dataset:
  name: mvtec
  format: mvtec
  path: ./datasets/MVTec
  category: wood
  task: segmentation
  train_batch_size: 4
  eval_batch_size: 4
  inference_batch_size: 4
  num_workers: 8
  image_size:
  - 224
  - 224
  center_crop: null
  normalization: imagenet
  transform_config:
    train: null
    eval: null
  test_split_mode: from_dir
  test_split_ratio: 0.2
  val_split_mode: same_as_test
  val_split_ratio: 0.5
model:
  name: cfa
  backbone: wide_resnet50_2
  gamma_c: 1
  gamma_d: 1
  num_nearest_neighbors: 3
  num_hard_negative_features: 3
  radius: 1.0e-05
  lr: 0.001
  weight_decay: 0.0005
  amsgrad: true
  early_stopping:
    patience: 5
    metric: pixel_AUROC
    mode: max
  normalization_method: min_max
  input_size:
  - 224
  - 224
metrics:
  image:
  - AUROC
  pixel:
  - AUROC
  threshold:
    adaptive: true
    image_default: null
    pixel_default: null
    method: adaptive
    manual_image: null
    manual_pixel: null
visualization:
  show_images: false
  save_images: true
  log_images: true
  image_save_path: null
  mode: full
project:
  seed: 0
  path: results/cfa/mvtec/wood/run
  unique_dir: false
logging:
  logger: []
  log_graph: false
optimization:
  export_mode: null
trainer:
  enable_checkpointing: true
  default_root_dir: results/cfa/mvtec/wood/run
  gradient_clip_val: 0
  gradient_clip_algorithm: norm
  num_nodes: 1
  devices: 1
  enable_progress_bar: true
  overfit_batches: 0.0
  track_grad_norm: -1
  check_val_every_n_epoch: 1
  fast_dev_run: false
  accumulate_grad_batches: 1
  max_epochs: 30
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: 1.0
  limit_val_batches: 1.0
  limit_test_batches: 1.0
  limit_predict_batches: 1.0
  val_check_interval: 1.0
  log_every_n_steps: 50
  accelerator: auto
  strategy: null
  sync_batchnorm: false
  precision: 32
  enable_model_summary: true
  num_sanity_val_steps: 0
  profiler: null
  benchmark: false
  deterministic: false
  reload_dataloaders_every_n_epochs: 0
  auto_lr_find: false
  replace_sampler_ddp: true
  detect_anomaly: false
  auto_scale_batch_size: false
  plugins: null
  move_metrics_to_cpu: false
  multiple_trainloader_mode: max_size_cycle