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@@ -4,23 +4,26 @@ license: mit
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  tags:
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  - Doc-UFCN
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  - PyTorch
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- - Object detection
 
 
 
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  metrics:
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  - IoU
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  - F1
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  - AP@.5
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  - AP@.75
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  - AP@[.5,.95]
 
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  ---
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- # Hugin-Munin line detection
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-
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- The Hugin-Munin line detection model predicts text lines from Hugin-Munin document images. This model was developed during the [HUGIN-MUNIN project](https://hugin-munin-project.github.io/).
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  ## Model description
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- The model has been trained using the Doc-UFCN library on Hugin-Munin document images.
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  It has been trained on images with their largest dimension equal to 768 pixels, keeping the original aspect ratio.
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  The model predicts two classes: vertical and horizontal text lines.
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@@ -29,7 +32,7 @@ The model predicts two classes: vertical and horizontal text lines.
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  The model achieves the following results:
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  | set | class | IoU | F1 | AP@[.5] | AP@[.75] | AP@[.5,.95] |
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- | ----- | ---------- | ----- | ----- | ------- | -------- | ----------- |
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  | train | vertical | 88.29 | 89.67 | 71.37 | 33.26 | 36.32 |
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  | | horizontal | 69.81 | 81.35 | 91.73 | 36.62 | 45.67 |
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  | val | vertical | 73.01 | 75.13 | 46.02 | 4.99 | 15.58 |
@@ -54,4 +57,4 @@ Please refer to the Doc-UFCN library page (https://pypi.org/project/doc-ufcn/) t
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  pages = {2134-2141},
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  doi = {10.1109/ICPR48806.2021.9412447}
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  }
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- ```
 
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  tags:
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  - Doc-UFCN
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  - PyTorch
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+ - object-detection
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+ - dla
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+ - historical
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+ - handwritten
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  metrics:
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  - IoU
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  - F1
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  - AP@.5
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  - AP@.75
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  - AP@[.5,.95]
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+ pipeline_tag: image-segmentation
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  ---
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+ # Doc-UFCN - NorHand v1 - Line detection
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+ The NorHand v1 line detection model predicts text lines from NorHand document images. This model was developed during the [HUGIN-MUNIN project](https://hugin-munin-project.github.io/).
 
 
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  ## Model description
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+ The model has been trained using the Doc-UFCN library on NorHand document images.
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  It has been trained on images with their largest dimension equal to 768 pixels, keeping the original aspect ratio.
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  The model predicts two classes: vertical and horizontal text lines.
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  The model achieves the following results:
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  | set | class | IoU | F1 | AP@[.5] | AP@[.75] | AP@[.5,.95] |
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+ | ----- | ---------- | ----: | ----: | ------: | -------: | ----------: |
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  | train | vertical | 88.29 | 89.67 | 71.37 | 33.26 | 36.32 |
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  | | horizontal | 69.81 | 81.35 | 91.73 | 36.62 | 45.67 |
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  | val | vertical | 73.01 | 75.13 | 46.02 | 4.99 | 15.58 |
 
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  pages = {2134-2141},
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  doi = {10.1109/ICPR48806.2021.9412447}
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  }
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+ ```