✨ sbb_textline_detector: Add a OCR-D interface

ocrd-tool.json

@@ -0,0 +1 @@
+qurator/sbb_textline_detector/ocrd-tool.json

qurator/sbb_textline_detector/__init__.py

@@ -1 +1,2 @@
 from .main import *
+from .ocrd_cli import *

qurator/sbb_textline_detector/main.py

@@ -35,16 +35,18 @@ __doc__ = \
 
 
 class textlineerkenner:
-    def __init__(self, image_dir, dir_out, dir_models):
+    def __init__(self, image_dir, dir_out, f_name, dir_models):
         self.image_dir = image_dir
         self.dir_out = dir_out
+        self.f_name = f_name
+        if self.f_name is None:
+            try:
+                self.f_name = image_dir.split('/')[len(image_dir.split('/')) - 1]
+                self.f_name = self.f_name.split('.')[0]
+                print(self.f_name)
+            except:
+                self.f_name = self.f_name.split('.')[0]
         self.dir_models = dir_models
-        try:
-            self.f_name = image_dir.split('/')[len(image_dir.split('/')) - 1]
-            self.f_name = self.f_name.split('.')[0]
-            print(self.f_name)
-        except:
-            self.f_name = self.f_name.split('.')[0]
         self.kernel = np.ones((5, 5), np.uint8)
         self.model_page_dir = dir_models + '/model_page.h5'
         self.model_region_dir = dir_models + '/model_strukturerkennung.h5'
@@ -365,6 +367,7 @@ class textlineerkenner:
         return img_r
 
     def get_image_and_scales(self):
+        print(self.image_dir)
         self.image = cv2.imread(self.image_dir)
         self.height_org = self.image.shape[0]
         self.width_org = self.image.shape[1]
@@ -1298,7 +1301,7 @@ class textlineerkenner:
             unireg.text = ' '
 
         tree = ET.ElementTree(data)
-        tree.write(dir_of_image + self.f_name + ".xml")
+        tree.write(os.path.join(dir_of_image, self.f_name) + ".xml")
 
     def run(self):
         self.get_image_and_scales()
@@ -1321,7 +1324,7 @@ class textlineerkenner:
 def main(image, out, model):
     possibles = globals()  # XXX unused?
     possibles.update(locals())
-    x = textlineerkenner(image, out, model)
+    x = textlineerkenner(image, out, None, model)
     x.run()
 
 

qurator/sbb_textline_detector/ocrd-tool.json

@@ -0,0 +1,19 @@
+{
+  "version": "0.0.1",
+  "tools": {
+    "ocrd_sbb_textline_detector": {
+      "executable": "ocrd_sbb_textline_detector",
+      "description": "Detect lines",
+      "steps": ["layout/segmentation/line"],
+      "input_file_grp": [
+        "OCR-D-IMG"
+      ],
+      "output_file_grp": [
+        "OCR-D-SBB-SEG-LINE"
+      ],
+      "parameters": {
+        "model": {"type": "string", "format": "file", "cacheable": true}
+      }
+    }
+  }
+}

qurator/sbb_textline_detector/ocrd_cli.py

@@ -0,0 +1,61 @@
+import json
+import os
+
+import click
+from ocrd import Processor
+from ocrd.decorators import ocrd_cli_options, ocrd_cli_wrap_processor
+from ocrd_utils import concat_padded, getLogger
+from pkg_resources import resource_string
+
+from qurator.sbb_textline_detector import textlineerkenner
+
+log = getLogger('processor.OcrdSbbTextlineDetectorRecognize')
+
+OCRD_TOOL = json.loads(resource_string(__name__, 'ocrd-tool.json').decode('utf8'))
+
+
+@click.command()
+@ocrd_cli_options
+def ocrd_sbb_textline_detector(*args, **kwargs):
+    return ocrd_cli_wrap_processor(OcrdSbbTextlineDetectorRecognize, *args, **kwargs)
+
+
+class OcrdSbbTextlineDetectorRecognize(Processor):
+
+    def __init__(self, *args, **kwargs):
+        kwargs['ocrd_tool'] = OCRD_TOOL['tools']['ocrd_sbb_textline_detector']
+        super(OcrdSbbTextlineDetectorRecognize, self).__init__(*args, **kwargs)
+
+    def _make_file_id(self, input_file, input_file_grp, n):
+        file_id = input_file.ID.replace(input_file_grp, self.output_file_grp)
+        if file_id == input_file.ID:
+            file_id = concat_padded(self.output_file_grp, n)
+        return file_id
+
+    def process(self):
+        for n, page_id in enumerate(self.workspace.mets.physical_pages):
+            image_file = self.workspace.mets.find_files(fileGrp=self.input_file_grp, pageId=page_id)[0]
+            log.info("INPUT FILE %i / %s", n, image_file)
+
+            file_id = self._make_file_id(image_file, self.output_file_grp, n)
+
+            # Process the files
+            try:
+                os.mkdir(self.output_file_grp)
+            except FileExistsError:
+                pass
+
+            model = self.parameter['model']
+            x = textlineerkenner(image_file.local_filename, self.output_file_grp, file_id, model)
+            x.run()
+
+            self.workspace.add_file(
+                 ID=file_id + '.xml',
+                 file_grp=self.output_file_grp,
+                 pageId=page_id,
+                 mimetype='application/vnd.prima.page+xml',
+                 local_filename=self.output_file_grp + '/' + file_id)
+
+
+if __name__ == '__main__':
+    ocrd_sbb_textline_detector()

requirements.txt

@@ -1,5 +1,5 @@
 opencv-python
-numpy<=1.14.5
+numpy
 matplotlib
 seaborn
 tqdm
@@ -9,3 +9,4 @@ scikit-learn
 tensorflow-gpu < 2.0
 scipy
 click
+ocrd >= 1.0.0b19

setup.py

@@ -21,6 +21,7 @@ setup(
     entry_points={
       'console_scripts': [
         "sbb_textline_detector=qurator.sbb_textline_detector:main",
+        "ocrd_sbb_textline_detector=qurator.sbb_textline_detector:ocrd_sbb_textline_detector",
       ]
     },
     python_requires='>=3.6.0',