SNI-SLAM.yaml

scale: 1
verbose: False
device: "cuda:0"
keyframe_device: "cpu" # Change this to "cpu" to reduce GPU memory usage
feature_device: "cpu"

planes_res:
  coarse: 0.24
  fine: 0.06
  bound_dividable: 0.24
c_planes_res:
  coarse: 0.24
  fine: 0.03
s_planes_res:
  coarse: 0.24
  fine: 0.03

meshing:
  level_set: 0
  resolution: 0.01
  eval_rec: False
  mesh_bound_scale: 1.02
tracking:
  ignore_edge_W: 75
  ignore_edge_H: 75
  vis_freq: 10000
  vis_inside_freq: 400
  const_speed_assumption: True
  no_vis_on_first_frame: True
  lr_T: 0.001
  lr_R: 0.001
  pixels: 2000
  iters: 8
  w_sdf_fs: 10
  w_sdf_center: 200
  w_sdf_tail: 50
  w_depth: 1
  w_color: 5
  w_semantic: 0.01

mapping:
  every_frame: 4
  joint_opt: True
  joint_opt_cam_lr: 0.001
  no_vis_on_first_frame: True
  no_mesh_on_first_frame: True
  no_log_on_first_frame: True
  vis_freq: 360
  vis_inside_freq: 400
  mesh_freq: 4000
  ckpt_freq: 500
  keyframe_every: 4
  mapping_window_size: 5
  keyframe_selection_method: 'overlap'
  lr_first_factor: 5
  lr_factor: 1
  pixels: 4000
  iters_first: 1000
  iters: 15
  w_sdf_fs: 5
  w_sdf_center: 200
  w_sdf_tail: 10
  w_depth: 0.1
  w_color: 5
  w_feature: 5
  w_semantic: 0.1
  lr:
    decoders_lr: 0.001
    planes_lr: 0.005
    c_planes_lr: 0.005
cam:
  H: 680
  W: 1200
  fx: 600.0
  fy: 600.0
  cx: 599.5
  cy: 339.5
  png_depth_scale: 1000.0 #for depth image in png format
  crop_edge: 0
rendering:
  n_stratified: 32
  n_importance: 8
  perturb: True
  learnable_beta: True
model:
  c_dim: 16
  truncation: 0.06
  hidden_dim: 32
  fused_hidden_dim: 16
  sem_hidden_dim: 256
  encoder:
    multires: 6
  cnn:
    n_classes: 52
    pretrained_model_path: '/data0/nerf/sni-slam/seg/dinov2_replica.pth'
  path: '/data0/nerf/sni-slam/seg/'

func:
  use_gt_semantic: False
  use_gt_pose: False
  enable_wandb: False