Docling/docling/models/picture_description_base_model.py
Michele Dolfi 5458a88464
ci: add coverage and ruff (#1383)
* add coverage calculation and push

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* new codecov version and usage of token

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* enable ruff formatter instead of black and isort

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* apply ruff lint fixes

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* apply ruff unsafe fixes

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add removed imports

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* runs 1 on linter issues

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* finalize linter fixes

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* Update pyproject.toml

Co-authored-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com>
Signed-off-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>

---------

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Signed-off-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>
Co-authored-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com>
2025-04-14 18:01:26 +02:00

92 lines
2.9 KiB
Python

from abc import abstractmethod
from collections.abc import Iterable
from pathlib import Path
from typing import List, Optional, Type, Union
from docling_core.types.doc import (
DoclingDocument,
NodeItem,
PictureItem,
)
from docling_core.types.doc.document import ( # TODO: move import to docling_core.types.doc
PictureDescriptionData,
)
from PIL import Image
from docling.datamodel.pipeline_options import (
AcceleratorOptions,
PictureDescriptionBaseOptions,
)
from docling.models.base_model import (
BaseItemAndImageEnrichmentModel,
BaseModelWithOptions,
ItemAndImageEnrichmentElement,
)
class PictureDescriptionBaseModel(
BaseItemAndImageEnrichmentModel, BaseModelWithOptions
):
images_scale: float = 2.0
def __init__(
self,
*,
enabled: bool,
enable_remote_services: bool,
artifacts_path: Optional[Union[Path, str]],
options: PictureDescriptionBaseOptions,
accelerator_options: AcceleratorOptions,
):
self.enabled = enabled
self.options = options
self.provenance = "not-implemented"
def is_processable(self, doc: DoclingDocument, element: NodeItem) -> bool:
return self.enabled and isinstance(element, PictureItem)
def _annotate_images(self, images: Iterable[Image.Image]) -> Iterable[str]:
raise NotImplementedError
def __call__(
self,
doc: DoclingDocument,
element_batch: Iterable[ItemAndImageEnrichmentElement],
) -> Iterable[NodeItem]:
if not self.enabled:
for element in element_batch:
yield element.item
return
images: List[Image.Image] = []
elements: List[PictureItem] = []
for el in element_batch:
assert isinstance(el.item, PictureItem)
describe_image = True
# Don't describe the image if it's smaller than the threshold
if len(el.item.prov) > 0:
prov = el.item.prov[0] # PictureItems have at most a single provenance
page = doc.pages.get(prov.page_no)
if page is not None:
page_area = page.size.width * page.size.height
if page_area > 0:
area_fraction = prov.bbox.area() / page_area
if area_fraction < self.options.picture_area_threshold:
describe_image = False
if describe_image:
elements.append(el.item)
images.append(el.image)
outputs = self._annotate_images(images)
for item, output in zip(elements, outputs):
item.annotations.append(
PictureDescriptionData(text=output, provenance=self.provenance)
)
yield item
@classmethod
@abstractmethod
def get_options_type(cls) -> Type[PictureDescriptionBaseOptions]:
pass