docling/tests/test_document_picture_classifier.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

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."
)