splatt3r / configs /main.yaml
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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