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| # Processing Snapshot | |
| This directory contains a source snapshot of the scripts used for the released | |
| BubbleID-Flow data products. It accompanies, but does not replace, the | |
| canonical software repository: | |
| https://github.com/UARK-NED3/BubbleID-Flow | |
| The repository baseline at the time of this release snapshot was commit | |
| `051c07dd8016cc27861509ac203b59b45b29e170`. The files under `scripts/` are the | |
| archived processing snapshot for this dataset release. Run them from this | |
| directory with `python -m scripts.<module_name>` so intra-script imports resolve | |
| from the snapshot. | |
| ## Environment | |
| `environment.yml` records the environment versions observed during release | |
| preparation: Python 3.10.19, PyTorch 2.9.1 CPU, Detectron2 0.6, OpenCV 4.11.0, | |
| NumPy 1.23.0, and pandas 2.3.3. The environment file is a dependency | |
| specification, not a platform-independent binary lockfile. | |
| ## Main entry points | |
| - `labelme_to_coco.py`: convert LabelMe annotations to ROI-aware COCO format. | |
| - `train_detectron2.py`: fine-tune the one-class Mask R-CNN model. | |
| - `evaluate_detectron2.py`: calculate COCO and union-mask metrics. | |
| - `analyze_segmentation_robustness.py`: reproduce score-threshold and | |
| segmentation-robustness analyses. | |
| - `audit_thermal_reduction.py`: calculate traceable thermal state summaries. | |
| - `analyze_optical_thermal_association.py`: perform state-level | |
| optical-thermal screening. | |
| - `analyze_multimodal_case.py`: prepare per-case optical, thermal, and AE | |
| summaries subject to the timing limits in `../timing_reconciliation.csv`. | |
| - `create_bubbleid_flow_showcase_video.py`: regenerate the derived presentation | |
| videos under `../Videos`. | |
| ## Reproduction boundary | |
| The release contains the 130 LabelMe files and checkpoint but does not include | |
| a frozen file-level 104/26 train/holdout split manifest, original training | |
| seed, augmentation record, or checkpoint-selection history. It therefore | |
| supports reanalysis and new split construction, but does not independently | |
| reconstruct the reported same-sequence evaluation exactly. | |