---
license: mit
metrics:
  - mean_iou
datasets:
  - Riksarkivet/placeholder_region_segmentation
tags:
  - mmdet
  - htrflow_core
  - instance segmentation
library_name: htrflow_core
library_version: 0.0.1
inference: false
pipeline_tag: image-segmentation
---

## Model Description

**RTMDet** is both an instance segmentation and object detection model from [OpenMMLab](https://mmyolo.readthedocs.io/en/latest/recommended_topics/algorithm_descriptions/rtmdet_description.html) and was trained using [MMDetection](https://mmdetection.readthedocs.io/en/latest/). This RTMDet model is fine-tuned to segment text regions within the documents, which enables a pre-localization text-line regions, which is a crucial step for current text-recognition models work at the text-line level.

## Usage

```python
#WIP
```

## Evaluation

(WIP)

## Training Data

(WIP)

## References

If you would like to learn more about the Swedish National Archives HTR pipeline or access the training data, please refer to the following resources:

- [The AI-lab at the Swedish National Archives](https://github.com/Swedish-National-Archives-AI-lab)
- [MMDetection](https://github.com/open-mmlab/mmdetection)
- [RTMDET Paper](https://paperswithcode.com/paper/rtmdet-an-empirical-study-of-designing-real)