defaults:
  - _self_

data:
  num_classes: 14
  image_size: [512, 512]
  mean: [0.4810, 0.4810, 0.4810]  #[0.4513, 0.4513, 0.4513]
  std: [0.2492, 0.2492, 0.2492] #[0.1879, 0.1879, 0.1879]
  background_cls_id: 0
  split_ratio: 0.8
  base_dir: 'E:\Seg\Test\medical_segmentation\Bitewing'
  mask_dir: "${data.base_dir}/newAnnotations/"
  original_dir: "${data.base_dir}/Images/"
  dataset_path: "${hydra:runtime.cwd}/Bitwening_dataset1"
  
  # Normalization settings
  normalization:
    always_apply: true
  
  # Image resize configuration
  resize:
    interpolation: "INTER_NEAREST"  # CV2 interpolation method
  
  # Complete augmentation configuration with all parameters
  augmentation:
    # HorizontalFlip
    use_horizontal_flip: true
    horizontal_flip_prob: 0.5
    
    # VerticalFlip
    use_vertical_flip: true
    vertical_flip_prob: 0.5
    
    # ShiftScaleRotate
    use_shift_scale_rotate: true
    shift_scale_rotate_prob: 0.5
    rotate_limit: 0.15
    scale_limit: 0.12
    shift_limit: 0.12
    border_mode: 4  # cv2.BORDER_REFLECT_101
    
    # RandomBrightnessContrast
    use_brightness_contrast: true
    brightness_contrast_prob: 0.5
    brightness_limit: 0.2
    contrast_limit: 0.2
    
    # CoarseDropout
    use_coarse_dropout: true
    coarse_dropout:
      max_holes: 8
      min_holes: 5
      max_height: 25
      max_width: 25
      fill_value: 0
      mask_fill_value: 0
      prob: 0.5

training:
  batch_size: 10
  num_epochs: 1
  init_lr: 3e-4
  optimizer_name: "AdamW"
  weight_decay: 0.1
  use_scheduler: true
  scheduler: "MultiStepLR"
  model_name: "nvidia/segformer-b4-finetuned-ade-512-512"
  num_workers: 0
  pin_memory: true
  drop_last: true
  shuffle_train: true
  shuffle_valid: false

inference:
  batch_size: 10
  num_batches: 3

wandb:
  project: "UM_medical_segmentation"
  log_model: true

trainer:
  accelerator: "gpu"
  devices: "1"
  strategy: "auto"
  precision: "16-mixed"
  enable_model_summary: false

id2color:
  0: [0, 0, 0]         # Black
  1: [0, 0, 255]       # Blue
  2: [0, 255, 0]       # Green
  3: [255, 0, 0]       # Red
  4: [255, 255, 0]     # Yellow
  5: [255, 165, 0]     # Orange
  6: [128, 0, 128]     # Purple
  7: [0, 255, 255]     # Cyan
  8: [255, 20, 147]    # Deep Pink
  9: [75, 0, 130]      # Indigo
  10: [139, 69, 19]    # Saddle Brown
  11: [255, 192, 203]  # Pink
  12: [47, 79, 79]     # Dark Slate Gray
  13: [173, 255, 47]   # Green Yellow
  14: [0, 128, 128]    # Teal



experiment:
  name: "EXPERIMENT_1 bitewing dataset"          # Descriptive name for the experiment
  description: "Testing on 14 classes dataset with no layers and just fine tuning the model "    # What this experiment is testing
  goal: "to check the performance of the model on 100 epochs"    # What you hope to achieve