feat(OCR): Introduce the OcrOptions.force_full_page_ocr parameter that forces a full page OCR scanning (#290)

- When the OCR is forced, any existing PDF cells are rejected.
- Introduce the force-ocr cmd parameter in docling CLI.
- Update unit tests.
- Add the full_page_ocr.py example in mkdocs.

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

docling/cli/main.py

@@ -153,6 +153,13 @@ def convert(
             ..., help="If enabled, the bitmap content will be processed using OCR."
         ),
     ] = True,
+    force_ocr: Annotated[
+        bool,
+        typer.Option(
+            ...,
+            help="Replace any existing text with OCR generated text over the full content.",
+        ),
+    ] = False,
     ocr_engine: Annotated[
         OcrEngine, typer.Option(..., help="The OCR engine to use.")
     ] = OcrEngine.EASYOCR,
@@ -219,11 +226,11 @@ def convert(
 
     match ocr_engine:
         case OcrEngine.EASYOCR:
-            ocr_options: OcrOptions = EasyOcrOptions()
+            ocr_options: OcrOptions = EasyOcrOptions(force_full_page_ocr=force_ocr)
         case OcrEngine.TESSERACT_CLI:
-            ocr_options = TesseractCliOcrOptions()
+            ocr_options = TesseractCliOcrOptions(force_full_page_ocr=force_ocr)
         case OcrEngine.TESSERACT:
-            ocr_options = TesseractOcrOptions()
+            ocr_options = TesseractOcrOptions(force_full_page_ocr=force_ocr)
         case _:
             raise RuntimeError(f"Unexpected OCR engine type {ocr_engine}")
 

docling/datamodel/pipeline_options.py

@@ -22,6 +22,7 @@ class TableStructureOptions(BaseModel):
 
 class OcrOptions(BaseModel):
     kind: str
+    force_full_page_ocr: bool = False  # If enabled a full page OCR is always applied
     bitmap_area_threshold: float = (
         0.05  # percentage of the area for a bitmap to processed with OCR
     )

docling/models/base_ocr_model.py

@@ -10,7 +10,7 @@ from PIL import Image, ImageDraw
 from rtree import index
 from scipy.ndimage import find_objects, label
 
-from docling.datamodel.base_models import OcrCell, Page
+from docling.datamodel.base_models import Cell, OcrCell, Page
 from docling.datamodel.document import ConversionResult
 from docling.datamodel.pipeline_options import OcrOptions
 from docling.datamodel.settings import settings
@@ -73,7 +73,9 @@ class BaseOcrModel(BasePageModel):
         coverage, ocr_rects = find_ocr_rects(page.size, bitmap_rects)
 
         # return full-page rectangle if sufficiently covered with bitmaps
-        if coverage > max(BITMAP_COVERAGE_TRESHOLD, self.options.bitmap_area_threshold):
+        if self.options.force_full_page_ocr or coverage > max(
+            BITMAP_COVERAGE_TRESHOLD, self.options.bitmap_area_threshold
+        ):
             return [
                 BoundingBox(
                     l=0,
@@ -96,7 +98,7 @@ class BaseOcrModel(BasePageModel):
             return ocr_rects
 
     # Filters OCR cells by dropping any OCR cell that intersects with an existing programmatic cell.
-    def filter_ocr_cells(self, ocr_cells, programmatic_cells):
+    def _filter_ocr_cells(self, ocr_cells, programmatic_cells):
         # Create R-tree index for programmatic cells
         p = index.Property()
         p.dimension = 2
@@ -117,6 +119,23 @@ class BaseOcrModel(BasePageModel):
         ]
         return filtered_ocr_cells
 
+    def post_process_cells(self, ocr_cells, programmatic_cells):
+        r"""
+        Post-process the ocr and programmatic cells and return the final list of of cells
+        """
+        if self.options.force_full_page_ocr:
+            # If a full page OCR is forced, use only the OCR cells
+            cells = [
+                Cell(id=c_ocr.id, text=c_ocr.text, bbox=c_ocr.bbox)
+                for c_ocr in ocr_cells
+            ]
+            return cells
+
+        ## Remove OCR cells which overlap with programmatic cells.
+        filtered_ocr_cells = self._filter_ocr_cells(ocr_cells, programmatic_cells)
+        programmatic_cells.extend(filtered_ocr_cells)
+        return programmatic_cells
+
     def draw_ocr_rects_and_cells(self, conv_res, page, ocr_rects, show: bool = False):
         image = copy.deepcopy(page.image)
         draw = ImageDraw.Draw(image, "RGBA")

docling/models/easyocr_model.py

@@ -5,7 +5,7 @@ import numpy
 import torch
 from docling_core.types.doc import BoundingBox, CoordOrigin
 
-from docling.datamodel.base_models import OcrCell, Page
+from docling.datamodel.base_models import Cell, OcrCell, Page
 from docling.datamodel.document import ConversionResult
 from docling.datamodel.pipeline_options import EasyOcrOptions
 from docling.datamodel.settings import settings
@@ -88,12 +88,8 @@ class EasyOcrModel(BaseOcrModel):
                         ]
                         all_ocr_cells.extend(cells)
 
-                    ## Remove OCR cells which overlap with programmatic cells.
-                    filtered_ocr_cells = self.filter_ocr_cells(
-                        all_ocr_cells, page.cells
-                    )
-
-                    page.cells.extend(filtered_ocr_cells)
+                    # Post-process the cells
+                    page.cells = self.post_process_cells(all_ocr_cells, page.cells)
 
                 # DEBUG code:
                 if settings.debug.visualize_ocr:

docling/models/tesseract_ocr_cli_model.py

@@ -7,7 +7,7 @@ from typing import Iterable, Optional, Tuple
 import pandas as pd
 from docling_core.types.doc import BoundingBox, CoordOrigin
 
-from docling.datamodel.base_models import OcrCell, Page
+from docling.datamodel.base_models import Cell, OcrCell, Page
 from docling.datamodel.document import ConversionResult
 from docling.datamodel.pipeline_options import TesseractCliOcrOptions
 from docling.datamodel.settings import settings
@@ -170,12 +170,8 @@ class TesseractOcrCliModel(BaseOcrModel):
                             )
                             all_ocr_cells.append(cell)
 
-                    ## Remove OCR cells which overlap with programmatic cells.
-                    filtered_ocr_cells = self.filter_ocr_cells(
-                        all_ocr_cells, page.cells
-                    )
-
-                    page.cells.extend(filtered_ocr_cells)
+                    # Post-process the cells
+                    page.cells = self.post_process_cells(all_ocr_cells, page.cells)
 
                 # DEBUG code:
                 if settings.debug.visualize_ocr:

docling/models/tesseract_ocr_model.py

@@ -3,7 +3,7 @@ from typing import Iterable
 
 from docling_core.types.doc import BoundingBox, CoordOrigin
 
-from docling.datamodel.base_models import OcrCell, Page
+from docling.datamodel.base_models import Cell, OcrCell, Page
 from docling.datamodel.document import ConversionResult
 from docling.datamodel.pipeline_options import TesseractOcrOptions
 from docling.datamodel.settings import settings
@@ -140,12 +140,8 @@ class TesseractOcrModel(BaseOcrModel):
                         # del high_res_image
                         all_ocr_cells.extend(cells)
 
-                    ## Remove OCR cells which overlap with programmatic cells.
-                    filtered_ocr_cells = self.filter_ocr_cells(
-                        all_ocr_cells, page.cells
-                    )
-
-                    page.cells.extend(filtered_ocr_cells)
+                    # Post-process the cells
+                    page.cells = self.post_process_cells(all_ocr_cells, page.cells)
 
                 # DEBUG code:
                 if settings.debug.visualize_ocr: