# ============================================================
# CNN-Based Thermal Pattern Analysis — Configuration
# ============================================================

# --- Data ---
data:
  raw_dir: "data/raw"
  processed_dir: "data/processed"
  sequences_dir: "data/sequences"
  image_size: [224, 224]
  sequence_length: 5 # shorter = more sequences for 90%+ accuracy
  train_split: 0.7
  val_split: 0.15
  test_split: 0.15
  num_workers: 0

# --- Preprocessing ---
preprocessing:
  bilateral_filter:
    d: 9
    sigma_color: 75
    sigma_space: 75
  clahe:
    clip_limit: 2.0
    tile_grid_size: [8, 8]
  normalize: true # Min-Max to [0, 1]

# --- Augmentation ---
augmentation:
  enabled: true
  rotation_limit: 15 # degrees
  horizontal_flip: true
  vertical_flip: false
  brightness_limit: 0.1
  contrast_limit: 0.1

# --- Model ---
model:
  feature_extractor:
    backbone: "resnet18"
    pretrained: true
    in_channels: 1 # grayscale
    embedding_dim: 256
  sequence_analyzer:
    hidden_size: 128
    num_layers: 2
    bidirectional: true
    dropout: 0.3
    attention: true
  anomaly_detector:
    similarity_metric: "cosine"
    threshold: 0.7

# --- Training ---
training:
  epochs: 100
  batch_size: 16
  learning_rate: 0.0003
  weight_decay: 0.00001
  optimizer: "adamw"
  scheduler: "cosine_annealing"
  early_stopping:
    patience: 25
    min_delta: 0.0005
  loss:
    contrastive_weight: 0.0
    triplet_weight: 0.0
    triplet_margin: 1.0

# --- Evaluation ---
evaluation:
  metrics:
    - accuracy
    - precision
    - recall
    - f1_score
    - auc_roc
  grad_cam: true
  confusion_matrix: true

# --- Paths ---
paths:
  checkpoints: "checkpoints"
  logs: "logs"
  results: "results"
  visualizations: "results/visualizations"

# --- Device ---
device: "auto" # auto | cpu | cuda
seed: 42