SYMBOL INDEX (306 symbols across 32 files)

FILE: core/config/config_utils.py
  function generate_loss_weights_dict (line 3) | def generate_loss_weights_dict(cfg):

FILE: core/dataset/kitti_2012.py
  class KITTI_2012 (line 13) | class KITTI_2012(KITTI_Prepared):
    method __init__ (line 14) | def __init__(self, data_dir, img_hw=(256, 832), init=True):
    method get_data_list (line 21) | def get_data_list(self):
    method __len__ (line 31) | def __len__(self):
    method read_cam_intrinsic (line 34) | def read_cam_intrinsic(self, calib_file):
    method __getitem__ (line 38) | def __getitem__(self, idx):

FILE: core/dataset/kitti_2015.py
  class KITTI_2015 (line 5) | class KITTI_2015(KITTI_2012):
    method __init__ (line 6) | def __init__(self, data_dir, img_hw=(256, 832)):

FILE: core/dataset/kitti_odo.py
  function process_folder (line 7) | def process_folder(q, data_dir, output_dir, stride=1):
  class KITTI_Odo (line 33) | class KITTI_Odo(object):
    method __init__ (line 34) | def __init__(self, data_dir):
    method __len__ (line 38) | def __len__(self):
    method prepare_data_mp (line 41) | def prepare_data_mp(self, output_dir, stride=1):
    method __getitem__ (line 76) | def __getitem__(self, idx):

FILE: core/dataset/kitti_prepared.py
  class KITTI_Prepared (line 10) | class KITTI_Prepared(torch.utils.data.Dataset):
    method __init__ (line 11) | def __init__(self, data_dir, num_scales=3, img_hw=(256, 832), num_iter...
    method get_data_list (line 22) | def get_data_list(self, info_file):
    method count (line 35) | def count(self):
    method rand_num (line 38) | def rand_num(self, idx):
    method __len__ (line 44) | def __len__(self):
    method resize_img (line 50) | def resize_img(self, img, img_hw):
    method random_flip_img (line 63) | def random_flip_img(self, img):
    method preprocess_img (line 69) | def preprocess_img(self, img, img_hw=None, is_test=False):
    method read_cam_intrinsic (line 78) | def read_cam_intrinsic(self, fname):
    method rescale_intrinsics (line 87) | def rescale_intrinsics(self, K, img_hw_orig, img_hw_new):
    method get_intrinsics_per_scale (line 92) | def get_intrinsics_per_scale(self, K, scale):
    method get_multiscale_intrinsics (line 99) | def get_multiscale_intrinsics(self, K, num_scales):
    method __getitem__ (line 109) | def __getitem__(self, idx):

FILE: core/dataset/kitti_raw.py
  function process_folder (line 8) | def process_folder(q, static_frames, test_scenes, data_dir, output_dir, ...
  class KITTI_RAW (line 45) | class KITTI_RAW(object):
    method __init__ (line 46) | def __init__(self, data_dir, static_frames_txt, test_scenes_txt):
    method __len__ (line 51) | def __len__(self):
    method collect_static_frame (line 54) | def collect_static_frame(self):
    method collect_test_scenes (line 66) | def collect_test_scenes(self):
    method prepare_data_mp (line 74) | def prepare_data_mp(self, output_dir, stride=1):
    method prepare_data (line 122) | def prepare_data(self, output_dir):
    method __getitem__ (line 177) | def __getitem__(self, idx):

FILE: core/dataset/nyu_v2.py
  function collect_image_list (line 14) | def collect_image_list(path):
  function process_folder (line 24) | def process_folder(q, data_dir, output_dir, stride, train_scenes):
  class NYU_Prepare (line 68) | class NYU_Prepare(object):
    method __init__ (line 69) | def __init__(self, data_dir, test_dir):
    method __len__ (line 78) | def __len__(self):
    method get_all_scenes (line 81) | def get_all_scenes(self):
    method get_test_scenes (line 90) | def get_test_scenes(self):
    method get_train_scenes (line 104) | def get_train_scenes(self):
    method prepare_data_mp (line 118) | def prepare_data_mp(self, output_dir, stride=1):
    method __getitem__ (line 163) | def __getitem__(self, idx):
  class NYU_v2 (line 168) | class NYU_v2(torch.utils.data.Dataset):
    method __init__ (line 169) | def __init__(self, data_dir, num_scales=3, img_hw=(448, 576), num_iter...
    method get_data_list (line 182) | def get_data_list(self, info_file):
    method count (line 195) | def count(self):
    method rand_num (line 198) | def rand_num(self, idx):
    method __len__ (line 204) | def __len__(self):
    method resize_img (line 210) | def resize_img(self, img, img_hw):
    method random_flip_img (line 223) | def random_flip_img(self, img):
    method undistort_img (line 229) | def undistort_img(self, img, K):
    method preprocess_img (line 250) | def preprocess_img(self, img, K, img_hw=None, is_test=False):
    method read_cam_intrinsic (line 262) | def read_cam_intrinsic(self, fname):
    method rescale_intrinsics (line 271) | def rescale_intrinsics(self, K, img_hw_orig, img_hw_new):
    method get_intrinsics_per_scale (line 277) | def get_intrinsics_per_scale(self, K, scale):
    method get_multiscale_intrinsics (line 284) | def get_multiscale_intrinsics(self, K, num_scales):
    method __getitem__ (line 294) | def __getitem__(self, idx):

FILE: core/evaluation/eval_odom.py
  function scale_lse_solver (line 9) | def scale_lse_solver(X, Y):
  function umeyama_alignment (line 22) | def umeyama_alignment(x, y, with_scale=False):
  class KittiEvalOdom (line 72) | class KittiEvalOdom():
    method __init__ (line 77) | def __init__(self):
    method loadPoses (line 81) | def loadPoses(self, file_name):
    method trajectory_distances (line 106) | def trajectory_distances(self, poses):
    method rotation_error (line 123) | def rotation_error(self, pose_error):
    method translation_error (line 131) | def translation_error(self, pose_error):
    method last_frame_from_segment_length (line 137) | def last_frame_from_segment_length(self, dist, first_frame, len_):
    method calc_sequence_errors (line 143) | def calc_sequence_errors(self, poses_gt, poses_result):
    method save_sequence_errors (line 178) | def save_sequence_errors(self, err, file_name):
    method compute_overall_err (line 185) | def compute_overall_err(self, seq_err):
    method plotPath (line 198) | def plotPath(self, seq, poses_gt, poses_result):
    method compute_segment_error (line 230) | def compute_segment_error(self, seq_errs):
    method scale_optimization (line 259) | def scale_optimization(self, gt, pred):
    method eval (line 282) | def eval(self, gt_txt, result_txt, seq=None):

FILE: core/evaluation/evaluate_depth.py
  function process_depth (line 3) | def process_depth(gt_depth, pred_depth, min_depth, max_depth):
  function eval_depth (line 13) | def eval_depth(gt_depths,

FILE: core/evaluation/evaluate_flow.py
  function get_scaled_intrinsic_matrix (line 9) | def get_scaled_intrinsic_matrix(calib_file, zoom_x, zoom_y):
  function load_intrinsics_raw (line 19) | def load_intrinsics_raw(calib_file):
  function read_raw_calib_file (line 29) | def read_raw_calib_file(filepath):
  function scale_intrinsics (line 45) | def scale_intrinsics(mat, sx, sy):
  function read_flow_gt_worker (line 53) | def read_flow_gt_worker(dir_gt, i):
  function load_gt_flow_kitti (line 60) | def load_gt_flow_kitti(gt_dataset_dir, mode):
  function calculate_error_rate (line 85) | def calculate_error_rate(epe_map, gt_flow, mask):
  function eval_flow_avg (line 93) | def eval_flow_avg(gt_flows,

FILE: core/evaluation/evaluate_mask.py
  class EvalSegErr (line 12) | class EvalSegErr(Exception):
    method __init__ (line 13) | def __init__(self, value):
    method __str__ (line 16) | def __str__(self):
  function pixel_accuracy (line 20) | def pixel_accuracy(eval_segm, gt_segm):
  function mean_accuracy (line 48) | def mean_accuracy(eval_segm, gt_segm):
  function mean_IU (line 74) | def mean_IU(eval_segm, gt_segm):
  function frequency_weighted_IU (line 104) | def frequency_weighted_IU(eval_segm, gt_segm):
  function get_pixel_area (line 140) | def get_pixel_area(segm):
  function extract_both_masks (line 144) | def extract_both_masks(eval_segm, gt_segm, cl, n_cl):
  function extract_classes (line 151) | def extract_classes(segm):
  function union_classes (line 158) | def union_classes(eval_segm, gt_segm):
  function extract_masks (line 168) | def extract_masks(segm, cl, n_cl):
  function segm_size (line 178) | def segm_size(segm):
  function check_size (line 188) | def check_size(eval_segm, gt_segm):
  function read_mask_gt_worker (line 195) | def read_mask_gt_worker(gt_dataset_dir, idx):
  function load_gt_mask (line 199) | def load_gt_mask(gt_dataset_dir):
  function eval_mask (line 216) | def eval_mask(pred_masks, gt_masks, opt):

FILE: core/evaluation/evaluation_utils.py
  function compute_errors (line 11) | def compute_errors(gt, pred, nyu=False):

FILE: core/evaluation/flowlib.py
  function show_flow (line 29) | def show_flow(filename):
  function visualize_flow (line 41) | def visualize_flow(flow, mode='Y'):
  function read_flow (line 84) | def read_flow(filename):
  function read_flow_png (line 107) | def read_flow_png(flow_file):
  function write_flow_png (line 130) | def write_flow_png(flo, flow_file):
  function write_flow (line 147) | def write_flow(flow, filename):
  function segment_flow (line 166) | def segment_flow(flow):
  function flow_error (line 203) | def flow_error(tu, tv, u, v):
  function flow_to_image (line 258) | def flow_to_image(flow):
  function evaluate_flow_file (line 299) | def evaluate_flow_file(gt, pred):
  function evaluate_flow (line 315) | def evaluate_flow(gt_flow, pred_flow):
  function read_disp_png (line 332) | def read_disp_png(file_name):
  function disp_to_flowfile (line 350) | def disp_to_flowfile(disp, filename):
  function read_image (line 378) | def read_image(filename):
  function warp_image (line 389) | def warp_image(im, flow):
  function scale_image (line 428) | def scale_image(image, new_range):
  function compute_color (line 444) | def compute_color(u, v):
  function make_color_wheel (line 488) | def make_color_wheel():

FILE: core/networks/__init__.py
  function get_model (line 8) | def get_model(mode):

FILE: core/networks/model_depth_pose.py
  class Model_depth_pose (line 14) | class Model_depth_pose(nn.Module):
    method __init__ (line 15) | def __init__(self, cfg):
    method meshgrid (line 26) | def meshgrid(self, h, w):
    method robust_rand_sample (line 32) | def robust_rand_sample(self, match, mask, num):
    method top_ratio_sample (line 52) | def top_ratio_sample(self, match, mask, ratio):
    method rand_sample (line 59) | def rand_sample(self, match, num):
    method filt_negative_depth (line 65) | def filt_negative_depth(self, point2d_1_depth, point2d_2_depth, point2...
    method filt_invalid_coord (line 91) | def filt_invalid_coord(self, point2d_1_depth, point2d_2_depth, point2d...
    method ray_angle_filter (line 123) | def ray_angle_filter(self, match, P1, P2, return_angle=False):
    method midpoint_triangulate (line 168) | def midpoint_triangulate(self, match, K_inv, P1, P2):
    method rt_from_fundamental_mat_nyu (line 199) | def rt_from_fundamental_mat_nyu(self, fmat, K, depth_match):
    method verifyRT (line 228) | def verifyRT(self, match, K_inv, P1, P2):
    method rt_from_fundamental_mat (line 239) | def rt_from_fundamental_mat(self, fmat, K, depth_match):
    method reproject (line 277) | def reproject(self, P, point3d):
    method scale_adapt (line 284) | def scale_adapt(self, depth1, depth2, eps=1e-12):
    method affine_adapt (line 291) | def affine_adapt(self, depth1, depth2, use_translation=True, eps=1e-12):
    method register_depth (line 312) | def register_depth(self, depth_pred, coord_tri, depth_tri):
    method get_trian_loss (line 331) | def get_trian_loss(self, tri_depth, pred_tri_depth):
    method get_reproj_fdp_loss (line 336) | def get_reproj_fdp_loss(self, pred1, pred2, P2, K, K_inv, valid_mask, ...
    method disp2depth (line 359) | def disp2depth(self, disp, min_depth=0.1, max_depth=100.0):
    method get_smooth_loss (line 366) | def get_smooth_loss(self, img, disp):
    method infer_depth (line 382) | def infer_depth(self, img):
    method infer_vo (line 387) | def infer_vo(self, img1, img2, K, K_inv, match_num=6000):
    method check_rt (line 402) | def check_rt(self, img1, img2, K, K_inv):
    method inference (line 426) | def inference(self, img1, img2, K, K_inv):
    method forward (line 463) | def forward(self, inputs):

FILE: core/networks/model_flow.py
  function transformerFwd (line 12) | def transformerFwd(U,
  class Model_flow (line 151) | class Model_flow(nn.Module):
    method __init__ (line 152) | def __init__(self, cfg):
    method get_occlusion_mask_from_flow (line 169) | def get_occlusion_mask_from_flow(self, tensor_size, flow):
    method get_flow_norm (line 177) | def get_flow_norm(self, flow, p=2):
    method get_visible_masks (line 185) | def get_visible_masks(self, optical_flows, optical_flows_rev):
    method get_consistent_masks (line 195) | def get_consistent_masks(self, optical_flows, optical_flows_rev):
    method generate_img_pyramid (line 219) | def generate_img_pyramid(self, img, num_pyramid):
    method warp_flow_pyramid (line 227) | def warp_flow_pyramid(self, img_pyramid, flow_pyramid):
    method compute_loss_pixel (line 233) | def compute_loss_pixel(self, img_pyramid, img_warped_pyramid, occ_mask...
    method compute_loss_ssim (line 244) | def compute_loss_ssim(self, img_pyramid, img_warped_pyramid, occ_mask_...
    method gradients (line 257) | def gradients(self, img):
    method cal_grad2_error (line 262) | def cal_grad2_error(self, flow, img):
    method compute_loss_flow_smooth (line 273) | def compute_loss_flow_smooth(self, optical_flows, img_pyramid):
    method compute_loss_flow_consis (line 282) | def compute_loss_flow_consis(self, fwd_flow_diff_pyramid, occ_mask_list):
    method inference_flow (line 293) | def inference_flow(self, img1, img2):
    method inference_corres (line 299) | def inference_corres(self, img1, img2):
    method forward (line 319) | def forward(self, inputs, output_flow=False, use_flow_loss=True):

FILE: core/networks/model_flowposenet.py
  function mean_on_mask (line 16) | def mean_on_mask(diff, valid_mask):
  function edge_aware_smoothness_loss (line 22) | def edge_aware_smoothness_loss(pred_disp, img, max_scales):
  function compute_smooth_loss (line 64) | def compute_smooth_loss(tgt_depth, tgt_img, ref_depth, ref_img, max_scal...
  class Model_flowposenet (line 71) | class Model_flowposenet(nn.Module):
    method __init__ (line 72) | def __init__(self, cfg):
    method compute_pairwise_loss (line 79) | def compute_pairwise_loss(self, tgt_img, ref_img, tgt_depth, ref_depth...
    method disp2depth (line 106) | def disp2depth(self, disp, min_depth=0.01, max_depth=80.0):
    method infer_depth (line 113) | def infer_depth(self, img):
    method inference (line 119) | def inference(self, img1, img2, K, K_inv):
    method inference_flow (line 123) | def inference_flow(self, img1, img2):
    method infer_pose (line 127) | def infer_pose(self, img1, img2, K, K_inv):
    method forward (line 135) | def forward(self, inputs):

FILE: core/networks/model_triangulate_pose.py
  class Model_triangulate_pose (line 11) | class Model_triangulate_pose(nn.Module):
    method __init__ (line 12) | def __init__(self, cfg):
    method meshgrid (line 24) | def meshgrid(self, h, w):
    method compute_epipolar_loss (line 30) | def compute_epipolar_loss(self, fmat, match, mask):
    method get_rigid_mask (line 53) | def get_rigid_mask(self, dist_map):
    method inference (line 59) | def inference(self, img1, img2, K, K_inv):
    method forward (line 76) | def forward(self, inputs, output_F=False, visualizer=None):

FILE: core/networks/pytorch_ssim/ssim.py
  function SSIM (line 4) | def SSIM(x, y):

FILE: core/networks/structures/depth_model.py
  class ResNetMultiImageInput (line 17) | class ResNetMultiImageInput(models.ResNet):
    method __init__ (line 21) | def __init__(self, block, layers, num_classes=1000, num_input_images=1):
  function resnet_multiimage_input (line 41) | def resnet_multiimage_input(num_layers, pretrained=False, num_input_imag...
  class ResnetEncoder (line 60) | class ResnetEncoder(nn.Module):
    method __init__ (line 63) | def __init__(self, num_layers, pretrained, num_input_images=1):
    method forward (line 85) | def forward(self, input_image):
  class ConvBlock (line 97) | class ConvBlock(nn.Module):
    method __init__ (line 100) | def __init__(self, in_channels, out_channels):
    method forward (line 106) | def forward(self, x):
  class Conv3x3 (line 111) | class Conv3x3(nn.Module):
    method __init__ (line 114) | def __init__(self, in_channels, out_channels, use_refl=True):
    method forward (line 123) | def forward(self, x):
  function upsample (line 128) | def upsample(x):
  class DepthDecoder (line 135) | class DepthDecoder(nn.Module):
    method __init__ (line 136) | def __init__(self, num_ch_enc, scales=range(4), num_output_channels=1,...
    method init_decoder (line 149) | def init_decoder(self):
    method forward (line 173) | def forward(self, input_features):
  class Depth_Model (line 193) | class Depth_Model(nn.Module):
    method __init__ (line 194) | def __init__(self, depth_scale, num_layers=18):
    method forward (line 200) | def forward(self, img):

FILE: core/networks/structures/feature_pyramid.py
  class FeaturePyramid (line 7) | class FeaturePyramid(nn.Module):
    method __init__ (line 8) | def __init__(self):
    method forward (line 29) | def forward(self, img):

FILE: core/networks/structures/flowposenet.py
  function conv (line 7) | def conv(in_planes, out_planes, kernel_size=3):
  function upconv (line 13) | def upconv(in_planes, out_planes):
  class FlowPoseNet (line 19) | class FlowPoseNet(nn.Module):
    method __init__ (line 21) | def __init__(self):
    method init_weights (line 35) | def init_weights(self):
    method forward (line 42) | def forward(self, flow):

FILE: core/networks/structures/inverse_warp.py
  function set_id_grid (line 8) | def set_id_grid(depth):
  function check_sizes (line 20) | def check_sizes(input, input_name, expected):
  function pixel2cam (line 29) | def pixel2cam(depth, intrinsics_inv):
  function cam2pixel (line 47) | def cam2pixel(cam_coords, proj_c2p_rot, proj_c2p_tr, padding_mode):
  function euler2mat (line 77) | def euler2mat(angle):
  function quat2mat (line 115) | def quat2mat(quat):
  function pose_vec2mat (line 139) | def pose_vec2mat(vec, rotation_mode='euler'):
  function inverse_warp (line 157) | def inverse_warp(img, depth, pose, intrinsics, rotation_mode='euler', pa...
  function cam2pixel2 (line 194) | def cam2pixel2(cam_coords, proj_c2p_rot, proj_c2p_tr, padding_mode):
  function inverse_warp2 (line 230) | def inverse_warp2(img, depth, ref_depth, pose, intrinsics, padding_mode=...

FILE: core/networks/structures/net_utils.py
  function conv (line 7) | def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dila...
  function deconv (line 13) | def deconv(in_planes, out_planes, kernel_size=4, stride=2, padding=1):
  function warp_flow (line 16) | def warp_flow(x, flow, use_mask=False):

FILE: core/networks/structures/pwc_tf.py
  class PWC_tf (line 16) | class PWC_tf(nn.Module):
    method __init__ (line 17) | def __init__(self, md=4):
    method predict_flow (line 91) | def predict_flow(self, in_planes):
    method warp (line 94) | def warp(self, x, flow):
    method corr_naive (line 97) | def corr_naive(self, input1, input2, d=4):
    method forward (line 108) | def forward(self, feature_list_1, feature_list_2, img_hw):

FILE: core/networks/structures/ransac.py
  class reduced_ransac (line 8) | class reduced_ransac(nn.Module):
    method __init__ (line 9) | def __init__(self, check_num, thres, dataset):
    method robust_rand_sample (line 15) | def robust_rand_sample(self, match, mask, num, robust=True):
    method top_ratio_sample (line 36) | def top_ratio_sample(self, match, mask, ratio):
    method forward (line 44) | def forward(self, match, mask, visualizer=None):

FILE: core/visualize/profiler.py
  class Profiler (line 6) | class Profiler(object):
    method __init__ (line 7) | def __init__(self, silent=False):
    method reset (line 13) | def reset(self, silent=None):
    method report_process (line 18) | def report_process(self, process_name):
    method report_all (line 26) | def report_all(self, whole_process_name):

FILE: core/visualize/visualizer.py
  class Visualizer (line 15) | class Visualizer(object):
    method __init__ (line 16) | def __init__(self, loss_weights_dict, dump_dir=None):
    method add_log_pack (line 23) | def add_log_pack(self, log_pack):
    method dump_log (line 26) | def dump_log(self, fname=None):
    method print_loss (line 32) | def print_loss(self, loss_pack, iter_=None):
  class Visualizer_debug (line 50) | class Visualizer_debug():
    method __init__ (line 51) | def __init__(self, dump_dir=None, img1=None, img2=None):
    method draw_point_corres (line 56) | def draw_point_corres(self, batch_idx, match, name):
    method draw_invalid_corres_ray (line 62) | def draw_invalid_corres_ray(self, img1, img2, depth_match, point2d_1_c...
    method draw_epipolar_line (line 69) | def draw_epipolar_line(self, batch_idx, match, F, name):
    method show_corres (line 76) | def show_corres(self, img1, img2, match, name):
    method show_mask (line 93) | def show_mask(self, mask, name):
    method save_img (line 98) | def save_img(self, img, name):
    method save_depth_img (line 101) | def save_depth_img(self, depth, name):
    method save_disp_color_img (line 109) | def save_disp_color_img(self, disp, name):
    method drawlines (line 120) | def drawlines(self, img1, img2, lines, pts1, pts2):
    method show_epipolar_line (line 133) | def show_epipolar_line(self, img1, img2, match, F, name):
    method show_ray (line 153) | def show_ray(self, ax, K, RT, point2d, cmap='Greens'):
    method visualize_points (line 166) | def visualize_points(self, ax, points, cmap=None):
    method scatter_3d (line 171) | def scatter_3d(self, ax, point, scatter_color='r'):
    method visualize_two_rays (line 174) | def visualize_two_rays(self, ax, match, P1, P2):

FILE: data/eigen/export_gt_depth.py
  function load_velodyne_points (line 19) | def load_velodyne_points(filename):
  function read_calib_file (line 28) | def read_calib_file(path):
  function sub2ind (line 50) | def sub2ind(matrixSize, rowSub, colSub):
  function generate_depth_map (line 57) | def generate_depth_map(calib_dir, velo_filename, cam=2, vel_depth=False):
  function export_gt_depths_kitti (line 112) | def export_gt_depths_kitti():

FILE: infer_vo.py
  function save_traj (line 19) | def save_traj(path, poses):
  function projection (line 31) | def projection(xy, points, h_max, w_max):
  function unprojection (line 47) | def unprojection(xy, depth, K):
  function cv_triangulation (line 62) | def cv_triangulation(matches, pose):
  class infer_vo (line 76) | class infer_vo():
    method __init__ (line 77) | def __init__(self, seq_id, sequences_root_dir):
    method read_rescale_camera_intrinsics (line 99) | def read_rescale_camera_intrinsics(self, path):
    method load_images (line 114) | def load_images(self):
    method get_prediction (line 129) | def get_prediction(self, img1, img2, model, K, K_inv, match_num):
    method process_video (line 141) | def process_video(self, images, model):
    method normalize_coord (line 175) | def normalize_coord(self, xy, K):
    method align_to_depth (line 182) | def align_to_depth(self, xy1, xy2, pose, depth2):
    method solve_pose_pnp (line 213) | def solve_pose_pnp(self, xy1, xy2, depth1):
    method solve_pose_flow (line 255) | def solve_pose_flow(self, xy1, xy2):
  class pObject (line 311) | class pObject(object):
    method __init__ (line 312) | def __init__(self):

FILE: test.py
  function test_kitti_2012 (line 16) | def test_kitti_2012(cfg, model, gt_flows, noc_masks):
  function test_kitti_2015 (line 43) | def test_kitti_2015(cfg, model, gt_flows, noc_masks, gt_masks, depth_sav...
  function disp2depth (line 78) | def disp2depth(disp, min_depth=0.001, max_depth=80.0):
  function resize_depths (line 85) | def resize_depths(gt_depth_list, pred_disp_list):
  function test_eigen_depth (line 99) | def test_eigen_depth(cfg, model):
  function resize_disp (line 130) | def resize_disp(pred_disp_list, gt_depths):
  function load_nyu_test_data (line 143) | def load_nyu_test_data(data_dir):
  function test_nyu (line 153) | def test_nyu(cfg, model, test_images, test_gt_depths):
  function test_single_image (line 185) | def test_single_image(img_path, model, training_hw, save_dir='./'):
  class pObject (line 227) | class pObject(object):
    method __init__ (line 228) | def __init__(self):

FILE: train.py
  function save_model (line 19) | def save_model(iter_, model_dir, filename, model, optimizer):
  function load_model (line 22) | def load_model(model_dir, filename, model, optimizer):
  function train (line 29) | def train(cfg):
  class pObject (line 204) | class pObject(object):
    method __init__ (line 205) | def __init__(self):