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@ -57,7 +57,7 @@ make install EXTRAS=OCR
Pretrained models can be downloaded from [zenodo](https://zenodo.org/records/17194824) or [huggingface](https://huggingface.co/SBB?search_models=eynollah).
For documentation on methods and models, have a look at [`models.md`](https://github.com/qurator-spk/eynollah/tree/main/docs/models.md).
For documentation on models, have a look at [`models.md`](https://github.com/qurator-spk/eynollah/tree/main/docs/models.md).
Model cards are also provided for our trained models.
## Training
@ -74,7 +74,7 @@ image enhancement, text recognition (OCR), and reading order detection.
### Layout Analysis
The layout analysis module is responsible for detecting layout elements, identifying text lines, and determining reading
order using either heuristic methods or a reading order detection model.
order using either heuristic methods or a [pretrained reading order detection model](https://github.com/qurator-spk/eynollah#machine-based-reading-order).
Reading order detection can be performed either as part of layout analysis based on image input, or, currently under
development, based on pre-existing layout analysis results in PAGE-XML format as input.
@ -174,6 +174,7 @@ If the input file group is PAGE-XML (from a previous OCR-D workflow step), Eynol
(because some other preprocessing step was in effect like `denoised`), then
the output PAGE-XML will be based on that as new top-level (`@imageFilename`)
ocrd-eynollah-segment -I OCR-D-XYZ -O OCR-D-SEG -P models eynollah_layout_v0_5_0
In general, it makes more sense to add other workflow steps **after** Eynollah.