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main.yaml
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defaults:
- dataset: dl3dv
- optional dataset/view_sampler_dataset_specific_config: ${dataset/view_sampler}_${dataset}
- model/encoder: costvolume
- model/decoder: splatting_cuda
- model/refiner: svd
- loss: [mse]
wandb:
project: mvsplat360
entity: placeholder
name: placeholder
mode: disabled
id: null
mode: train
dataset:
overfit_to_scene: null
data_loader:
# Avoid having to spin up new processes to print out visualizations.
train:
num_workers: 10
persistent_workers: true
batch_size: 4
seed: 1234
drop_last: False
test:
num_workers: 4
persistent_workers: false
batch_size: 1
seed: 2345
val:
num_workers: 1
persistent_workers: true
batch_size: 1
seed: 3456
optimizer:
lr: 2.e-4
refiner_lr: 1.e-5
warm_up_steps: 2000
# cosine_lr: true
sched_method: one_cycle
checkpointing:
load: null
every_n_train_steps: 1000 # 5000
save_top_k: 3
pretrained_model: null
legacy_support: false
resume: true
train:
depth_mode: null
extended_visualization: false
print_log_every_n_steps: 1
eval_model_every_n_val: 2
eval_save_model: true
eval_data_length: 999999999
eval_deterministic: false
tune_mvsplat: true
val_log_video: true
eval_index_path: assets/evaluation_index_re10k.json
val_log_video_extra: false
val_log_images_to_video: false
val_log_projection: true
val_log_cameras: true
test:
output_path: outputs/test
compute_scores: false
eval_time_skip_steps: 0
save_image: false
save_video: false
save_context: false
save_combined: false
save_gt: false
refiner_overlap: 0
refiner_loop_times: 1
save_video_pts_times: 1.
render_stable_poses: false
stable_k_size: 15
save_nn_gt: false
hack_refine_video_path: null
hack_refine_video_input_ctx: true
seed: 111123
trainer:
max_steps: -1
val_check_interval: 0.5
gradient_clip_val: 0.5
num_sanity_val_steps: 2
accumulate_grad_batches: 1
precision: 32
check_val_every_n_epoch: 1
num_nodes: 1
output_dir: null
use_diff_refinement: false
use_legacy_renderer: false
hack_pure_svd_debug: false
perturb_novel_views: false