# Safe School AI - Configuration File
# Recommended settings for Colab T4/RTX3060 GPU

# Dataset paths
data:
  rwf_2000_root: "data/RWF-2000"  # Path to RWF-2000 dataset
  school_dataset_root: "data/school_dataset"  # Optional: out-of-domain test set only (no finetune)
  train_split: 0.8
  val_split: 0.1
  test_split: 0.1

# Model configuration
model:
  backbone: "x3d_m"  # Options: x3d_s, x3d_m, x3d_l, r2plus1d_18
  pretrained: true
  num_classes: 2  # Binary: Violence / Non-Violence
  dropout: 0.5
  
  # Layer freezing strategy
  freeze_backbone: true  # Freeze backbone initially
  freeze_epochs: 5  # Number of epochs to train only the head
  unfreeze_layers: ["blocks.4", "blocks.5"]  # Layers to unfreeze after freeze_epochs

# Video preprocessing
video:
  num_frames: 32  # Number of frames to sample per clip (matches trained models)
  frame_size: [224, 224]  # Height x Width
  fps: 30  # Target FPS for sampling
  clip_duration: 4.0  # Duration in seconds
  mean: [0.45, 0.45, 0.45]  # ImageNet stats
  std: [0.225, 0.225, 0.225]

# Data augmentation (for training)
augmentation:
  enabled: true
  random_crop: true
  random_horizontal_flip: true
  horizontal_flip_prob: 0.5
  color_jitter: true
  brightness: 0.2
  contrast: 0.2
  saturation: 0.2
  hue: 0.1
  temporal_jitter: true  # Random temporal sampling

# Training hyperparameters - RWF-2000
train_rwf:
  batch_size: 8  # Adjust based on GPU memory (T4: 8, RTX3060: 12-16)
  num_epochs: 30
  learning_rate: 0.001
  weight_decay: 0.0001
  optimizer: "adam"  # Options: adam, sgd, adamw
  scheduler: "step"  # Options: step, cosine, plateau
  step_size: 10
  gamma: 0.1
  early_stopping_patience: 10
  
  # Mixed precision training (2x faster on modern GPUs)
  mixed_precision: true  # Enable FP16 training
  
  # Loss function
  loss: "cross_entropy"  # Options: cross_entropy, focal_loss
  label_smoothing: 0.1
  
  # Checkpointing
  save_frequency: 5  # Save checkpoint every N epochs
  save_best_only: true

# Inference settings
inference:
  device: "auto"  # Options: auto, cuda, cpu
  batch_size: 1
  confidence_threshold: 0.5
  use_smoothing: true  # Temporal smoothing for video predictions
  smoothing_window: 5  # Number of frames to smooth over
  use_tta: false  # Test-time augmentation

# Paths
paths:
  checkpoints_dir: "checkpoints"
  logs_dir: "logs"
  results_dir: "results"
  export_dir: "exports"

# Logging
logging:
  level: "INFO"  # DEBUG, INFO, WARNING, ERROR
  save_logs: true
  log_file: "training.log"
  tensorboard: false  # Enable TensorBoard logging
  
# Hardware
device:
  cuda_visible_devices: "0"  # GPU device ID
  num_workers: 4  # DataLoader workers (adjust based on CPU cores)
  pin_memory: true
  mixed_precision: true  # Use AMP for faster training

# Random seed for reproducibility
seed: 42