move logic in BaseTextImageEnrichmentModel

Signed-off-by: Michele Dolfi <[email protected]>

docling/datamodel/base_models.py

@@ -7,6 +7,7 @@
     PictureDataType,
     Size,
     TableCell,
+    TextItem,
 )
 from docling_core.types.io import (  # DO ΝΟΤ REMOVE; explicitly exposed from this location
     DocumentStream,
@@ -201,6 +202,13 @@ class AssembledUnit(BaseModel):
     headers: List[PageElement] = []
 
 
+class TextImageEnrichmentElement(BaseModel):
+    element: TextItem
+    image: Image
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+
 class Page(BaseModel):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 

docling/models/base_model.py

@@ -1,10 +1,10 @@
 from abc import ABC, abstractmethod
 from typing import Any, Generic, Iterable, Optional
 
-from docling_core.types.doc import DoclingDocument, NodeItem
+from docling_core.types.doc import DoclingDocument, NodeItem, TextItem
 from typing_extensions import TypeVar
 
-from docling.datamodel.base_models import Page
+from docling.datamodel.base_models import Page, TextImageEnrichmentElement
 from docling.datamodel.document import ConversionResult
 
 
@@ -46,3 +46,22 @@ def prepare_element(
         if self.is_processable(doc=conv_res.document, element=element):
             return element
         return None
+
+
+class BaseTextImageEnrichmentModel(GenericEnrichmentModel[TextImageEnrichmentElement]):
+
+    images_scale: float
+
+    def prepare_element(
+        self, conv_res: ConversionResult, element: NodeItem
+    ) -> Optional[TextImageEnrichmentElement]:
+        if not self.is_processable(doc=conv_res.document, element=element):
+            return None
+
+        assert isinstance(element, TextItem)
+        element_prov = element.prov[0]
+        page_ix = element_prov.page_no - 1
+        cropped_image = conv_res.pages[page_ix].get_image(
+            scale=self.images_scale, cropbox=element_prov.bbox
+        )
+        return TextImageEnrichmentElement(element=element, image=cropped_image)

docs/examples/develop_formula_understanding.py

@@ -3,31 +3,21 @@
 from typing import Iterable
 
 from docling_core.types.doc import DocItemLabel, DoclingDocument, NodeItem, TextItem
-from PIL import Image as PILImage
-from pydantic import BaseModel, ConfigDict
 
-from docling.datamodel.base_models import InputFormat
-from docling.datamodel.document import ConversionResult
+from docling.datamodel.base_models import InputFormat, TextImageEnrichmentElement
 from docling.datamodel.pipeline_options import PdfPipelineOptions
 from docling.document_converter import DocumentConverter, PdfFormatOption
-from docling.models.base_model import BaseEnrichmentModel, GenericEnrichmentModel
+from docling.models.base_model import BaseTextImageEnrichmentModel
 from docling.pipeline.standard_pdf_pipeline import StandardPdfPipeline
 
 
 class ExampleFormulaUPipelineOptions(PdfPipelineOptions):
     do_formula_understanding: bool = True
 
 
-class FormulaEnrichmentElement(BaseModel):
-    element: TextItem
-    image: PILImage.Image
-
-    model_config = ConfigDict(arbitrary_types_allowed=True)
-
-
-class ExampleFormulaUEnrichmentModel(GenericEnrichmentModel[FormulaEnrichmentElement]):
-
-    images_scale: float = 2.6
+# A new enrichment model using both the document element and its image as input
+class ExampleFormulaUEnrichmentModel(BaseTextImageEnrichmentModel):
+    images_scale = 2.6
 
     def __init__(self, enabled: bool):
         self.enabled = enabled
@@ -39,21 +29,8 @@ def is_processable(self, doc: DoclingDocument, element: NodeItem) -> bool:
             and element.label == DocItemLabel.FORMULA
         )
 
-    def prepare_element(
-        self, conv_res: ConversionResult, element: NodeItem
-    ) -> FormulaEnrichmentElement:
-        if self.is_processable(doc=conv_res.document, element=element):
-            assert isinstance(element, TextItem)
-            element_prov = element.prov[0]
-            page_ix = element_prov.page_no - 1
-            cropped_image = conv_res.pages[page_ix].get_image(
-                scale=self.images_scale, cropbox=element_prov.bbox
-            )
-
-            return FormulaEnrichmentElement(element=element, image=cropped_image)
-
     def __call__(
-        self, doc: DoclingDocument, element_batch: Iterable[FormulaEnrichmentElement]
+        self, doc: DoclingDocument, element_batch: Iterable[TextImageEnrichmentElement]
     ) -> Iterable[NodeItem]:
         if not self.enabled:
             return