---
title: PanopticQuality
tags:
- evaluate
- metric
description: >-
  PanopticQuality score
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
emoji: 🕵️
---

# SEA-AI/PanopticQuality

This hugging face metric uses `seametrics.segmentation.PanopticQuality` under the hood to compute a panoptic quality score. It is a wrapper class for the torchmetrics class [`torchmetrics.detection.PanopticQuality`](https://lightning.ai/docs/torchmetrics/stable/detection/panoptic_quality.html). 

## Getting Started

To get started with PanopticQuality, make sure you have the necessary dependencies installed. This metric relies on the `evaluate`, `seametrics` and `seametrics[segmentation]`libraries for metric calculation and integration with FiftyOne datasets.

### Installation

First, ensure you have Python 3.8 or later installed. Then, install det-metrics using pip:

```sh
pip install evaluate git+https://github.com/SEA-AI/seametrics@develop
```

### Basic Usage


## Metric Settings

## Output Values

## Further References

- **seametrics Library**: Explore the [seametrics GitHub repository](https://github.com/SEA-AI/seametrics/tree/main) for more details on the underlying library.
- **Torchmetrics**: https://lightning.ai/docs/torchmetrics/stable/detection/panoptic_quality.html
- **Understanding Metrics**: The Panoptic Segmentation task, as well as Panoptic Quality as the evaluation metric, were introduced [in this paper](https://arxiv.org/pdf/1801.00868.pdf).

## Contribution

Your contributions are welcome! If you'd like to improve SEA-AI/PanopticQuality or add new features, please feel free to fork the repository, make your changes, and submit a pull request.