panoptica 0.5.4

Panoptic Quality (PQ) computation for binary masks.

Panoptica

Computing instance-wise segmentation quality metrics for 2D and 3D semantic- and instance segmentation maps.

Features

The package provides 3 core modules:

1. Instance Approximator
2. Instance Matcher
3. Panoptic Evaluator

Installation

To install the current release, you can simply run:

pip install panoptica

Use Cases

Semantic Segmentation Input

Although for many biomedical segmentation problems, an instance-wise evaluation is highly relevant and desirable, they are still addressed as semantic segmentation problems due to lack of appropriate instance labels.

Modules [1-3] can be used to obtain panoptic metrics of matched instances based on a semantic segmentation input.

Unmatched Instances Input

It is a common issue that instance segementation outputs have good segmentations with mismatched labels.

For this case modules [2-3] can be utilized to match the instances and report panoptic metrics.

Matched Instances Input

Ideally the input data already provides matched instances.

In this case module 3 can be used to directly report panoptic metrics without requiring any internal preprocessing.

Tutorials

Juypter notebook Tutorials are avalable for all use cases in our tutorials repo.

Citation

If you have used panoptica in your research, please cite us! The citation can be exported from: TODO