mirror of
https://github.com/docling-project/docling.git
synced 2025-06-27 05:20:05 +00:00

* 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>
79 lines
2.8 KiB
Python
79 lines
2.8 KiB
Python
from pathlib import Path
|
|
|
|
from docling_core.types.doc import PictureClassificationData
|
|
|
|
from docling.datamodel.base_models import InputFormat
|
|
from docling.datamodel.document import ConversionResult
|
|
from docling.datamodel.pipeline_options import PdfPipelineOptions
|
|
from docling.document_converter import DocumentConverter, PdfFormatOption
|
|
from docling.pipeline.standard_pdf_pipeline import StandardPdfPipeline
|
|
|
|
|
|
def get_converter():
|
|
pipeline_options = PdfPipelineOptions()
|
|
pipeline_options.generate_page_images = True
|
|
|
|
pipeline_options.do_ocr = False
|
|
pipeline_options.do_table_structure = False
|
|
pipeline_options.do_code_enrichment = False
|
|
pipeline_options.do_formula_enrichment = False
|
|
pipeline_options.do_picture_classification = True
|
|
pipeline_options.generate_picture_images = True
|
|
pipeline_options.images_scale = 2
|
|
|
|
converter = DocumentConverter(
|
|
format_options={
|
|
InputFormat.PDF: PdfFormatOption(
|
|
pipeline_cls=StandardPdfPipeline,
|
|
pipeline_options=pipeline_options,
|
|
)
|
|
}
|
|
)
|
|
|
|
return converter
|
|
|
|
|
|
def test_picture_classifier():
|
|
pdf_path = Path("tests/data/pdf/picture_classification.pdf")
|
|
converter = get_converter()
|
|
|
|
print(f"converting {pdf_path}")
|
|
|
|
doc_result: ConversionResult = converter.convert(pdf_path)
|
|
|
|
results = doc_result.document.pictures
|
|
|
|
assert len(results) == 2
|
|
|
|
res = results[0]
|
|
assert len(res.annotations) == 1
|
|
assert isinstance(res.annotations[0], PictureClassificationData)
|
|
classification_data = res.annotations[0]
|
|
assert classification_data.provenance == "DocumentPictureClassifier"
|
|
assert len(classification_data.predicted_classes) == 16, (
|
|
"Number of predicted classes is not equal to 16"
|
|
)
|
|
confidences = [pred.confidence for pred in classification_data.predicted_classes]
|
|
assert confidences == sorted(confidences, reverse=True), (
|
|
"Predictions are not sorted in descending order of confidence"
|
|
)
|
|
assert classification_data.predicted_classes[0].class_name == "bar_chart", (
|
|
"The prediction is wrong for the bar chart image."
|
|
)
|
|
|
|
res = results[1]
|
|
assert len(res.annotations) == 1
|
|
assert isinstance(res.annotations[0], PictureClassificationData)
|
|
classification_data = res.annotations[0]
|
|
assert classification_data.provenance == "DocumentPictureClassifier"
|
|
assert len(classification_data.predicted_classes) == 16, (
|
|
"Number of predicted classes is not equal to 16"
|
|
)
|
|
confidences = [pred.confidence for pred in classification_data.predicted_classes]
|
|
assert confidences == sorted(confidences, reverse=True), (
|
|
"Predictions are not sorted in descending order of confidence"
|
|
)
|
|
assert classification_data.predicted_classes[0].class_name == "map", (
|
|
"The prediction is wrong for the bar chart image."
|
|
)
|