Spaces:
Runtime error
Runtime error
File size: 1,847 Bytes
660acc7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
base_config:
- config/logging.yaml
- config/wandb.yaml
- config/dataset/dataset_train.yaml
- config/dataset/dataset_val.yaml
- config/dataset/dataset_vis.yaml
- config/model_sdv2.yaml
pipeline:
name: MarigoldPipeline
kwargs:
scale_invariant: true
shift_invariant: true
depth_normalization:
type: scale_shift_depth
clip: true
norm_min: -1.0
norm_max: 1.0
min_max_quantile: 0.02
augmentation:
lr_flip_p: 0.5
dataloader:
num_workers: 2
effective_batch_size: 32
max_train_batch_size: 2
seed: 2024 # to ensure continuity when resuming from checkpoint
# Training settings
trainer:
name: MarigoldTrainer
training_noise_scheduler:
pretrained_path: stable-diffusion-2
init_seed: 2024 # use null to train w/o seeding
save_period: 50
backup_period: 2000
validation_period: 2000
visualization_period: 2000
multi_res_noise:
strength: 0.9
annealed: true
downscale_strategy: original
gt_depth_type: depth_raw_norm
gt_mask_type: valid_mask_raw
max_epoch: 10000 # a large enough number
max_iter: 30000 # usually converges at around 20k
optimizer:
name: Adam
loss:
name: mse_loss
kwargs:
reduction: mean
lr: 3.0e-05
lr_scheduler:
name: IterExponential
kwargs:
total_iter: 25000
final_ratio: 0.01
warmup_steps: 100
# Validation (and visualization) settings
validation:
denoising_steps: 50
ensemble_size: 1 # simplified setting for on-training validation
processing_res: 0
match_input_res: false
resample_method: bilinear
main_val_metric: abs_relative_difference
main_val_metric_goal: minimize
init_seed: 2024
eval:
alignment: least_square
align_max_res: null
eval_metrics:
- abs_relative_difference
- squared_relative_difference
- rmse_linear
- rmse_log
- log10
- delta1_acc
- delta2_acc
- delta3_acc
- i_rmse
- silog_rmse
|