configs/active.yaml

project:
  name: MambaRefine-CD
  output_root: outputs
  seed: 42

data:
  dataset_name: DSIFN-CD
  root: datasets/DSIFN-CD
  image_size: 256
  train_dir: train
  val_dir: val
  test_dir: test
  a_folder: A
  b_folder: B
  mask_folder: Mask
  binary_threshold: 127
  check_split_overlap: true
  check_hash_overlap: true

model:
  name: MambaRefineCD
  encoder_family: mambavision
  encoder_variant: small
  encoder_pretrained: true
  freeze_encoder: false
  unfreeze_after_iters: null
  decoder_channels: 128

ablation:
  id: original
  temporal_input_mode: abs_signed   # abs_only | signed_only | abs_signed

train:
  device: cuda:0
  iterations: 50000
  batch_size: 8
  num_workers: 8
  lr: 0.0001
  weight_decay: 0.01
  optimizer: adamw
  scheduler: cosine
  warmup_iters: 1000
  amp: true
  grad_clip_norm: 1.0
  log_interval: 50
  val_interval: 5000
  save_best_only: true
  best_metric: F1
  higher_is_better: true

loss:
  bce_weight: 1.0
  dice_weight: 1.0
  aux_weight: 0.2
  boundary_weight: 0.2
  residual_reg_weight: 0.02

eval:
  threshold: 0.5
  sweep_thresholds_on_val: true
  use_val_threshold_for_test: true
  also_report_test_sweep: true
  threshold_min: 0.05
  threshold_max: 0.95
  threshold_step: 0.05
  save_predictions: true
  measure_fps: true

checkpoint:
  path: null
  auto_find_latest_best: true

resume:
  enabled: false
  path: null
  resume_optimizer: true
  resume_scheduler: true
  resume_iteration: true

logging:
  tensorboard: true
  print_params: true
  print_flops: true
  print_peak_memory: true
  print_fps: true