training.config.yaml

callbacks:
  anneal_weight:
    attr_name: total_unsupervised_importance
    final_val: 1.0
    freeze_until_epoch: 0
    increase_factor: 0.01
    init_val: 0.0
dali:
  base:
    predict:
      sequence_length: 96
    train:
      sequence_length: 32
  context:
    predict:
      sequence_length: 96
    train:
      batch_size: 10
  general:
    seed: 123456
data:
  columns_for_singleview_pca:
  - 0
  - 1
  - 2
  - 3
  - 4
  - 5
  - 6
  - 7
  - 8
  - 9
  - 10
  - 11
  - 12
  - 13
  - 14
  - 15
  - 16
  - 17
  csv_file: /root/capsule/scratch/super_updated_disc_face_lp/CollectedData.csv
  data_dir: /root/capsule/scratch/super_updated_disc_face_lp
  detector:
    downsample_factor: 2
    image_resize_dims:
      height: null
      width: null
    keypoint_names: null
    keypoints_for_crop: null
    num_keypoints: null
  downsample_factor: 2
  dynamic_crop: false
  image_resize_dims:
    height: 384
    width: 384
  keypoint_names:
  - eye_top
  - eye_right
  - eye_bottom
  - eye_left
  - pupil_top
  - pupil_right
  - pupil_bottom
  - pupil_left
  - pupil_top_right
  - pupil_bottom_right
  - pupil_bottom_left
  - pupil_top_left
  - reflection
  - nostril
  - nose_tip
  - whisker_1
  - whisker_2
  - whisker_3
  mirrored_column_matches: null
  num_keypoints: 18
  num_max_instances: 1
  video_dir: /root/capsule/scratch/super_updated_disc_face_lp/videos/
eval:
  confidence_thresh_for_vid: 0.9
  fiftyone:
    address: 127.0.0.1
    dataset_name: test
    launch_app_from_script: false
    model_display_names:
    - test_model
    port: 5151
    remote: true
  hydra_paths:
  - ' '
  predict_vids_after_training: true
  save_vids_after_training: false
  test_videos_directory: /root/capsule/scratch/super_updated_disc_face_lp/videos/
hydra:
  run:
    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
  sweep:
    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
    subdir: ${hydra.job.num}
losses:
  pca_multiview:
    components_to_keep: 3
    epsilon: null
    log_weight: 5.0
  pca_singleview:
    components_to_keep: 0.99
    epsilon: null
    log_weight: 5.0
  temporal:
    epsilon: 20.0
    log_weight: 5.0
    prob_threshold: 0.05
model:
  backbone: resnet50_animal_ap10k
  checkpoint: null
  heatmap_loss_type: mse
  losses_to_use:
  - pca_singleview
  model_name: test
  model_type: heatmap
training:
  check_val_every_n_epoch: 5
  ckpt_every_n_epochs: null
  early_stop_patience: 3
  early_stopping: false
  gpu_id: 0
  imgaug: dlc
  log_every_n_steps: 10
  lr_scheduler: multisteplr
  lr_scheduler_params:
    multisteplr:
      gamma: 0.5
      milestones:
      - 150
      - 200
      - 250
  max_epochs: 300
  min_epochs: 300
  num_gpus: 1
  num_workers: 4
  rng_seed_data_pt: 0
  rng_seed_model_pt: 0
  test_batch_size: 32
  train_batch_size: 16
  train_frames: 1
  train_prob: 0.95
  unfreezing_epoch: 20
  uniform_heatmaps_for_nan_keypoints: true
  val_batch_size: 32
  val_prob: 0.05