qurator-spk
/
eynollah
mirror of https://github.com/qurator-spk/eynollah.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

Update README.md

Browse Source
pull/102/head
cneud 1 year ago
parent 419e589df7
commit c7057bad5e
1 changed files with 8 additions and 9 deletions
Show Stats Download Patch File Download Diff File

17
README.md
Unescape Escape View File

@ -38,6 +38,11 @@ cd eynollah; pip install -e .
Alternatively, you can run `make install` or `make install-dev` for editable installation. Alternatively, you can run `make install` or `make install-dev` for editable installation.
## Models
Pre-trained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/).
In case you want to train your own model to use with Eynollah, have a look at [sbb_pixelwise_segmentation](https://github.com/qurator-spk/sbb_pixelwise_segmentation).
## Usage ## Usage
The command-line interface can be called like this: The command-line interface can be called like this:
@ -70,13 +75,7 @@ The following options can be used to further configure the processing:
| `-sa <directory>` | save all (plot, enhanced/binary image, layout) to this directory | | `-sa <directory>` | save all (plot, enhanced/binary image, layout) to this directory |
If no option is set, the tool will perform layout detection of main regions (background, text, images, separators and marginals). If no option is set, the tool will perform layout detection of main regions (background, text, images, separators and marginals).
The tool produces better quality output when RGB images are used as input than greyscale or binarized images.
The tool produces better output from RGB images as input than greyscale or binarized images.
## Models
Pre-trained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/).
In case you want to train your own model to use with Eynollah, have a look at [sbb_pixelwise_segmentation](https://github.com/qurator-spk/sbb_pixelwise_segmentation).
#### Use as OCR-D processor #### Use as OCR-D processor
@ -88,10 +87,10 @@ In this case, the source image file group with (preferably) RGB images should be
ocrd-eynollah-segment -I OCR-D-IMG -O SEG-LINE -P models ocrd-eynollah-segment -I OCR-D-IMG -O SEG-LINE -P models
``` ```
Any image referenced by `@imageFilename` in PAGE-XML is passed on directly to Eynollah as a processor, so that e.g. calling Any image referenced by `@imageFilename` in PAGE-XML is passed on directly to Eynollah as a processor, so that e.g.
``` ```
ocrd-eynollah-segment -I OCR-D-IMG-BIN -O SEG-LINE -P models ocrd-eynollah-segment -I OCR-D-IMG-BIN -O SEG-LINE -P models
``` ```
still uses the original (RGB) image despite any binarization that may have occured in previous OCR-D processing steps uses the original (RGB) image despite any binarization that may have occured in previous OCR-D processing steps

Write Preview
Loading…
Cancel
Save