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Configuration

AutoTomeQC relies on a YAML configuration file to define directories, post-processing rules, and paths to AI model weights. By default, it uses the configuration defined in src/autotomeqc/config/yolo-config.yaml.

Example Configuration

qc:
  output_dir: "example/output"
  save_segmented_images: true
  save_input_images: true
  yolo:
    weights_path: "weights/seg_fast_yolo26_640.pt"
    conf_thresh: 0.5
    img_size: 640
    img_dim:
    max_det: 10
  yolo_post_processing:
    out_dim:
    loop_bbox_margin: 30
    allow_no_loop: true
    overlap_threshold: 0.5

Key Parameters

  • output_dir: The directory where JSON QC reports and debug images are saved.
  • save_segmented_images: If true, the pipeline saves the standardized BBox crop of the detected section to disk.
  • allow_no_loop: If true, the pipeline will process sections normally even if the global context loop is missing.
  • overlap_threshold: The minimum intersection-over-area required to consider a section "inside" the loop.