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train_brandenburg_gate.yaml
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train_brandenburg_gate.yaml
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NEUCONW:
N_SAMPLES: 8
N_IMPORTANCE: 16
UP_SAMPLE_STEP: 2
N_OUTSIDE: 4
USE_DISP: False
PERTURB: 1.0
NOISE_STD: 1.0
NEAR_FAR_OVERRIDE: True
DEPTH_LOSS: True
S_VAL_BASE: 3
BOUNDARY_SAMPLES: 10
SAMPLE_RANGE: 16
SDF_THRESHOLD: 0.0
TRAIN_VOXEL_SIZE: 0.08
UPDATE_FREQ: 5000
N_VOCAB: 5000
ENCODE_A: True
N_A: 48
N_STATIC_HEAD: 1
ANNEAL_END: 50000
RENDER_BG: True
MESH_MASK_LIST: ['sky']
RAY_MASK_LIST: ['person', 'car', 'bicycle', 'minibike']
ENCODE_A_BG: True
FLOOR_NORMAL: False
FLOOR_LABELS: [ 'road' ]
# network config
SDF_CONFIG:
d_in: 3
d_out: 513
d_hidden: 512
n_layers: 8
skip_in: (4,)
multires: 6
bias: 0.5
scale: 1
geometric_init: True
weight_norm: True
inside_outside: False
COLOR_CONFIG:
d_in: 9
d_feature: 512
mode: "idr"
d_out: 3
d_hidden: 256
n_layers: 4
head_channels: 128
static_head_layers: 2
weight_norm: True
multires_view: 4
S_CONFIG:
init_val: 0.3
# loss config
LOSS:
coef: 1.0
igr_weight: 0.0001
mask_weight: 0.1
depth_weight: 0.1
floor_weight: 0.01
DATASET:
ROOT_DIR: 'data/heritage-recon/brandenburg_gate'
DATASET_NAME: 'phototourism'
SPLIT: 'train'
PHOTOTOURISM:
IMG_DOWNSCALE: 1
USE_CACHE: True
CACHE_DIR: 'cache_sgs'
TRAINER:
CANONICAL_BS: 4096
CANONICAL_LR: 1e-4
OPTIMIZER: "adam"
WEIGHT_DECAY: 0
LR_SCHEDULER: 'none'
SAVE_DIR: './checkpoints'
VAL_FREQ: 10000.0
SAVE_FREQ: 10000