Merge 7a22e51f5d into 3dcbb20cac

README.md

@@ -19,7 +19,8 @@
 * Output in [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML)
 * [OCR-D](https://github.com/qurator-spk/eynollah#use-as-ocr-d-processor) interface
 
-:warning: Development is currently focused on achieving the best possible quality of results for a wide variety of historical documents and therefore processing can be very slow.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.
+: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+historical documents and therefore processing can be very slow.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.
 
 ## Installation
 Python `3.8-3.11` with Tensorflow `<2.13` on Linux are currently supported.
@@ -42,7 +43,7 @@ cd eynollah; pip install -e .
 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/) or [huggingface](https://huggingface.co/SBB?search_models=eynollah). 
+Pretrained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/) 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).
 
@@ -50,10 +51,20 @@ For documentation on methods and models, have a look at [`models.md`](https://gi
 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).
 
 ## Usage
-The command-line interface can be called like this:
+Eynollah supports four use cases: layout analysis (segmentation), binarization, text recognition (OCR), 
+and (trainable) reading order detection.
+
+### Layout Analysis
+The layout analysis module is responsible for detecting layouts, identifying text lines, and determining reading order 
+using both heuristic methods or a machine-based reading order detection model. 
+
+Note that there are currently two supported ways for reading order detection: either as part of layout analysis based 
+on image input, or, currently under development, for given layout analysis results based on PAGE-XML data as input.
+
+The command-line interface for layout analysis can be called like this:
 
 ```sh
-eynollah \
+eynollah layout \
   -i <single image file> | -di <directory containing image files> \
   -o <output directory> \
   -m <directory containing model files> \
@@ -66,6 +77,7 @@ The following options can be used to further configure the processing:
 |-------------------|:-------------------------------------------------------------------------------|
 | `-fl`             | full layout analysis including all steps and segmentation classes              |
 | `-light`          | lighter and faster but simpler method for main region detection and deskewing  |
+| `-tll`            | this indicates the light textline and should be passed with light version      |
 | `-tab`            | apply table detection                                                          |
 | `-ae`             | apply enhancement (the resulting image is saved to the output directory)       |
 | `-as`             | apply scaling                                                                  |
@@ -80,11 +92,38 @@ The following options can be used to further configure the processing:
 | `-sp <directory>` | save cropped page image to this directory                                      |
 | `-sa <directory>` | save all (plot, enhanced/binary image, layout) to this directory               |
 
-If no option is set, the tool performs layout detection of main regions (background, text, images, separators and marginals).
+If no option is set, the tool performs layout detection of main regions (background, text, images, separators 
+and marginals).
 The best output quality is produced when RGB images are used as input rather than greyscale or binarized images.
 
-#### Use as OCR-D processor
+### Binarization
+The binarization module performs document image binarization using pretrained pixelwise segmentation models. 
 
+The command-line interface for binarization of single image can be called like this:
+
+```sh
+eynollah binarization \
+  -m <directory containing model files> \
+  <single image file> \
+  <output image>
+```
+
+and for flowing from a directory like this:
+
+```sh
+eynollah binarization \
+  -m <path to directory containing model files> \
+  -di <directory containing image files> \
+  -do <output directory>
+```
+
+### OCR
+Under development
+
+### Machine-based-reading-order
+Under development
+
+#### Use as OCR-D processor
 Eynollah ships with a CLI interface to be used as [OCR-D](https://ocr-d.de) [processor](https://ocr-d.de/en/spec/cli),
 formally described in [`ocrd-tool.json`](https://github.com/qurator-spk/eynollah/tree/main/src/eynollah/ocrd-tool.json).
 
@@ -92,7 +131,6 @@ In this case, the source image file group with (preferably) RGB images should be
 
     ocrd-eynollah-segment -I OCR-D-IMG -O OCR-D-SEG -P models 2022-04-05
 
-
 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_:
@@ -103,7 +141,6 @@ 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 2022-04-05
 
 Still, in general, it makes more sense to add other workflow steps **after** Eynollah.

src/eynollah/eynollah.py

@@ -4343,12 +4343,12 @@ class Eynollah:
             polygons_lines_xml = []
             contours_tables = []
             ocr_all_textlines = None
-            conf_contours_textregions =None
+            conf_contours_textregions = [0]
             pcgts = self.writer.build_pagexml_no_full_layout(
                 cont_page, page_coord, order_text_new, id_of_texts_tot,
                 all_found_textline_polygons, page_coord, polygons_of_images, polygons_of_marginals,
                 all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals,
-                cont_page, polygons_lines_xml, contours_tables, ocr_all_textlines, conf_contours_textregions)
+                cont_page, polygons_lines_xml, contours_tables, ocr_all_textlines, conf_contours_textregions, self.skip_layout_and_reading_order)
             return pcgts
 
         #print("text region early -1 in %.1fs", time.time() - t0)

src/eynollah/writer.py

@@ -168,7 +168,7 @@ class EynollahXmlWriter():
         with open(self.output_filename, 'w') as f:
             f.write(to_xml(pcgts))
 
-    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):
+    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):
         self.logger.debug('enter build_pagexml_no_full_layout')
 
         # create the file structure
@@ -184,7 +184,7 @@ class EynollahXmlWriter():
 
         for mm in range(len(found_polygons_text_region)):
             textregion = TextRegionType(id=counter.next_region_id, type_='paragraph',
-                    Coords=CoordsType(points=self.calculate_polygon_coords(found_polygons_text_region[mm], page_coord), conf=conf_contours_textregion[mm]),
+                    Coords=CoordsType(points=self.calculate_polygon_coords(found_polygons_text_region[mm], page_coord, skip_layout_reading_order), conf=conf_contours_textregion[mm]),
                     )
             #textregion.set_conf(conf_contours_textregion[mm])
             page.add_TextRegion(textregion)
@@ -303,10 +303,20 @@ class EynollahXmlWriter():
 
         return pcgts
 
-    def calculate_polygon_coords(self, contour, page_coord):
+    def calculate_polygon_coords(self, contour, page_coord, skip_layout_reading_order=False):
         self.logger.debug('enter calculate_polygon_coords')
         coords = ''
         for value_bbox in contour:
+            if skip_layout_reading_order:
+                if len(value_bbox) == 2:
+                    coords += str(int((value_bbox[0]) / self.scale_x))
+                    coords += ','
+                    coords += str(int((value_bbox[1]) / self.scale_y))
+                else:
+                    coords += str(int((value_bbox[0][0]) / self.scale_x))
+                    coords += ','
+                    coords += str(int((value_bbox[0][1]) / self.scale_y))
+            else:
                 if len(value_bbox) == 2:
                     coords += str(int((value_bbox[0] + page_coord[2]) / self.scale_x))
                     coords += ','