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82 lines
3.0 KiB
Python
82 lines
3.0 KiB
Python
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from pathlib import Path
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from docling_core.types.doc import PictureClassificationData
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from docling.backend.docling_parse_v2_backend import DoclingParseV2DocumentBackend
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.document import ConversionResult
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from docling.datamodel.pipeline_options import PdfPipelineOptions
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from docling.document_converter import DocumentConverter, PdfFormatOption
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from docling.pipeline.standard_pdf_pipeline import StandardPdfPipeline
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def get_converter():
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pipeline_options = PdfPipelineOptions()
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pipeline_options.generate_page_images = True
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pipeline_options.do_ocr = False
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pipeline_options.do_table_structure = False
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pipeline_options.do_code_enrichment = False
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pipeline_options.do_formula_enrichment = False
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pipeline_options.do_picture_classification = True
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pipeline_options.generate_picture_images = True
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pipeline_options.images_scale = 2
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converter = DocumentConverter(
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format_options={
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InputFormat.PDF: PdfFormatOption(
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backend=DoclingParseV2DocumentBackend,
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pipeline_cls=StandardPdfPipeline,
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pipeline_options=pipeline_options,
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)
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}
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)
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return converter
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def test_picture_classifier():
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pdf_path = Path("tests/data/picture_classification.pdf")
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converter = get_converter()
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print(f"converting {pdf_path}")
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doc_result: ConversionResult = converter.convert(pdf_path)
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results = doc_result.document.pictures
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assert len(results) == 2
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res = results[0]
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assert len(res.annotations) == 1
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assert type(res.annotations[0]) == PictureClassificationData
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classification_data = res.annotations[0]
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assert classification_data.provenance == "DocumentPictureClassifier"
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assert (
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len(classification_data.predicted_classes) == 16
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), "Number of predicted classes is not equal to 16"
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confidences = [pred.confidence for pred in classification_data.predicted_classes]
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assert confidences == sorted(
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confidences, reverse=True
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), "Predictions are not sorted in descending order of confidence"
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assert (
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classification_data.predicted_classes[0].class_name == "bar_chart"
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), "The prediction is wrong for the bar chart image."
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res = results[1]
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assert len(res.annotations) == 1
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assert type(res.annotations[0]) == PictureClassificationData
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classification_data = res.annotations[0]
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assert classification_data.provenance == "DocumentPictureClassifier"
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assert (
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len(classification_data.predicted_classes) == 16
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), "Number of predicted classes is not equal to 16"
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confidences = [pred.confidence for pred in classification_data.predicted_classes]
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assert confidences == sorted(
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confidences, reverse=True
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), "Predictions are not sorted in descending order of confidence"
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assert (
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classification_data.predicted_classes[0].class_name == "map"
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), "The prediction is wrong for the bar chart image."
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