configs/main.yaml

name: '%Y-%m-%d-%H-%M-%S'

save_dir: './results/${name}/'

# Environment
seed: 0
devices: 'auto'

# Loggers
use_profiler: False
loggers:
 use_csv_logger: True
 use_wandb: True

# Model
use_pretrained: True
pretrained_mast3r_path: './checkpoints/MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric.pth'

# Data
data:
 root: '/home/bras5602/data/scannetpp'
 batch_size: 12
 num_workers: 16
 resolution: [512, 512]
 epochs_per_train_epoch: 100 # How many times to sample from each scene each training epoch (helps avoid unnecessary Pytorch Lightning overhead)

# Optimization
opt:
 epochs: 20
 lr: 0.00001
 weight_decay: 0.05
 gradient_clip_val: 0.5

loss:
 mse_loss_weight: 1.0
 lpips_loss_weight: 0.25
 mast3r_loss_weight: Null
 apply_mask: True
 average_over_mask: True

use_offsets: True
sh_degree: 1