# RipBench v1.2.2 - evaluation scripts (minimal upload)

`eval/` holds the released evaluators of the RipBench paper, unchanged: `evaluate_classification.py`, `evaluate_detection.py` (axis-aligned boxes, mask-derived boxes and instance masks), `evaluate_obb.py` and `evaluate_semantic.py`, with `results_io.py` and `video_metadata.py` as their helpers. Each script states its inputs (prediction dumps + the `labels/` views) and the frozen protocol (operating thresholds selected on the validation split, per-frame scoring) in its docstring; `pip install -r requirements_tooling.txt`.

The test split carries no annotations in this release, so the evaluators score the train and validation splits locally; test-split evaluation is done through the benchmark's submission procedure (see the dataset README). Table builders, per-video bootstrap tooling, the label and video-view builders and the result files of the paper are not part of this minimal upload.