The Pennington MATLAB to Python project is a collaborative undergraduate and graduate research effort led by the LSU Department of Mathematics and the Pennington Biomedical Research Center. The goal is to translate and preserve body-scanning and metabolic analysis workflows in Python.
The Python projects are now organized as staged compartments under unified/.
The primary interface is:
python -m unified --input INPUTStage-local commands remain available:
python -m unified img2obj --input IMAGE_OR_IMAGE_DIR
python -m unified obj2anthro --input OBJ_OR_OBJ_DIR --method slice --units auto
python -m unified ml| Stage | Path | Purpose |
|---|---|---|
| Image to OBJ | unified/img2obj/ |
Relocated Python_img_to_obj/ image preprocessor. |
| OBJ to anthropometry | unified/obj2anthro/ |
OBJ measurement orchestration and backend adapters. |
| Segmentation backend | unified/obj2anthro/backends/segmentation/ |
Relocated Python_Fall2025/. |
| Slice backend | Python_slice_2026/ |
Unmoved root implementation exposed through unified/obj2anthro/backends/slice/. |
| ML experiments | unified/ml/experiment/ |
Relocated Python_ML_2021/; historical ML/DOE code, not redesigned as inference. |
See unified/README.md for the staged tool and unified/RELOCATION_MAP.md for
old-to-new command mappings.
- Eliminate MATLAB licensing requirements where possible.
- Improve collaboration through Python's scientific ecosystem.
- Modernize documentation and execution paths while preserving established research implementations.
The codebase calculates metrics from human body scans and related datasets:
- 3D measurement from triangularized body-scan mesh objects (
.obj). - Biometric calculations such as body-section circumferences using geometric methods.
- Historical ML and DOE experiments retained for future staged integration.
As of Summer 2026, this project is being conducted under the guidance of Dr. Peter R. Wolenski, Russell B. Long Professor of Mathematics at LSU.