batdetect2/example_data/config.yaml

targets:
  detection_target:
    name: bat
    match_if:
      name: all_of
      conditions:
        - name: has_tag
          tag: { key: event, value: Echolocation }
        - name: not
          condition:
            name: has_tag
            tag: { key: class, value: Unknown }
    assign_tags:
      - key: class
        value: Bat

  classification_targets:
    - name: myomys
      tags:
        - key: class
          value: Myotis mystacinus
    - name: pippip
      tags:
        - key: class
          value: Pipistrellus pipistrellus
    - name: eptser
      tags:
        - key: class
          value: Eptesicus serotinus
    - name: rhifer
      tags:
        - key: class
          value: Rhinolophus ferrumequinum

  roi:
    name: anchor_bbox
    anchor: top-left

preprocess:
  audio:
    samplerate: 256000
    resample:
      enabled: True
      method: "poly"

  spectrogram:
    stft:
      window_duration: 0.002
      window_overlap: 0.75
      window_fn: hann
    frequencies:
      max_freq: 120000
      min_freq: 10000
    size:
      height: 128
      resize_factor: 0.5
    transforms:
      - name: pcen
        time_constant: 0.1
        gain: 0.98
        bias: 2
        power: 0.5
      - name: spectral_mean_substraction

postprocess:
  nms_kernel_size: 9
  detection_threshold: 0.01
  top_k_per_sec: 200

model:
  input_height: 128
  in_channels: 1
  out_channels: 32
  encoder:
    layers:
      - name: FreqCoordConvDown
        out_channels: 32
      - name: FreqCoordConvDown
        out_channels: 64
      - name: LayerGroup
        layers:
          - name: FreqCoordConvDown
            out_channels: 128
          - name: ConvBlock
            out_channels: 256
  bottleneck:
    channels: 256
    layers:
      - name: SelfAttention
        attention_channels: 256
  decoder:
    layers:
      - name: FreqCoordConvUp
        out_channels: 64
      - name: FreqCoordConvUp
        out_channels: 32
      - name: LayerGroup
        layers:
          - name: FreqCoordConvUp
            out_channels: 32
          - name: ConvBlock
            out_channels: 32

train:
  learning_rate: 0.001
  t_max: 100

  labels:
    sigma: 3

  trainer:
    max_epochs: 5

  dataloaders:
    train:
      batch_size: 8
      num_workers: 2
      shuffle: True

    val:
      batch_size: 1
      num_workers: 2

  loss:
    detection:
      weight: 1.0
      focal:
        beta: 4
        alpha: 2
    classification:
      weight: 2.0
      focal:
        beta: 4
        alpha: 2
    size:
      weight: 0.1

  logger:
    name: mlflow
    tracking_uri: http://10.20.20.211:9000
    log_model: true

  augmentations:
    enabled: true
    audio:
      - name: mix_audio
        probability: 0.2
        min_weight: 0.3
        max_weight: 0.7
      - name: add_echo
        probability: 0.2
        max_delay: 0.005
        min_weight: 0.0
        max_weight: 1.0
    spectrogram:
      - name: scale_volume
        probability: 0.2
        min_scaling: 0.0
        max_scaling: 2.0
      - name: warp
        probability: 0.2
        delta: 0.04
      - name: mask_time
        probability: 0.2
        max_perc: 0.05
        max_masks: 3
      - name: mask_freq
        probability: 0.2
        max_perc: 0.10
        max_masks: 3