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---
license: mit
metrics:
- mean_iou
datasets:
- Riksarkivet/placeholder_region_segmentation
tags:
- mmdet
- htrflow_core
- instance segmentation
library_name: htrflow
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)
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