mirror of
https://github.com/DS4SD/docling.git
synced 2025-07-27 20:44:16 +00:00
585 lines
24 KiB
Python
585 lines
24 KiB
Python
import itertools
|
|
import logging
|
|
import re
|
|
from io import BytesIO
|
|
from pathlib import Path
|
|
from typing import Optional
|
|
|
|
from docling_core.types import DoclingDocument
|
|
from docling_core.types.doc import (
|
|
BoundingBox,
|
|
DocItem,
|
|
DocItemLabel,
|
|
DoclingDocument,
|
|
GroupLabel,
|
|
ImageRef,
|
|
ImageRefMode,
|
|
PictureItem,
|
|
ProvenanceItem,
|
|
Size,
|
|
TableCell,
|
|
TableData,
|
|
TableItem,
|
|
)
|
|
from docling_core.types.doc.tokens import DocumentToken, TableToken
|
|
|
|
from docling.backend.abstract_backend import AbstractDocumentBackend
|
|
from docling.backend.pdf_backend import PdfDocumentBackend
|
|
from docling.datamodel.base_models import Page
|
|
from docling.datamodel.document import ConversionResult
|
|
from docling.datamodel.pipeline_options import PdfPipelineOptions
|
|
from docling.models.smol_docling_model import SmolDoclingModel
|
|
from docling.pipeline.base_pipeline import PaginatedPipeline
|
|
from docling.utils.profiling import ProfilingScope, TimeRecorder
|
|
|
|
_log = logging.getLogger(__name__)
|
|
|
|
|
|
class VlmPipeline(PaginatedPipeline):
|
|
# _smol_vlm_path = "SmolDocling-0.0.2"
|
|
_smol_vlm_path = "SmolDocling_2.7_DT_0.7"
|
|
|
|
def __init__(self, pipeline_options: PdfPipelineOptions):
|
|
super().__init__(pipeline_options)
|
|
self.pipeline_options: PdfPipelineOptions
|
|
|
|
# force_backend_text = False - use text that is coming from SmolDocling
|
|
# force_backend_text = True - get text from backend using bounding boxes predicted by SmolDoclingss
|
|
self.force_backend_text = pipeline_options.force_backend_text
|
|
|
|
if pipeline_options.artifacts_path is None:
|
|
self.artifacts_path = self.download_models_hf()
|
|
else:
|
|
self.artifacts_path = Path(pipeline_options.artifacts_path)
|
|
|
|
keep_images = (
|
|
self.pipeline_options.generate_page_images
|
|
or self.pipeline_options.generate_picture_images
|
|
or self.pipeline_options.generate_table_images
|
|
)
|
|
|
|
self.build_pipe = [
|
|
SmolDoclingModel(
|
|
artifacts_path=self.artifacts_path / VlmPipeline._smol_vlm_path,
|
|
accelerator_options=pipeline_options.accelerator_options,
|
|
),
|
|
]
|
|
|
|
self.enrichment_pipe = [
|
|
# Other models working on `NodeItem` elements in the DoclingDocument
|
|
]
|
|
|
|
@staticmethod
|
|
def download_models_hf(
|
|
local_dir: Optional[Path] = None, force: bool = False
|
|
) -> Path:
|
|
from huggingface_hub import snapshot_download
|
|
from huggingface_hub.utils import disable_progress_bars
|
|
|
|
disable_progress_bars()
|
|
|
|
# TODO: download the correct model (private repo)
|
|
download_path = snapshot_download(
|
|
repo_id="ds4sd/xxx",
|
|
force_download=force,
|
|
local_dir=local_dir,
|
|
)
|
|
|
|
return Path(download_path)
|
|
|
|
def initialize_page(self, conv_res: ConversionResult, page: Page) -> Page:
|
|
with TimeRecorder(conv_res, "page_init"):
|
|
page._backend = conv_res.input._backend.load_page(page.page_no) # type: ignore
|
|
if page._backend is not None and page._backend.is_valid():
|
|
page.size = page._backend.get_size()
|
|
|
|
return page
|
|
|
|
def _assemble_document(self, conv_res: ConversionResult) -> ConversionResult:
|
|
with TimeRecorder(conv_res, "doc_assemble", scope=ProfilingScope.DOCUMENT):
|
|
|
|
conv_res.document = self._turn_tags_into_doc(conv_res.pages)
|
|
|
|
# Generate images of the requested element types
|
|
if (
|
|
self.pipeline_options.generate_picture_images
|
|
or self.pipeline_options.generate_table_images
|
|
):
|
|
scale = self.pipeline_options.images_scale
|
|
for element, _level in conv_res.document.iterate_items():
|
|
if not isinstance(element, DocItem) or len(element.prov) == 0:
|
|
continue
|
|
if (
|
|
isinstance(element, PictureItem)
|
|
and self.pipeline_options.generate_picture_images
|
|
) or (
|
|
isinstance(element, TableItem)
|
|
and self.pipeline_options.generate_table_images
|
|
):
|
|
page_ix = element.prov[0].page_no - 1
|
|
page = conv_res.pages[page_ix]
|
|
assert page.size is not None
|
|
assert page.image is not None
|
|
|
|
crop_bbox = (
|
|
element.prov[0]
|
|
.bbox.scaled(scale=scale)
|
|
.to_top_left_origin(page_height=page.size.height * scale)
|
|
)
|
|
|
|
cropped_im = page.image.crop(crop_bbox.as_tuple())
|
|
element.image = ImageRef.from_pil(
|
|
cropped_im, dpi=int(72 * scale)
|
|
)
|
|
|
|
return conv_res
|
|
|
|
def _turn_tags_into_doc(self, pages: list[Page]) -> DoclingDocument:
|
|
|
|
def extract_text_from_backend(page: Page, bbox: BoundingBox | None) -> str:
|
|
# Convert bounding box normalized to 0-100 into page coordinates for cropping
|
|
text = ""
|
|
if bbox:
|
|
if page.size:
|
|
bbox.l = bbox.l * page.size.width
|
|
bbox.t = bbox.t * page.size.height
|
|
bbox.r = bbox.r * page.size.width
|
|
bbox.b = bbox.b * page.size.height
|
|
if page._backend:
|
|
text = page._backend.get_text_in_rect(bbox)
|
|
return text
|
|
|
|
def extract_text(tag_content: str) -> str:
|
|
return re.sub(r"<.*?>", "", tag_content).strip()
|
|
|
|
def extract_bounding_box(tag_content: str) -> Optional[BoundingBox]:
|
|
locs = re.findall(r"<loc_(\d+)>", tag_content)
|
|
if len(locs) == 4:
|
|
l, t, r, b = map(float, locs)
|
|
l, t, r, b = [coord / 500.0 for coord in (l, t, r, b)]
|
|
return BoundingBox(l=l, t=t, r=r, b=b)
|
|
return None
|
|
|
|
def parse_texts(texts, tokens):
|
|
split_word = TableToken.OTSL_NL.value
|
|
split_row_tokens = [
|
|
list(y)
|
|
for x, y in itertools.groupby(tokens, lambda z: z == split_word)
|
|
if not x
|
|
]
|
|
table_cells = []
|
|
r_idx = 0
|
|
c_idx = 0
|
|
|
|
def count_right(tokens, c_idx, r_idx, which_tokens):
|
|
span = 0
|
|
c_idx_iter = c_idx
|
|
while tokens[r_idx][c_idx_iter] in which_tokens:
|
|
c_idx_iter += 1
|
|
span += 1
|
|
if c_idx_iter >= len(tokens[r_idx]):
|
|
return span
|
|
return span
|
|
|
|
def count_down(tokens, c_idx, r_idx, which_tokens):
|
|
span = 0
|
|
r_idx_iter = r_idx
|
|
while tokens[r_idx_iter][c_idx] in which_tokens:
|
|
r_idx_iter += 1
|
|
span += 1
|
|
if r_idx_iter >= len(tokens):
|
|
return span
|
|
return span
|
|
|
|
for i, text in enumerate(texts):
|
|
cell_text = ""
|
|
if text in [
|
|
TableToken.OTSL_FCEL.value,
|
|
TableToken.OTSL_ECEL.value,
|
|
TableToken.OTSL_CHED.value,
|
|
TableToken.OTSL_RHED.value,
|
|
TableToken.OTSL_SROW.value,
|
|
]:
|
|
row_span = 1
|
|
col_span = 1
|
|
right_offset = 1
|
|
if text != TableToken.OTSL_ECEL.value:
|
|
cell_text = texts[i + 1]
|
|
right_offset = 2
|
|
|
|
# Check next element(s) for lcel / ucel / xcel, set properly row_span, col_span
|
|
next_right_cell = ""
|
|
if i + right_offset < len(texts):
|
|
next_right_cell = texts[i + right_offset]
|
|
|
|
next_bottom_cell = ""
|
|
if r_idx + 1 < len(split_row_tokens):
|
|
if c_idx < len(split_row_tokens[r_idx + 1]):
|
|
next_bottom_cell = split_row_tokens[r_idx + 1][c_idx]
|
|
|
|
if next_right_cell in [
|
|
TableToken.OTSL_LCEL.value,
|
|
TableToken.OTSL_XCEL.value,
|
|
]:
|
|
# we have horisontal spanning cell or 2d spanning cell
|
|
col_span += count_right(
|
|
split_row_tokens,
|
|
c_idx + 1,
|
|
r_idx,
|
|
[TableToken.OTSL_LCEL.value, TableToken.OTSL_XCEL.value],
|
|
)
|
|
if next_bottom_cell in [
|
|
TableToken.OTSL_UCEL.value,
|
|
TableToken.OTSL_XCEL.value,
|
|
]:
|
|
# we have a vertical spanning cell or 2d spanning cell
|
|
row_span += count_down(
|
|
split_row_tokens,
|
|
c_idx,
|
|
r_idx + 1,
|
|
[TableToken.OTSL_UCEL.value, TableToken.OTSL_XCEL.value],
|
|
)
|
|
|
|
table_cells.append(
|
|
TableCell(
|
|
text=cell_text.strip(),
|
|
row_span=row_span,
|
|
col_span=col_span,
|
|
start_row_offset_idx=r_idx,
|
|
end_row_offset_idx=r_idx + row_span,
|
|
start_col_offset_idx=c_idx,
|
|
end_col_offset_idx=c_idx + col_span,
|
|
)
|
|
)
|
|
if text in [
|
|
TableToken.OTSL_FCEL.value,
|
|
TableToken.OTSL_ECEL.value,
|
|
TableToken.OTSL_CHED.value,
|
|
TableToken.OTSL_RHED.value,
|
|
TableToken.OTSL_SROW.value,
|
|
TableToken.OTSL_LCEL.value,
|
|
TableToken.OTSL_UCEL.value,
|
|
TableToken.OTSL_XCEL.value,
|
|
]:
|
|
c_idx += 1
|
|
if text == TableToken.OTSL_NL.value:
|
|
r_idx += 1
|
|
c_idx = 0
|
|
return table_cells, split_row_tokens
|
|
|
|
def extract_tokens_and_text(s: str):
|
|
# Pattern to match anything enclosed by < > (including the angle brackets themselves)
|
|
pattern = r"(<[^>]+>)"
|
|
# Find all tokens (e.g. "<otsl>", "<loc_140>", etc.)
|
|
tokens = re.findall(pattern, s)
|
|
# Remove any tokens that start with "<loc_"
|
|
tokens = [
|
|
token
|
|
for token in tokens
|
|
if not (token.startswith("<loc_") or token in ["<otsl>", "</otsl>"])
|
|
]
|
|
# Split the string by those tokens to get the in-between text
|
|
text_parts = re.split(pattern, s)
|
|
text_parts = [
|
|
token
|
|
for token in text_parts
|
|
if not (token.startswith("<loc_") or token in ["<otsl>", "</otsl>"])
|
|
]
|
|
# Remove any empty or purely whitespace strings from text_parts
|
|
text_parts = [part for part in text_parts if part.strip()]
|
|
|
|
return tokens, text_parts
|
|
|
|
def parse_table_content(otsl_content: str) -> TableData:
|
|
tokens, mixed_texts = extract_tokens_and_text(otsl_content)
|
|
table_cells, split_row_tokens = parse_texts(mixed_texts, tokens)
|
|
|
|
return TableData(
|
|
num_rows=len(split_row_tokens),
|
|
num_cols=(
|
|
max(len(row) for row in split_row_tokens) if split_row_tokens else 0
|
|
),
|
|
table_cells=table_cells,
|
|
)
|
|
|
|
doc = DoclingDocument(name="Example Document")
|
|
current_group = None
|
|
|
|
for pg_idx, page in enumerate(pages):
|
|
xml_content = ""
|
|
if page.predictions.doctags:
|
|
xml_content = page.predictions.doctags.tag_string
|
|
pil_image = page.image
|
|
page_no = pg_idx + 1
|
|
|
|
if page.size:
|
|
pg_width = page.size.width
|
|
pg_height = page.size.height
|
|
size = Size(width=pg_width, height=pg_height)
|
|
parent_page = doc.add_page(page_no=page_no, size=size)
|
|
|
|
lines = xml_content.split("\n")
|
|
bounding_boxes = []
|
|
|
|
for line in lines:
|
|
line = line.strip()
|
|
line = line.replace("<doc_tag>", "")
|
|
if line.startswith("<paragraph>"):
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "red"))
|
|
doc.add_text(
|
|
label=DocItemLabel.PARAGRAPH,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=(
|
|
ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
if prov_item
|
|
else None
|
|
),
|
|
)
|
|
elif line.startswith("<title>"):
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "blue"))
|
|
current_group = doc.add_group(
|
|
label=GroupLabel.SECTION, name=content
|
|
)
|
|
doc.add_text(
|
|
label=DocItemLabel.TITLE,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=(
|
|
ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
if prov_item
|
|
else None
|
|
),
|
|
)
|
|
|
|
elif line.startswith("<section_header_level_1>"):
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "green"))
|
|
current_group = doc.add_group(
|
|
label=GroupLabel.SECTION, name=content
|
|
)
|
|
doc.add_text(
|
|
label=DocItemLabel.SECTION_HEADER,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=(
|
|
ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
if prov_item
|
|
else None
|
|
),
|
|
)
|
|
|
|
elif line.startswith("<otsl>"):
|
|
prov_item = extract_bounding_box(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "aquamarine"))
|
|
|
|
table_data = parse_table_content(line)
|
|
doc.add_table(data=table_data, parent=current_group)
|
|
|
|
elif line.startswith("<footnote>"):
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "orange"))
|
|
doc.add_text(
|
|
label=DocItemLabel.FOOTNOTE,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=(
|
|
ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
if prov_item
|
|
else None
|
|
),
|
|
)
|
|
|
|
elif line.startswith("<page_header>"):
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "purple"))
|
|
doc.add_text(
|
|
label=DocItemLabel.PAGE_HEADER,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=(
|
|
ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
if prov_item
|
|
else None
|
|
),
|
|
)
|
|
|
|
elif line.startswith("<page_footer>"):
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "cyan"))
|
|
doc.add_text(
|
|
label=DocItemLabel.PAGE_FOOTER,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=(
|
|
ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
if prov_item
|
|
else None
|
|
),
|
|
)
|
|
|
|
elif line.startswith("<picture>"):
|
|
bbox = extract_bounding_box(line)
|
|
if bbox:
|
|
bounding_boxes.append((bbox, "yellow"))
|
|
if pil_image:
|
|
# Convert bounding box normalized to 0-100 into pixel coordinates for cropping
|
|
width, height = pil_image.size
|
|
crop_box = (
|
|
int(bbox.l * width),
|
|
int(bbox.t * height),
|
|
int(bbox.r * width),
|
|
int(bbox.b * height),
|
|
)
|
|
|
|
cropped_image = pil_image.crop(crop_box)
|
|
doc.add_picture(
|
|
parent=current_group,
|
|
image=ImageRef.from_pil(image=cropped_image, dpi=300),
|
|
prov=ProvenanceItem(
|
|
bbox=bbox, charspan=(0, 0), page_no=page_no
|
|
),
|
|
)
|
|
else:
|
|
doc.add_picture(
|
|
parent=current_group,
|
|
prov=ProvenanceItem(
|
|
bbox=bbox, charspan=(0, 0), page_no=page_no
|
|
),
|
|
)
|
|
elif line.startswith("<list_item>"):
|
|
prov_item_inst = None
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "brown"))
|
|
prov_item_inst = ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
doc.add_text(
|
|
label=DocItemLabel.LIST_ITEM,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=prov_item_inst if prov_item_inst else None,
|
|
)
|
|
|
|
elif line.startswith("<caption>"):
|
|
prov_item_inst = None
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "magenta"))
|
|
prov_item_inst = ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
doc.add_text(
|
|
label=DocItemLabel.PARAGRAPH,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=prov_item_inst if prov_item_inst else None,
|
|
)
|
|
elif line.startswith("<checkbox_unselected>"):
|
|
prov_item_inst = None
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "gray"))
|
|
prov_item_inst = ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
doc.add_text(
|
|
label=DocItemLabel.CHECKBOX_UNSELECTED,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=prov_item_inst if prov_item_inst else None,
|
|
)
|
|
|
|
elif line.startswith("<checkbox_selected>"):
|
|
prov_item_inst = None
|
|
prov_item = extract_bounding_box(line)
|
|
if self.force_backend_text:
|
|
content = extract_text_from_backend(page, prov_item)
|
|
else:
|
|
content = extract_text(line)
|
|
if prov_item:
|
|
bounding_boxes.append((prov_item, "black"))
|
|
prov_item_inst = ProvenanceItem(
|
|
bbox=prov_item, charspan=(0, 0), page_no=page_no
|
|
)
|
|
doc.add_text(
|
|
label=DocItemLabel.CHECKBOX_SELECTED,
|
|
text=content,
|
|
parent=current_group,
|
|
prov=prov_item_inst if prov_item_inst else None,
|
|
)
|
|
# return doc, bounding_boxes
|
|
return doc
|
|
|
|
@classmethod
|
|
def get_default_options(cls) -> PdfPipelineOptions:
|
|
return PdfPipelineOptions()
|
|
|
|
@classmethod
|
|
def is_backend_supported(cls, backend: AbstractDocumentBackend):
|
|
return isinstance(backend, PdfDocumentBackend)
|
|
|
|
# def _turn_tags_into_doc(self, document_tags):
|
|
# return DoclingDocument()
|