config.yml

  hydra:
     run:
        dir: ./outputs/${comment}/${now:%Y-%m-%d}/
  comment: ${method}_margin_${margin.m_loss}_wi_${loss.w_lambda}_normIF_${normalize_img_features}
  backbone_model: resnet18
  backbone_outfeatures: 512
  img_out_features: 128
  data_type: OAI
  method: AdaTriplet-AM
  type_of_triplets: semihard
  test_CXR_side: all
  device: cuda
  image_crop_path:
  image_raw_path:
  projectpath:
  metadatapath:
  datapath:
  result_path:
  pretrained_matching_model_folder_path: None
  cropset: CropIMG_Path.csv
  clinicalset: Clinical_data_follow_ups.csv
  merged_crop_clinical_file: PreprocessedData.csv
  preprocess_data: PreprocessedData_Forensic.csv
  metadata_KLset: ID_SIDE_KL.csv
  test_site: C
  loss_identity_func: LB
  eval_dismat_algorithm: euclidean
  num_workers: 8
  batchsize: 128
  n_folds: 5
  i_fold: 0
  learning_rate: 1e-4
  weight_decay: 1e-4
  dropout_rate: 0.2
  csc_mode: False
  pretrained: True
  normalize_img_features: True
  normalize_identity_features: True
  save_distribution: False
  noepochs: 100
  seed: 28
  personal_id: ID
  load_model_metric: mAP
  query_time: 12
  distance_loss: cosine
  automargin_mode: normal
  loss:
      w_lambda: 1
      w_neg: 1
  k_param_automargin: 2
  k_n_param_autobeta: 2
  k_p_param_autobeta: 2
  margin:
    delta_p: 0
    delta_n: 0
    beta: 0
    m_loss: 0.25
  sampler:
    samplers_per_class: 4
  vars:
    best_ap: -1e8
    best_cmc: -1e8