Metadata-Version: 2.4
Name: bioimageflow-measurement-tools
Version: 0.1.6
Summary: Lightweight measurement tools for BioImageFlow
Project-URL: Homepage, https://github.com/bioimageit/bioimageflow
Project-URL: Repository, https://github.com/bioimageit/bioimageflow
Project-URL: Issues, https://github.com/bioimageit/bioimageflow/issues
Author: BioImageFlow Contributors
License-Expression: BSD-4-Clause
License-File: LICENSE
Keywords: bioimage-analysis,bioimageflow,microscopy,workflow
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.10
Requires-Dist: bioimageflow-core<0.2,>=0.1.6
Requires-Dist: bioimageflow<0.2,>=0.1.6
Requires-Dist: imageio
Requires-Dist: numpy
Requires-Dist: pandas
Description-Content-Type: text/markdown

# bioimageflow-measurement-tools

Optional BioImageFlow package for object measurements, label counting, table
summaries, and segmentation benchmark metrics.

Core libraries: imageio, NumPy, pandas, and BioImageFlow's `ProcessingTool` and
`DataFrameTool` APIs. The package should grow toward a compact CellProfiler-like
measurement layer while keeping deterministic public tests.

## Tools

- `RegionProperties`
- `ShapeProperties`
- `IntensityProperties`
- `CountLabels`
- `SummarizeTable`
- `LabelBenchmark`
- `ObjectMatchingMetrics`
- `DiceIoU`
- `AggregatePerImage`
- `NormalizeFeatures`

## Tests

Run package tests with:

```bash
uv run pytest packages/bioimageflow-measurement-tools/tests
```

The tests use generated label images, intensity images, and tables with exact
expected values. Public-data workflow tests should assert stable ranges rather
than commit large datasets.
