomaly_maps, ground_truth_maps, num_thresholds):
  function calculate_au_pro (line 213) | def calculate_au_pro(gts, predictions, integration_limit=0.3, num_thresh...

FILE: utils/lr_sched.py
  function adjust_learning_rate (line 3) | def adjust_learning_rate(optimizer, epoch, args):

FILE: utils/misc.py
  class SmoothedValue (line 13) | class SmoothedValue(object):
    method __init__ (line 18) | def __init__(self, window_size=20, fmt=None):
    method update (line 26) | def update(self, value, n=1):
    method synchronize_between_processes (line 31) | def synchronize_between_processes(self):
    method median (line 45) | def median(self):
    method avg (line 50) | def avg(self):
    method global_avg (line 55) | def global_avg(self):
    method max (line 59) | def max(self):
    method value (line 63) | def value(self):
    method __str__ (line 66) | def __str__(self):
  class MetricLogger (line 75) | class MetricLogger(object):
    method __init__ (line 76) | def __init__(self, delimiter="\t"):
    method update (line 80) | def update(self, **kwargs):
    method __getattr__ (line 89) | def __getattr__(self, attr):
    method __str__ (line 97) | def __str__(self):
    method synchronize_between_processes (line 105) | def synchronize_between_processes(self):
    method add_meter (line 109) | def add_meter(self, name, meter):
    method log_every (line 112) | def log_every(self, iterable, print_freq, header=None):
  function setup_for_distributed (line 159) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 176) | def is_dist_avail_and_initialized():
  function get_world_size (line 184) | def get_world_size():
  function get_rank (line 190) | def get_rank():
  function is_main_process (line 196) | def is_main_process():
  function save_on_master (line 200) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 205) | def init_distributed_mode(args):
  class NativeScalerWithGradNormCount (line 240) | class NativeScalerWithGradNormCount:
    method __init__ (line 243) | def __init__(self):
    method __call__ (line 246) | def __call__(self, loss, optimizer, clip_grad=None, parameters=None, c...
    method state_dict (line 262) | def state_dict(self):
    method load_state_dict (line 265) | def load_state_dict(self, state_dict):
  function get_grad_norm_ (line 269) | def get_grad_norm_(parameters, norm_type: float = 2.0) -> torch.Tensor:
  function save_model (line 284) | def save_model(args, epoch, model, model_without_ddp, optimizer, loss_sc...
  function save_model_gan (line 303) | def save_model_gan(args, epoch, model, discriminator, model_without_ddp,...
  function load_model (line 326) | def load_model(args, model_without_ddp, optimizer, loss_scaler):
  function load_model_gan (line 342) | def load_model_gan(args, model_without_ddp, discriminator_without_ddp,
  function all_reduce_mean (line 364) | def all_reduce_mean(x):

FILE: utils/mvtec3d_util.py
  function organized_pc_to_unorganized_pc (line 5) | def organized_pc_to_unorganized_pc(organized_pc):
  function read_tiff_organized_pc (line 9) | def read_tiff_organized_pc(path):
  function resize_organized_pc (line 14) | def resize_organized_pc(organized_pc, target_height=224, target_width=22...
  function organized_pc_to_depth_map (line 24) | def organized_pc_to_depth_map(organized_pc):

FILE: utils/preprocess_eyecandies.py
  function load_and_convert_depth (line 14) | def load_and_convert_depth(depth_img, info_depth):
  function depth_to_pointcloud (line 24) | def depth_to_pointcloud(depth_img, info_depth, pose_txt, focal_length):
  function remove_point_cloud_background (line 58) | def remove_point_cloud_background(pc):

FILE: utils/preprocessing.py
  function get_edges_of_pc (line 12) | def get_edges_of_pc(organized_pc):
  function get_plane_eq (line 20) | def get_plane_eq(unorganized_pc,ransac_n_pts=50):
  function remove_plane (line 25) | def remove_plane(organized_pc_clean, organized_rgb ,distance_threshold=0...
  function connected_components_cleaning (line 49) | def connected_components_cleaning(organized_pc, organized_rgb, image_path):
  function roundup_next_100 (line 80) | def roundup_next_100(x):
  function pad_cropped_pc (line 83) | def pad_cropped_pc(cropped_pc, single_channel=False):
  function preprocess_pc (line 99) | def preprocess_pc(tiff_path):

FILE: utils/utils.py
  function set_seeds (line 7) | def set_seeds(seed: int = 0) -> None:
  class KNNGaussianBlur (line 12) | class KNNGaussianBlur(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, radius : int = 4):
    method __call__ (line 20) | def __call__(self, img):