kangaroo-detection/dvc.yaml

stages:
  gen-dag:
    cmd:
      - dvc dag --full --md >> ${gen-dag.output}
      - dvc dag -o --md >> ${gen-dag.output}
    always_changed: true
    outs:
      - ${gen-dag.output}

  environment-check:
    cmd: >
      python -m src.pipeline.environment_check
    always_changed: true
    deps:
      - ${src.pipeline.environment-check}
    outs:
      - ${environment-check.output}
    params:
      - environment-check

  train-model:
    vars:
      - model.hyper.yaml:initial-weights
      - data.yaml
    cmd: >
      python -u -m src.pipeline.train_model
      | tee ${train-pipeline.output.log}
    deps:
      # previous stage
      - ${environment-check.output}
      # src code
      - ${src.pipeline.train-model}
      - ${src.current-model}
      # data/weight
      - ${sample-data.path}
      - ${initial-weights}
    outs:
      - ${train-pipeline.output.log}
      - ${train-pipeline.summary}:
          persist: true
      - ${train-pipeline.output.model}:
          persist: true
    params:
      - src.current-model
      - train-pipeline
      - model.hyper.yaml: #! DANGER: DO NOT USE implicit name in params
        - train
    metrics:
      - ${train-pipeline.output.metric.folder}${train-pipeline.output.metric.general}
  evaluate:
    cmd: >
      python -u -m src.pipeline.evaluate
      | tee ${evaluate.output.log}
    deps:
      # previous stage
      - ${environment-check.output}
      - ${evaluate.model-weight} #weight
      # src code
      - ${src.pipeline.evaluate}
      - ${src.current-model}
      # data
      - ${evaluate.data.path}
    params:
      - evaluate
      - src.current-model
      - model.hyper.yaml:
        - inference
    metrics:
      - ${evaluate.output.metric}

# plots
plots:
  - loss_bounding_box:
      title: MaskRCNN on BBox
      template: linear
      y: 
        out/train.metrics/epoch_mrcnn_bbox_loss.json: value
        out/train.metrics/epoch_val_mrcnn_bbox_loss.json: value
      x_label: 'Epoch'
      y_label: 'Loss'