data:
  image_resize_dims:
    height: 256
    width: 256
  data_dir: ${LP_ROOT_PATH:}/data/mirror-mouse-fused
  video_dir: ${data.data_dir}/videos
  csv_file: CollectedData.csv
  num_keypoints: 51
  keypoint_names:
    - chin_tip_main
    - chin3_4_main
    - chin_half_main
    - chin1_4_main
    - chin_base_main
    - head_main
    - mid_main
    - tail_neck_main
    - caudal_v_main
    - caudal_d_main
    - pectoral_L_base_main
    - pectoral_L_main
    - pectoral_R_base_main
    - pectoral_R_main
    - dorsal_main
    - anal_main
    - fork_main
    - chin_tip_top
    - chin3_4_top
    - chin_half_top
    - chin1_4_top
    - chin_base_top
    - head_top
    - mid_top
    - tail_neck_top
    - caudal_v_top
    - caudal_d_top
    - pectoral_L_base_top
    - pectoral_L_top
    - pectoral_R_base_top
    - pectoral_R_top
    - dorsal_top
    - anal_top
    - fork_top
    - chin_tip_right
    - chin3_4_right
    - chin_half_right
    - chin1_4_right
    - chin_base_right
    - head_right
    - mid_right
    - tail_neck_right
    - caudal_v_right
    - caudal_d_right
    - pectoral_L_base_right
    - pectoral_L_right
    - pectoral_R_base_right
    - pectoral_R_right
    - dorsal_right
    - anal_right
    - fork_right
  mirrored_column_matches:
    - [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
    - [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33]
    - [34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]
  # all labels in multiple views w/ <25 nans
  columns_for_singleview_pca:
    [4, 5, 6, 7, 8, 9, 14, 15, 16, 22, 23, 24, 38, 39, 40, 41, 42, 43, 48, 50]

training:
  imgaug: dlc
  train_batch_size: 8
  val_batch_size: 32
  test_batch_size: 32
  train_prob: 0.95
  val_prob: 0.05
  train_frames: 1
  num_gpus: 1
  unfreezing_epoch: 20
  min_epochs: 300
  max_epochs: 300
  log_every_n_steps: 10
  check_val_every_n_epoch: 5
  rng_seed_data_pt: 0
  rng_seed_model_pt: 0
  optimizer: Adam
  optimizer_params:
    learning_rate: 1e-3
  lr_scheduler: multisteplr
  lr_scheduler_params:
    multisteplr:
      milestones: [150, 200, 250]
      gamma: 0.5

model:
  losses_to_use: []
  backbone: resnet50_animal_ap10k
  model_type: heatmap
  heatmap_loss_type: mse
  model_name: test_model

dali:
  general:
    seed: 123456
  base:
    train:
      sequence_length: 32
    predict:
      sequence_length: 64
  context:
    train:
      batch_size: 16
    predict:
      sequence_length: 64

losses:
  pca_multiview:
    log_weight: 10.7
    components_to_keep: 3
    epsilon: null
  pca_singleview:
    log_weight: 10.7
    components_to_keep: 0.99
    epsilon: null
  temporal:
    log_weight: 10.7
    epsilon: 10.0
    prob_threshold: 0.05

eval:
  predict_vids_after_training: false
  save_vids_after_training: false
  test_videos_directory: ${data.video_dir}
  confidence_thresh_for_vid: 0.90

callbacks:
  anneal_weight:
    attr_name: total_unsupervised_importance
    init_val: 0.0
    increase_factor: 0.01
    final_val: 1.0
    freeze_until_epoch: 60