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README.md
53
README.md
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@ -19,7 +19,8 @@
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* Output in [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML)
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* [OCR-D](https://github.com/qurator-spk/eynollah#use-as-ocr-d-processor) interface
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:warning: Development is currently focused on achieving the best possible quality of results for a wide variety of historical documents and therefore processing can be very slow. We aim to improve this, but contributions are welcome.
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:warning: Development is currently focused on achieving the best possible quality of results for a wide variety of
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historical documents and therefore processing can be very slow. We aim to improve this, but contributions are welcome.
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## Installation
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Python `3.8-3.11` with Tensorflow `<2.13` on Linux are currently supported.
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@ -42,7 +43,7 @@ cd eynollah; pip install -e .
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Alternatively, you can run `make install` or `make install-dev` for editable installation.
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## Models
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Pre-trained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/) or [huggingface](https://huggingface.co/SBB?search_models=eynollah).
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Pretrained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/) or [huggingface](https://huggingface.co/SBB?search_models=eynollah).
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For documentation on methods and models, have a look at [`models.md`](https://github.com/qurator-spk/eynollah/tree/main/docs/models.md).
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@ -50,10 +51,20 @@ For documentation on methods and models, have a look at [`models.md`](https://gi
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In case you want to train your own model with Eynollah, have a look at [`train.md`](https://github.com/qurator-spk/eynollah/tree/main/docs/train.md).
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## Usage
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The command-line interface can be called like this:
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Eynollah supports four use cases: layout analysis (segmentation), binarization, text recognition (OCR),
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and (trainable) reading order detection.
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### Layout Analysis
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The layout analysis module is responsible for detecting layouts, identifying text lines, and determining reading order
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using both heuristic methods or a machine-based reading order detection model.
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Note that there are currently two supported ways for reading order detection: either as part of layout analysis based
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on image input, or, currently under development, for given layout analysis results based on PAGE-XML data as input.
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The command-line interface for layout analysis can be called like this:
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```sh
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eynollah \
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eynollah layout \
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-i <single image file> | -di <directory containing image files> \
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-o <output directory> \
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-m <directory containing model files> \
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@ -66,6 +77,7 @@ The following options can be used to further configure the processing:
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|-------------------|:-------------------------------------------------------------------------------|
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| `-fl` | full layout analysis including all steps and segmentation classes |
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| `-light` | lighter and faster but simpler method for main region detection and deskewing |
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| `-tll` | this indicates the light textline and should be passed with light version |
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| `-tab` | apply table detection |
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| `-ae` | apply enhancement (the resulting image is saved to the output directory) |
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| `-as` | apply scaling |
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@ -80,11 +92,38 @@ The following options can be used to further configure the processing:
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| `-sp <directory>` | save cropped page image to this directory |
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| `-sa <directory>` | save all (plot, enhanced/binary image, layout) to this directory |
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If no option is set, the tool performs layout detection of main regions (background, text, images, separators and marginals).
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If no option is set, the tool performs layout detection of main regions (background, text, images, separators
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and marginals).
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The best output quality is produced when RGB images are used as input rather than greyscale or binarized images.
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#### Use as OCR-D processor
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### Binarization
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The binarization module performs document image binarization using pretrained pixelwise segmentation models.
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The command-line interface for binarization of single image can be called like this:
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```sh
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eynollah binarization \
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-m <directory containing model files> \
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<single image file> \
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<output image>
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```
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and for flowing from a directory like this:
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```sh
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eynollah binarization \
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-m <path to directory containing model files> \
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-di <directory containing image files> \
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-do <output directory>
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```
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### OCR
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Under development
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### Machine-based-reading-order
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Under development
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#### Use as OCR-D processor
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Eynollah ships with a CLI interface to be used as [OCR-D](https://ocr-d.de) [processor](https://ocr-d.de/en/spec/cli),
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formally described in [`ocrd-tool.json`](https://github.com/qurator-spk/eynollah/tree/main/src/eynollah/ocrd-tool.json).
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@ -92,7 +131,6 @@ In this case, the source image file group with (preferably) RGB images should be
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ocrd-eynollah-segment -I OCR-D-IMG -O OCR-D-SEG -P models 2022-04-05
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If the input file group is PAGE-XML (from a previous OCR-D workflow step), Eynollah behaves as follows:
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- existing regions are kept and ignored (i.e. in effect they might overlap segments from Eynollah results)
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- existing annotation (and respective `AlternativeImage`s) are partially _ignored_:
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@ -103,7 +141,6 @@ If the input file group is PAGE-XML (from a previous OCR-D workflow step), Eynol
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(because some other preprocessing step was in effect like `denoised`), then
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the output PAGE-XML will be based on that as new top-level (`@imageFilename`)
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ocrd-eynollah-segment -I OCR-D-XYZ -O OCR-D-SEG -P models 2022-04-05
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Still, in general, it makes more sense to add other workflow steps **after** Eynollah.
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@ -4343,12 +4343,12 @@ class Eynollah:
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polygons_lines_xml = []
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contours_tables = []
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ocr_all_textlines = None
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conf_contours_textregions =None
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conf_contours_textregions = [0]
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pcgts = self.writer.build_pagexml_no_full_layout(
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cont_page, page_coord, order_text_new, id_of_texts_tot,
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all_found_textline_polygons, page_coord, polygons_of_images, polygons_of_marginals,
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all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals,
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cont_page, polygons_lines_xml, contours_tables, ocr_all_textlines, conf_contours_textregions)
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cont_page, polygons_lines_xml, contours_tables, ocr_all_textlines, conf_contours_textregions, self.skip_layout_and_reading_order)
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return pcgts
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#print("text region early -1 in %.1fs", time.time() - t0)
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@ -168,7 +168,7 @@ class EynollahXmlWriter():
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with open(self.output_filename, 'w') as f:
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f.write(to_xml(pcgts))
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def build_pagexml_no_full_layout(self, found_polygons_text_region, page_coord, order_of_texts, id_of_texts, all_found_textline_polygons, all_box_coord, found_polygons_text_region_img, found_polygons_marginals, all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals, cont_page, polygons_lines_to_be_written_in_xml, found_polygons_tables, ocr_all_textlines, conf_contours_textregion):
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def build_pagexml_no_full_layout(self, found_polygons_text_region, page_coord, order_of_texts, id_of_texts, all_found_textline_polygons, all_box_coord, found_polygons_text_region_img, found_polygons_marginals, all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals, cont_page, polygons_lines_to_be_written_in_xml, found_polygons_tables, ocr_all_textlines, conf_contours_textregion, skip_layout_reading_order=False):
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self.logger.debug('enter build_pagexml_no_full_layout')
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# create the file structure
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for mm in range(len(found_polygons_text_region)):
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textregion = TextRegionType(id=counter.next_region_id, type_='paragraph',
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Coords=CoordsType(points=self.calculate_polygon_coords(found_polygons_text_region[mm], page_coord), conf=conf_contours_textregion[mm]),
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Coords=CoordsType(points=self.calculate_polygon_coords(found_polygons_text_region[mm], page_coord, skip_layout_reading_order), conf=conf_contours_textregion[mm]),
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)
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#textregion.set_conf(conf_contours_textregion[mm])
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page.add_TextRegion(textregion)
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return pcgts
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def calculate_polygon_coords(self, contour, page_coord):
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def calculate_polygon_coords(self, contour, page_coord, skip_layout_reading_order=False):
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self.logger.debug('enter calculate_polygon_coords')
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coords = ''
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for value_bbox in contour:
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if len(value_bbox) == 2:
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coords += str(int((value_bbox[0] + page_coord[2]) / self.scale_x))
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coords += ','
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coords += str(int((value_bbox[1] + page_coord[0]) / self.scale_y))
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if skip_layout_reading_order:
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if len(value_bbox) == 2:
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coords += str(int((value_bbox[0]) / self.scale_x))
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coords += ','
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coords += str(int((value_bbox[1]) / self.scale_y))
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else:
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coords += str(int((value_bbox[0][0]) / self.scale_x))
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coords += ','
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coords += str(int((value_bbox[0][1]) / self.scale_y))
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else:
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coords += str(int((value_bbox[0][0] + page_coord[2]) / self.scale_x))
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coords += ','
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coords += str(int((value_bbox[0][1] + page_coord[0]) / self.scale_y))
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if len(value_bbox) == 2:
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coords += str(int((value_bbox[0] + page_coord[2]) / self.scale_x))
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coords += ','
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coords += str(int((value_bbox[1] + page_coord[0]) / self.scale_y))
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else:
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coords += str(int((value_bbox[0][0] + page_coord[2]) / self.scale_x))
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coords += ','
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coords += str(int((value_bbox[0][1] + page_coord[0]) / self.scale_y))
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coords=coords + ' '
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return coords[:-1]
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