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| 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. |