SYMBOL INDEX (200 symbols across 26 files)

FILE: data/ORFD_dataset.py
  class orfdCalibInfo (line 11) | class orfdCalibInfo():
    method __init__ (line 16) | def __init__(self, filepath):
    method get_cam_param (line 23) | def get_cam_param(self):
    method _load_calib (line 30) | def _load_calib(self, filepath):
    method _read_calib_file (line 37) | def _read_calib_file(self, filepath):
  class orfddataset (line 53) | class orfddataset(BaseDataset):
    method modify_commandline_options (line 56) | def modify_commandline_options(parser, is_train):
    method initialize (line 59) | def initialize(self, opt):
    method __getitem__ (line 76) | def __getitem__(self, index):
    method __len__ (line 133) | def __len__(self):
    method name (line 136) | def name(self):

FILE: data/__init__.py
  function find_dataset_using_name (line 8) | def find_dataset_using_name(dataset_name):
  function get_option_setter (line 31) | def get_option_setter(dataset_name):
  function create_dataset (line 35) | def create_dataset(opt):
  function CreateDataLoader (line 42) | def CreateDataLoader(opt):
  class CustomDatasetDataLoader (line 50) | class CustomDatasetDataLoader(BaseDataLoader):
    method name (line 51) | def name(self):
    method initialize (line 54) | def initialize(self, opt):
    method load_data (line 74) | def load_data(self):
    method __len__ (line 77) | def __len__(self):
    method __iter__ (line 80) | def __iter__(self):

FILE: data/base_data_loader.py
  class BaseDataLoader (line 1) | class BaseDataLoader():
    method __init__ (line 2) | def __init__(self):
    method initialize (line 5) | def initialize(self, opt):
    method load_data (line 9) | def load_data():

FILE: data/base_dataset.py
  class BaseDataset (line 4) | class BaseDataset(data.Dataset):
    method __init__ (line 5) | def __init__(self):
    method name (line 8) | def name(self):
    method modify_commandline_options (line 12) | def modify_commandline_options(parser, is_train):
    method initialize (line 15) | def initialize(self, opt):
    method __len__ (line 18) | def __len__(self):

FILE: demo.py
  class dataset (line 15) | class dataset():
    method __init__ (line 16) | def __init__(self):
  function load_calib (line 20) | def load_calib(filepath):
  function read_calib_file (line 28) | def read_calib_file(filepath):

FILE: models/__init__.py
  function find_model_using_name (line 5) | def find_model_using_name(model_name):
  function get_option_setter (line 28) | def get_option_setter(model_name):
  function create_model (line 32) | def create_model(opt, dataset):

FILE: models/base_model.py
  class BaseModel (line 7) | class BaseModel():
    method modify_commandline_options (line 11) | def modify_commandline_options(parser, is_train):
    method name (line 14) | def name(self):
    method initialize (line 17) | def initialize(self, opt):
    method set_input (line 29) | def set_input(self, input):
    method forward (line 32) | def forward(self):
    method setup (line 36) | def setup(self, opt, parser=None):
    method eval (line 45) | def eval(self):
    method train (line 51) | def train(self):
    method test (line 59) | def test(self):
    method get_image_names (line 64) | def get_image_names(self):
    method get_image_oriSize (line 68) | def get_image_oriSize(self):
    method optimize_parameters (line 71) | def optimize_parameters(self):
    method update_learning_rate (line 75) | def update_learning_rate(self):
    method get_current_visuals (line 82) | def get_current_visuals(self):
    method get_current_losses (line 90) | def get_current_losses(self):
    method save_networks (line 99) | def save_networks(self, epoch):
    method __patch_instance_norm_state_dict (line 112) | def __patch_instance_norm_state_dict(self, state_dict, module, keys, i...
    method load_networks (line 126) | def load_networks(self, epoch):
    method print_networks (line 146) | def print_networks(self, verbose):
    method set_requires_grad (line 160) | def set_requires_grad(self, nets, requires_grad=False):

FILE: models/loss.py
  function get_scheduler (line 8) | def get_scheduler(optimizer, opt):
  class SegmantationLoss (line 18) | class SegmantationLoss(nn.Module):
    method __init__ (line 19) | def __init__(self, class_weights=None):
    method __call__ (line 22) | def __call__(self, output, target, pixel_average=True):

FILE: models/roadseg_model.py
  class RoadSegModel (line 9) | class RoadSegModel(BaseModel):
    method name (line 10) | def name(self):
    method modify_commandline_options (line 14) | def modify_commandline_options(parser, is_train=True):
    method initialize (line 20) | def initialize(self, opt, dataset):
    method set_input (line 46) | def set_input(self, input):
    method forward (line 53) | def forward(self):
    method get_loss (line 56) | def get_loss(self):
    method backward (line 59) | def backward(self):
    method optimize_parameters (line 62) | def optimize_parameters(self):

FILE: models/sne_model.py
  class SNE (line 6) | class SNE(nn.Module):
    method __init__ (line 10) | def __init__(self):
    method forward (line 13) | def forward(self, depth, camParam):

FILE: models/transformer_models/backbones/transformer.py
  class Mlp (line 22) | class Mlp(nn.Module):
    method __init__ (line 23) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method _init_weights (line 35) | def _init_weights(self, m):
    method forward (line 50) | def forward(self, x, H, W):
  class Attention (line 60) | class Attention(nn.Module):
    method __init__ (line 61) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method _init_weights (line 83) | def _init_weights(self, m):
    method forward (line 98) | def forward(self, x, H, W):
  class Block (line 122) | class Block(nn.Module):
    method __init__ (line 124) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
    method _init_weights (line 140) | def _init_weights(self, m):
    method forward (line 155) | def forward(self, x, H, W):
  class _PositionAttentionModule (line 161) | class _PositionAttentionModule(nn.Module):
    method __init__ (line 164) | def __init__(self, in_channels, **kwargs):
    method forward (line 172) | def forward(self, x):
  class OverlapPatchEmbed (line 183) | class OverlapPatchEmbed(nn.Module):
    method __init__ (line 187) | def __init__(self, img_size=224, patch_size=7, stride=4, in_chans=3, e...
    method _init_weights (line 202) | def _init_weights(self, m):
    method forward (line 217) | def forward(self, x):
  function init_weights (line 225) | def init_weights(net, init_type='normal', gain=0.02):
  function init_net (line 250) | def init_net(net, init_type='normal', init_gain=0.02, gpu_ids=[]):
  function define_RoadSeg (line 262) | def define_RoadSeg(num_labels, use_sne=True, init_type='xavier', init_ga...
  class crossAttentionModule (line 268) | class crossAttentionModule(nn.Module):
    method __init__ (line 271) | def __init__(self, in_features, hidden_features):
    method forward (line 276) | def forward(self, x, y):
  class MixVisionTransformer (line 282) | class MixVisionTransformer(nn.Module):
    method __init__ (line 283) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
    method _init_weights (line 346) | def _init_weights(self, m):
    method init_weights (line 361) | def init_weights(self, pretrained=None):
    method reset_drop_path (line 366) | def reset_drop_path(self, drop_path_rate):
    method freeze_patch_emb (line 384) | def freeze_patch_emb(self):
    method no_weight_decay (line 388) | def no_weight_decay(self):
    method get_classifier (line 391) | def get_classifier(self):
    method reset_classifier (line 394) | def reset_classifier(self, num_classes, global_pool=''):
    method forward_features (line 398) | def forward_features(self, x, y):
    method forward (line 453) | def forward(self, x, y):
  class DWConv (line 460) | class DWConv(nn.Module):
    method __init__ (line 461) | def __init__(self, dim=768):
    method forward (line 465) | def forward(self, x, H, W):
  class mit_b0 (line 474) | class mit_b0(MixVisionTransformer):
    method __init__ (line 475) | def __init__(self, **kwargs):
  class mit_b1 (line 481) | class mit_b1(MixVisionTransformer):
    method __init__ (line 482) | def __init__(self, **kwargs):
  class mit_b2 (line 488) | class mit_b2(MixVisionTransformer):
    method __init__ (line 489) | def __init__(self, **kwargs):
  class mit_b3 (line 496) | class mit_b3(MixVisionTransformer):
    method __init__ (line 497) | def __init__(self, **kwargs):
  class mit_b4 (line 503) | class mit_b4(MixVisionTransformer):
    method __init__ (line 504) | def __init__(self, **kwargs):
  class mit_b5 (line 510) | class mit_b5(MixVisionTransformer):
    method __init__ (line 511) | def __init__(self, **kwargs):

FILE: models/transformer_models/decode_heads/decode_head.py
  class BaseDecodeHead (line 14) | class BaseDecodeHead(nn.Module, metaclass=ABCMeta):
    method __init__ (line 16) | def __init__(self,
    method extra_repr (line 55) | def extra_repr(self):
    method _init_inputs (line 62) | def _init_inputs(self, in_channels, in_index, input_transform):
    method init_weights (line 100) | def init_weights(self):
    method _transform_inputs (line 104) | def _transform_inputs(self, inputs):
    method forward (line 133) | def forward(self, inputs):
    method forward_train (line 137) | def forward_train(self, inputs, img_metas, gt_semantic_seg, train_cfg):
    method forward_test (line 157) | def forward_test(self, inputs, img_metas, test_cfg):
    method cls_seg (line 174) | def cls_seg(self, feat):

FILE: models/transformer_models/decode_heads/head.py
  class MLP (line 19) | class MLP(nn.Module):
    method __init__ (line 23) | def __init__(self, input_dim=2048, embed_dim=768):
    method forward (line 27) | def forward(self, x):
  class Head (line 33) | class Head(BaseDecodeHead):
    method __init__ (line 34) | def __init__(self, feature_strides=[4, 8, 16, 32], **kwargs):
    method forward (line 60) | def forward(self, inputs):

FILE: models/transformer_models/utils/drop.py
  function drop_block_2d (line 17) | def drop_block_2d(
  function drop_block_fast_2d (line 64) | def drop_block_fast_2d(
  class DropBlock2d (line 102) | class DropBlock2d(nn.Module):
    method __init__ (line 105) | def __init__(self,
    method forward (line 122) | def forward(self, x):
  function drop_path (line 133) | def drop_path(x, drop_prob: float = 0., training: bool = False):
  class DropPath (line 151) | class DropPath(nn.Module):
    method __init__ (line 154) | def __init__(self, drop_prob=None):
    method forward (line 158) | def forward(self, x):

FILE: models/transformer_models/utils/inverted_residual.py
  class InvertedResidual (line 8) | class InvertedResidual(nn.Module):
    method __init__ (line 31) | def __init__(self,
    method forward (line 81) | def forward(self, x):
  class InvertedResidualV3 (line 97) | class InvertedResidualV3(nn.Module):
    method __init__ (line 124) | def __init__(self,
    method forward (line 183) | def forward(self, x):

FILE: models/transformer_models/utils/make_divisible.py
  function make_divisible (line 1) | def make_divisible(value, divisor, min_value=None, min_ratio=0.9):

FILE: models/transformer_models/utils/norm.py
  function _no_grad_trunc_normal_ (line 6) | def _no_grad_trunc_normal_(tensor, mean, std, a, b):
  function trunc_normal_ (line 42) | def trunc_normal_(tensor, mean=0., std=1., a=-2., b=2.):

FILE: models/transformer_models/utils/res_layer.py
  class ResLayer (line 5) | class ResLayer(nn.Sequential):
    method __init__ (line 26) | def __init__(self,

FILE: models/transformer_models/utils/se_layer.py
  class SELayer (line 8) | class SELayer(nn.Module):
    method __init__ (line 26) | def __init__(self,
    method forward (line 53) | def forward(self, x):

FILE: models/transformer_models/utils/self_attention_block.py
  class SelfAttentionBlock (line 7) | class SelfAttentionBlock(nn.Module):
    method __init__ (line 32) | def __init__(self, key_in_channels, query_in_channels, channels,
    method init_weights (line 93) | def init_weights(self):
    method build_project (line 99) | def build_project(self, in_channels, channels, num_convs, use_conv_mod...
    method forward (line 131) | def forward(self, query_feats, key_feats):

FILE: models/transformer_models/utils/up_conv_block.py
  class UpConvBlock (line 6) | class UpConvBlock(nn.Module):
    method __init__ (line 44) | def __init__(self,
    method forward (line 94) | def forward(self, skip, x):

FILE: options/base_options.py
  class BaseOptions (line 9) | class BaseOptions():
    method __init__ (line 10) | def __init__(self):
    method initialize (line 13) | def initialize(self, parser):
    method gather_options (line 35) | def gather_options(self):
    method print_options (line 60) | def print_options(self, opt):
    method parse (line 80) | def parse(self):

FILE: options/test_options.py
  class TestOptions (line 3) | class TestOptions(BaseOptions):
    method initialize (line 4) | def initialize(self, parser):

FILE: options/train_options.py
  class TrainOptions (line 3) | class TrainOptions(BaseOptions):
    method initialize (line 4) | def initialize(self, parser):

FILE: road_hesai40_process.py
  function show_velo (line 25) | def show_velo(pointcloud):
  function depth_colorize (line 51) | def depth_colorize(depth):
  function load_velodyne_points (line 56) | def load_velodyne_points(filename):
  function read_calib_file (line 66) | def read_calib_file(path):
  function sub2ind (line 88) | def sub2ind(matrixSize, rowSub, colSub):
  function generate_depth_map (line 95) | def generate_depth_map(velo_filename):
  function lin_interp (line 222) | def lin_interp(shape, xyd):
  function main (line 234) | def main(velo_filename):

FILE: util/util.py
  function save_images (line 9) | def save_images(save_dir, visuals, image_name, image_size, prob_map):
  function tensor2im (line 27) | def tensor2im(input_image, imtype=np.uint8):
  function tensor2labelim (line 39) | def tensor2labelim(label_tensor, impalette, imtype=np.uint8):
  function tensor2confidencemap (line 52) | def tensor2confidencemap(label_tensor, imtype=np.uint8):
  function print_current_losses (line 61) | def print_current_losses(epoch, i, losses, t, t_data):
  function mkdirs (line 68) | def mkdirs(paths):
  function mkdir (line 75) | def mkdir(path):
  function confusion_matrix (line 80) | def confusion_matrix(x, y, n, ignore_label=None, mask=None):
  function getScores (line 86) | def getScores(conf_matrix):