pyPetrograph

v0.0.6

pyPetrograph is a machine-learning toolkit for thin-section petrography.

Warning: This tool is under development. Use with caution. APIs and numbers can still change.

What it does

Hand-label features and map their area %. Paint a few examples of each class you care about (pores, grains, cement, …) from color, edge sharpness, and microtexture. A LightGBM pixel classifier (random forest or XGBoost optional) maps the rest of the photo and reports area % of each class.

Count grains on a painted mineral map. Match pixels to a color legend, split grains that touch, and count how many grains sit in each class.

Segment grains from a multi-image overlay. Line up several image types of the same field (plane-polarized light, crossed polars, or others) and refine grain outlines with a U-Net, so boundaries are not drawn from one lighting alone.

For finer grain-boundary mapping there is optional support for SegmentEveryGrain (Zoltan Sylvester). SAM 2.1 weights (~860 MB) are a further opt-in on their page, not part of the default install.

Install

pip install pypetrograph

pip install segmenteverygrain

The second line is optional (SegmentEveryGrain’s existing-environment path).

Demos

Example notebooks, test images, and figures are in the GitHub repository.

Credits

The current version is primarily developed by Larry Syu-Heng Lai, based on early source code scripted by Zoltan Sylvester, at the Quantitative Clastic Laboratory, Bureau of Economic Geology, The University of Texas at Austin. This development is also part of a collaboration with Priyanka Periwal, Lucy Tingwei Ko, Kelly Hattori, and Amanda Calle across multiple research groups and the e-MAGE lab in the Bureau of Economic Geology.

License

GNU Affero General Public License 3.0 or later (LICENSE).