mirror of
https://github.com/qurator-spk/eynollah.git
synced 2025-11-10 06:34:11 +01:00
22 lines
1.2 KiB
Markdown
22 lines
1.2 KiB
Markdown
|
When using Eynollah in OCR-D, the source image file group with (preferably) RGB images should be used as input like this:
|
||
|
|
|
||
|
|
ocrd-eynollah-segment -I OCR-D-IMG -O OCR-D-SEG -P models eynollah_layout_v0_5_0
|
||
|
|
|
||
|
|
If the input file group is PAGE-XML (from a previous OCR-D workflow step), Eynollah behaves as follows:
|
||
|
|
- existing regions are kept and ignored (i.e. in effect they might overlap segments from Eynollah results)
|
||
|
|
- existing annotation (and respective `AlternativeImage`s) are partially _ignored_:
|
||
|
|
- previous page frame detection (`cropped` images)
|
||
|
|
- previous derotation (`deskewed` images)
|
||
|
|
- previous thresholding (`binarized` images)
|
||
|
|
- if the page-level image nevertheless deviates from the original (`@imageFilename`)
|
||
|
|
(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.
|
||
|
|
|
||
|
|
There is also an OCR-D processor for binarization:
|
||
|
|
|
||
|
|
ocrd-sbb-binarize -I OCR-D-IMG -O OCR-D-BIN -P models default-2021-03-09
|