# Ours
# location: server
location: local
data:
  type: semantic_seg
  name: watch
  num_classes: 4
  window_size: 7
  image_size: 128
  time_steps: 1
  weights: [0.01, 3, 1, 2]
  channels: red|green|blue|nir|swir16|swir22
  # channels: B02|B03|B04|B05|B06|B07|B08|B11|B12
  local:
    model_save_dir: /home/native/projects/data/smart_watch/models/
    train_dir: /media/native/data/data/smart_watch_dvc/Drop1-Aligned-L1-2022-01/
    test_dir: /media/native/data/data/smart_watch_dvc/Drop1-Aligned-L1-2022-01/
    train_coco_json: /media/native/data/data/smart_watch_dvc/Drop2-Aligned-TA1-2022-01/data_nowv_train.kwcoco.json
    test_coco_json: /media/native/data/data/smart_watch_dvc/Drop2-Aligned-TA1-2022-01/data_nowv_vali.kwcoco.json
    val_dir:
  server:
    model_save_dir: /data4/peri/smart_watch/models/
    train_dir: /data4/peri/datasets/smart_watch/processed/drop0_aligned_v2.1/
    test_dir: /data4/peri/datasets/smart_watch/processed/drop0_aligned_v2.1/
    val_dir: /data4/peri/datasets/smart_watch/processed/drop0_aligned_v2.1/
    rain_coco_json: /data4/datasets/smart_watch_dvc/extern/onera_2018/onera_train.kwcoco.json
    test_coco_json: /data4/datasets/smart_watch_dvc/extern/onera_2018/onera_test.kwcoco.json

training:
  backbone: resnet34 #resnet18 #resnet101, resnet50
  model_name: deeplab #shallow_seg, deeplabWS, resnet_enc, deeplab
  model_feats_channels: [64, 128, 256, 512, 256] #[64, 128, 256, 512, 256], [32, 32, 64, 64, 128], [64, 64, 128, 256, 512], [32, 32, 64, 128, 256], [64, 128, 256, 512, 256, 256] # this needs to match the correct number of layers in the model
  gn_n_groups: 32
  num_channels: 13
  out_features_dim: 10
  weight_std: True
  beta: False
  # pretrained: /home/native/projects/data/smart_watch/models/experiments_onera/tasks_experiments_onera_trainWin_7_modelName_resnet_2021-10-18-13:27/experiments_epoch_0_loss_11.28138166103723_valmF1_0.6866047574166068_valChangeF1_0.49019877611815305_time_2021-10-18-14:15:27.pth
  pretrained: False
  distributed: False
  learning_rate: 0.005 # best: 0.00007
  # resume: /home/native/projects/data/smart_watch/models/experiments_iarpa/tasks_experiments_iarpa_2022-01-27-17:08/experiments_epoch_28_loss_55.225655170587395_valmF1_nan_valChangeF1_0.0031579150989931425_time_2022-01-28-08:57:52.pth
  resume: False
  train_val_test_split: [0.95, 0.02, 0.03]
  epochs: 200
  start_epoch: 0
  batch_size: 64
  drop_last_batch: True
  momentum: 0.9
  weight_decay: 0.0001
  num_workers: 0
  test_with_full_supervision: 1
  model_single_input: False
  model_diff_input: False
  n_samples: 5

high_confidence_threshold:
  train_cutoff: 0.4
  val_cutoff: 0.4
  train_low_cutoff: 0.0
  val_low_cutoff: 0.0

evaluation:
  use_crf: False
  crf_t: 1
  crf_scale_factor: 1
  inference_window: 7
  batch_size: 1

procedures:
  train:  True
  validate: True