Configuration

Minimal TIF Workflow

vipr:
  inference:
    load_data:
      handler: gid_tif_reader
      parameters:
        data_path: '@vipr_gid/mlgiddetect/examples/data/w4_mapbbr32.tif'
        frame_index: 0

    load_model:
      handler: mlgiddetect
      parameters:
        model_name: frcnn
        device: cpu
        input_size: '800,800'

    prediction:
      handler: mlgiddetect_predictor
      parameters:
        score_threshold: 0.8

    postprocess:
      handler: mlgiddetect_postprocessor
      parameters:
        postprocess_boxes: true

Minimal HDF5 Workflow

vipr:
  inference:
    load_data:
      handler: gid_pygid_h5_reader
      parameters:
        data_path: /path/to/data.h5
        frame_index: 0
        # optional:
        # h5_img_path: entry/analysis/q_image
        # h5_qxy_path: entry/analysis/q_xy
        # h5_qz_path:  entry/analysis/q_z

Optional Preprocess Filter

vipr:
  inference:
    filters:
      INFERENCE_PREPROCESS_PRE_FILTER:
      - class: vipr_gid.mlgiddetect.preprocess.polar_transform_filter.PolarTransformFilter
        enabled: true
        method: preprocess_polar
        parameters: {}
        weight: 0

Key Parameters

load_data

• gid_tif_reader:

  • data_path (required)

  • frame_index (default 0)

• gid_pygid_h5_reader:

  • data_path (required)

  • frame_index (default 0)

  • h5_img_path, h5_qxy_path, h5_qz_path (optional)

load_model (mlgiddetect)

• model_path (optional; if missing, model is downloaded/cached)

• model_name (frcnn, rfdetrbase, rfdetrlarge)

• device (cpu or cuda)

• input_size (e.g. '800,800')

prediction (mlgiddetect_predictor)

• score_threshold (default 0.5)

postprocess (mlgiddetect_postprocessor)

• postprocess_boxes

• min_q_pix

• merge_min_score, merge_min_iou, merge_max_q, merge_quantile

• nms_level, final_score_level