idaholab / panda
This software provides dislocation-type defect identification and segmentation using a standard open source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of expert annotated micrographs for training.
Code health
idaholab/panda scores 10.0 out of 10 on defect risk, which Repowise rates Excellent. Maintainability scores 10.0 out of 10. Static performance risk scores 10.0 out of 10. The three are scored separately and never blended into a single number.
Full health report- Files
- 1
- Symbols
- 0
- Modules
- 0
- Doc pages
- 2
- Dead exports
- 0
Read more about idaholab/panda
- OverviewFiles, symbols, languages, packages, git intelligence
- ArchitectureDependency graph, layered architecture, symbol index, and third-party dependencies
- Code healthPer-file health scores, hotspots, test coverage, dead code, and refactoring targets
- AI explanationsProModule-by-module documentation generated from source
Add a badge to your README
Both badges are public, cached, and update on their own after every index. Nothing to install.
Repowise badge
Links to this page. Adding it also re-indexes the repo every week.
[](https://repowise.dev/repo/idaholab/panda)Code health badge
Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/idaholab/panda)How idaholab/panda works
This software provides dislocation-type defect identification and segmentation using a standard open source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of expert annotated micrographs for training. This page is an auto-generated, always-fresh map of the idaholab/panda repository, written primarily in Jupyter Notebook. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.
The codebase has 1 source files, 0 symbols, and 1 language, organised into 0 modules, led by markdown.
Use the links above to open the interactive dashboards, or connect this repo to your editor via the Repowise MCP server for grounded answers inside Claude, Cursor, or VS Code.