diff --git a/CHANGELOG.md b/CHANGELOG.md index f7f074fed..8344bf2d0 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -6,6 +6,8 @@ * **Update encoders to leverage dataclasses** All encoders now follow a class approach which get annotated with the dataclass decorator. Similar to the connectors, it uses a nested dataclass for the configs required to configure a client as well as a field/property approach to cache the client. This makes sure any variable associated with the class exists as a dataclass field. ### Features + +* **Store base64 encoded image data in metadata fields.** Rather than saving to file, stores base64 encoded data of the image bytes and the mimetype for the image in metadata fields: `image_base64` and `image_mime_type` (if that is what the user specifies by some other param like `pdf_extract_to_payload`). This would allow the API to have parity with the library. ### Fixes diff --git a/example-docs/embedded-images-tables.jpg b/example-docs/embedded-images-tables.jpg new file mode 100644 index 000000000..0445e7358 Binary files /dev/null and b/example-docs/embedded-images-tables.jpg differ diff --git a/example-docs/embedded-images-tables.pdf b/example-docs/embedded-images-tables.pdf new file mode 100644 index 000000000..fcf1c483d --- /dev/null +++ b/example-docs/embedded-images-tables.pdf @@ -0,0 +1,944 @@ +%PDF-1.7 +% +1 0 obj +<< /MarkInfo << /Marked true >> /Metadata 3 0 R /Names 4 0 R /OpenAction [ 5 0 R /FitH 804 ] /Outlines 6 0 R /PageLabels << /Nums [ 0 << /S /D /St 4 >> ] >> /PageLayout /SinglePage /PageMode /UseOutlines /Pages 7 0 R /StructTreeRoot 9 0 R /Threads 12 0 R /Type /Catalog >> +endobj +2 0 obj +<< /Author (Omotayo Sanni) /CreationDate (D:20181229014113+05'30') /Creator (Elsevier) /CrossMarkDomains#5b1#5d (elsevier.com) /CrossMarkDomains#5b2#5d (sciencedirect.com) /CrossmarkDomainExclusive (true) /CrossmarkMajorVersionDate (2010-04-23) /ElsevierWebPDFSpecifications (6.5) /Keywords (Corrosion; Stainless steel; Inhibitor; Sulphuric acid) /ModDate (D:20181229014113+05'30') /Subject (Data in Brief, 22 \(2018\) 451-457. doi:10.1016/j.dib.2018.11.134) /Title (Data on environmental sustainable corrosion inhibitor for stainless steel in aggressive environment) /doi (10.1016/j.dib.2018.11.134) /robots (noindex) >> +endobj +3 0 obj +<< /Subtype /XML /Type /Metadata /Length 7222 >> +stream + + + + + application/pdf + doi:10.1016/j.dib.2018.11.134 + + + Data on environmental sustainable corrosion inhibitor for stainless steel in aggressive environment + + + + + Omotayo Sanni + Abimbola Patricia I. 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a/test_unstructured/partition/pdf_image/test_image.py b/test_unstructured/partition/pdf_image/test_image.py index b8004c3ff..f8a29d706 100644 --- a/test_unstructured/partition/pdf_image/test_image.py +++ b/test_unstructured/partition/pdf_image/test_image.py @@ -1,5 +1,6 @@ import os import pathlib +import tempfile from unittest import mock import pytest @@ -7,6 +8,7 @@ from PIL import Image from pytesseract import TesseractError from unstructured_inference.inference import layout +from test_unstructured.partition.pdf_image.test_pdf import assert_element_extraction from test_unstructured.unit_utils import assert_round_trips_through_JSON, example_doc_path from unstructured.chunking.title import chunk_by_title from unstructured.documents.elements import ElementType @@ -632,3 +634,34 @@ def test_partition_image_has_filename(inference_results): assert element.metadata.filetype == "JPEG" # This should be kept from the filename we originally gave assert element.metadata.filename == filename + + +@pytest.mark.parametrize("file_mode", ["filename", "rb"]) +@pytest.mark.parametrize("extract_to_payload", [False, True]) +def test_partition_image_element_extraction( + file_mode, + extract_to_payload, + filename=example_doc_path("embedded-images-tables.jpg"), +): + extract_element_types = ["Image", "Table"] + + with tempfile.TemporaryDirectory() as tmpdir: + if file_mode == "filename": + elements = image.partition_image( + filename=filename, + strategy="hi_res", + extract_element_types=extract_element_types, + extract_to_payload=extract_to_payload, + image_output_dir_path=tmpdir, + ) + else: + with open(filename, "rb") as f: + elements = image.partition_image( + file=f, + strategy="hi_res", + extract_element_types=extract_element_types, + extract_to_payload=extract_to_payload, + image_output_dir_path=tmpdir, + ) + + assert_element_extraction(elements, extract_element_types, extract_to_payload, tmpdir) diff --git a/test_unstructured/partition/pdf_image/test_pdf.py b/test_unstructured/partition/pdf_image/test_pdf.py index fa14ee017..8dd45376d 100644 --- a/test_unstructured/partition/pdf_image/test_pdf.py +++ b/test_unstructured/partition/pdf_image/test_pdf.py @@ -1,6 +1,8 @@ +import base64 import logging import math import os +import tempfile from tempfile import SpooledTemporaryFile from unittest import mock @@ -15,6 +17,7 @@ from unstructured.documents.coordinates import PixelSpace from unstructured.documents.elements import ( CoordinatesMetadata, ElementMetadata, + ElementType, ListItem, NarrativeText, Text, @@ -1123,3 +1126,62 @@ def test_extractable_elements_repair_invalid_pdf_structure(filename, expected_lo caplog.set_level(logging.INFO) assert pdf.extractable_elements(filename=example_doc_path(filename)) assert expected_log in caplog.text + + +def assert_element_extraction(elements, extract_element_types, extract_to_payload, tmpdir): + extracted_elements = [] + for el_type in extract_element_types: + extracted_elements_by_type = [] + for el in elements: + if el.category == el_type: + extracted_elements_by_type.append(el) + extracted_elements.append(extracted_elements_by_type) + + for extracted_elements_by_type in extracted_elements: + for i, el in enumerate(extracted_elements_by_type): + if extract_to_payload: + assert el.metadata.image_base64 is not None + assert el.metadata.image_mime_type == "image/jpeg" + image_data = base64.b64decode(el.metadata.image_base64) + assert isinstance(image_data, bytes) + assert el.metadata.image_path is None + else: + basename = "table" if el.category == ElementType.TABLE else "figure" + expected_image_path = os.path.join( + str(tmpdir), f"{basename}-{el.metadata.page_number}-{i + 1}.jpg" + ) + assert el.metadata.image_path == expected_image_path + assert os.path.isfile(expected_image_path) + assert el.metadata.image_base64 is None + assert el.metadata.image_mime_type is None + + +@pytest.mark.parametrize("file_mode", ["filename", "rb"]) +@pytest.mark.parametrize("extract_to_payload", [False, True]) +def test_partition_pdf_element_extraction( + file_mode, + extract_to_payload, + filename=example_doc_path("embedded-images-tables.pdf"), +): + extract_element_types = ["Image", "Table"] + + with tempfile.TemporaryDirectory() as tmpdir: + if file_mode == "filename": + elements = pdf.partition_pdf( + filename=filename, + strategy="hi_res", + extract_element_types=extract_element_types, + extract_to_payload=extract_to_payload, + image_output_dir_path=tmpdir, + ) + else: + with open(filename, "rb") as f: + elements = pdf.partition_pdf( + file=f, + strategy="hi_res", + extract_element_types=extract_element_types, + extract_to_payload=extract_to_payload, + image_output_dir_path=tmpdir, + ) + + assert_element_extraction(elements, extract_element_types, extract_to_payload, tmpdir) diff --git a/test_unstructured/partition/pdf_image/test_pdf_image_utils.py b/test_unstructured/partition/pdf_image/test_pdf_image_utils.py index 2ae7ffa69..13bc2b50b 100644 --- a/test_unstructured/partition/pdf_image/test_pdf_image_utils.py +++ b/test_unstructured/partition/pdf_image/test_pdf_image_utils.py @@ -7,7 +7,7 @@ from PIL import Image as PILImg from test_unstructured.unit_utils import example_doc_path from unstructured.documents.coordinates import PixelSpace -from unstructured.documents.elements import ElementMetadata, ElementType, Image +from unstructured.documents.elements import ElementMetadata, ElementType, Image, Table from unstructured.partition.pdf_image import pdf_image_utils @@ -60,58 +60,66 @@ def test_convert_pdf_to_image( assert isinstance(images[0], PILImg.Image) -def test_save_elements(filename=example_doc_path("embedded-images.pdf")): +@pytest.mark.parametrize("element_category_to_save", [ElementType.IMAGE, ElementType.TABLE]) +@pytest.mark.parametrize("extract_to_payload", [False, True]) +def test_save_elements( + element_category_to_save, + extract_to_payload, + filename=example_doc_path("layout-parser-paper-fast.pdf"), +): with tempfile.TemporaryDirectory() as tmpdir: elements = [ Image( text="3", - coordinates=( - (78.7401411111111, 86.61545694444455), - (78.7401411111111, 519.9487805555556), - (512.0734647222223, 519.9487805555556), - (512.0734647222223, 86.61545694444455), - ), + coordinates=((78, 86), (78, 519), (512, 519), (512, 86)), coordinate_system=PixelSpace(width=1575, height=1166), metadata=ElementMetadata(page_number=1), ), Image( text="4", - coordinates=( - (570.8661397222222, 86.6154566666667), - (570.8661397222222, 519.6862825000001), - (1003.9369655555556, 519.6862825000001), - (1003.9369655555556, 86.6154566666667), - ), + coordinates=((570, 86), (570, 519), (1003, 519), (1003, 86)), coordinate_system=PixelSpace(width=1575, height=1166), metadata=ElementMetadata(page_number=1), ), Image( text="5", - coordinates=( - (1062.9921808333331, 86.61545694444455), - (1062.9921808333331, 519.9487805555556), - (1496.3255044444445, 519.9487805555556), - (1496.3255044444445, 86.61545694444455), - ), + coordinates=((1062, 86), (1062, 519), (1496, 519), (1496, 86)), coordinate_system=PixelSpace(width=1575, height=1166), metadata=ElementMetadata(page_number=1), ), + Table( + text="Sample Table", + coordinates=((1062, 86), (1062, 519), (1496, 519), (1496, 86)), + coordinate_system=PixelSpace(width=1575, height=1166), + metadata=ElementMetadata(page_number=2), + ), ] pdf_image_utils.save_elements( elements=elements, - element_category_to_save=ElementType.IMAGE, + element_category_to_save=element_category_to_save, pdf_image_dpi=200, filename=filename, output_dir_path=str(tmpdir), + extract_to_payload=extract_to_payload, ) - for i, el in enumerate(elements): + saved_elements = [el for el in elements if el.category == element_category_to_save] + for i, el in enumerate(saved_elements): + basename = "table" if el.category == ElementType.TABLE else "figure" expected_image_path = os.path.join( - str(tmpdir), f"figure-{el.metadata.page_number}-{i + 1}.jpg" + str(tmpdir), f"{basename}-{el.metadata.page_number}-{i + 1}.jpg" ) - assert os.path.isfile(el.metadata.image_path) - assert el.metadata.image_path == expected_image_path + if extract_to_payload: + assert isinstance(el.metadata.image_base64, str) + assert isinstance(el.metadata.image_mime_type, str) + assert not el.metadata.image_path + assert not os.path.isfile(expected_image_path) + else: + assert os.path.isfile(expected_image_path) + assert el.metadata.image_path == expected_image_path + assert not el.metadata.image_base64 + assert not el.metadata.image_mime_type def test_write_image_raises_error(): diff --git a/test_unstructured/partition/test_auto.py b/test_unstructured/partition/test_auto.py index aaf9f1ca7..4df28143d 100644 --- a/test_unstructured/partition/test_auto.py +++ b/test_unstructured/partition/test_auto.py @@ -3,7 +3,7 @@ import os import pathlib import warnings from importlib import import_module -from unittest.mock import ANY, Mock, patch +from unittest.mock import Mock, patch import docx import pytest @@ -347,15 +347,17 @@ def test_auto_partition_pdf_with_fast_strategy(monkeypatch): mock_partition.assert_called_once_with( filename=filename, - metadata_filename=None, file=None, url=None, - include_page_breaks=False, - infer_table_structure=False, - extract_images_in_pdf=ANY, - image_output_dir_path=ANY, strategy=PartitionStrategy.FAST, languages=None, + metadata_filename=None, + include_page_breaks=False, + infer_table_structure=False, + extract_images_in_pdf=False, + extract_element_types=None, + image_output_dir_path=None, + extract_to_payload=False, hi_res_model_name=None, ) diff --git a/unstructured/documents/elements.py b/unstructured/documents/elements.py index 0e152c8fa..0a87b56b0 100644 --- a/unstructured/documents/elements.py +++ b/unstructured/documents/elements.py @@ -173,9 +173,11 @@ class ElementMetadata: file_directory: Optional[str] filename: Optional[str] filetype: Optional[str] + image_path: Optional[str] + image_base64: Optional[str] + image_mime_type: Optional[str] # -- specific to DOCX which has distinct primary, first-page, and even-page header/footers -- header_footer_type: Optional[str] - image_path: Optional[str] # -- used in chunks only, when chunk must be split mid-text to fit window -- is_continuation: Optional[bool] languages: Optional[List[str]] @@ -457,6 +459,8 @@ class ConsolidationStrategy(enum.Enum): "filetype": cls.FIRST, "header_footer_type": cls.DROP, "image_path": cls.DROP, + "image_base64": cls.DROP, + "image_mime_type": cls.DROP, "is_continuation": cls.DROP, # -- not expected, added by chunking, not before -- "languages": cls.LIST_UNIQUE, "last_modified": cls.FIRST, diff --git a/unstructured/partition/auto.py b/unstructured/partition/auto.py index be6ebfe34..23d7d9ec3 100644 --- a/unstructured/partition/auto.py +++ b/unstructured/partition/auto.py @@ -137,7 +137,9 @@ def partition( detect_language_per_element: bool = False, pdf_infer_table_structure: bool = False, pdf_extract_images: bool = False, + pdf_extract_element_types: Optional[List[str]] = None, pdf_image_output_dir_path: Optional[str] = None, + pdf_extract_to_payload: bool = False, xml_keep_tags: bool = False, data_source_metadata: Optional[DataSourceMetadata] = None, metadata_filename: Optional[str] = None, @@ -193,11 +195,26 @@ def partition( transformation of the data into an HTML . The "text" field for a partitioned Table Element is always present, whether True or False. pdf_extract_images - If True and strategy=hi_res, any detected images will be saved in the path specified by - pdf_image_output_dir_path. + Only applicable if `strategy=hi_res`. + If True, any detected images will be saved in the path specified by 'image_output_dir_path' + or stored as base64 encoded data within metadata fields. + Deprecation Note: This parameter is marked for deprecation. Future versions will use + 'extract_element_types' for broader extraction capabilities. + pdf_extract_element_types + Only applicable if `strategy=hi_res`. + Images of the element type(s) specified in this list (e.g., ["Image", "Table"]) will be + saved in the path specified by 'image_output_dir_path' or stored as base64 encoded data + within metadata fields. + pdf_extract_to_payload + Only applicable if `strategy=hi_res`. + If True, images of the element type(s) defined in 'extract_element_types' will be encoded + as base64 data and stored in two metadata fields: 'image_base64' and 'image_mime_type'. + This parameter facilitates the inclusion of element data directly within the payload, + especially for web-based applications or APIs. pdf_image_output_dir_path - If pdf_extract_images=True and strategy=hi_res, any detected images will be saved in the - given path + Only applicable if `strategy=hi_res` and `pdf_extract_to_payload=False`. + The filesystem path for saving images of the element type(s) + specified in 'extract_element_types'. xml_keep_tags If True, will retain the XML tags in the output. Otherwise it will simply extract the text from within the tags. Only applies to partition_xml. @@ -397,7 +414,9 @@ def partition( strategy=strategy, languages=languages, extract_images_in_pdf=pdf_extract_images, + extract_element_types=pdf_extract_element_types, image_output_dir_path=pdf_image_output_dir_path, + extract_to_payload=pdf_extract_to_payload, hi_res_model_name=hi_res_model_name or model_name, **kwargs, ) diff --git a/unstructured/partition/image.py b/unstructured/partition/image.py index 4c1ba1fa6..9fb890d28 100644 --- a/unstructured/partition/image.py +++ b/unstructured/partition/image.py @@ -26,6 +26,10 @@ def partition_image( metadata_last_modified: Optional[str] = None, chunking_strategy: Optional[str] = None, hi_res_model_name: Optional[str] = None, + extract_images_in_pdf: bool = False, + extract_element_types: Optional[List[str]] = None, + image_output_dir_path: Optional[str] = None, + extract_to_payload: bool = False, **kwargs, ) -> List[Element]: """Parses an image into a list of interpreted elements. @@ -58,6 +62,27 @@ def partition_image( The last modified date for the document. hi_res_model_name The layout detection model used when partitioning strategy is set to `hi_res`. + extract_images_in_pdf + Only applicable if `strategy=hi_res`. + If True, any detected images will be saved in the path specified by 'image_output_dir_path' + or stored as base64 encoded data within metadata fields. + Deprecation Note: This parameter is marked for deprecation. Future versions will use + 'extract_element_types' for broader extraction capabilities. + extract_element_types + Only applicable if `strategy=hi_res`. + Images of the element type(s) specified in this list (e.g., ["Image", "Table"]) will be + saved in the path specified by 'image_output_dir_path' or stored as base64 encoded data + within metadata fields. + extract_to_payload + Only applicable if `strategy=hi_res`. + If True, images of the element type(s) defined in 'extract_element_types' will be encoded + as base64 data and stored in two metadata fields: 'image_base64' and 'image_mime_type'. + This parameter facilitates the inclusion of element data directly within the payload, + especially for web-based applications or APIs. + image_output_dir_path + Only applicable if `strategy=hi_res` and `extract_to_payload=False`. + The filesystem path for saving images of the element type(s) + specified in 'extract_element_types'. """ exactly_one(filename=filename, file=file) @@ -93,5 +118,9 @@ def partition_image( strategy=strategy, metadata_last_modified=metadata_last_modified, hi_res_model_name=hi_res_model_name, + extract_images_in_pdf=extract_images_in_pdf, + extract_element_types=extract_element_types, + image_output_dir_path=image_output_dir_path, + extract_to_payload=extract_to_payload, **kwargs, ) diff --git a/unstructured/partition/pdf.py b/unstructured/partition/pdf.py index 696f18be4..4df6eb5ef 100644 --- a/unstructured/partition/pdf.py +++ b/unstructured/partition/pdf.py @@ -106,7 +106,6 @@ from unstructured.utils import requires_dependencies if TYPE_CHECKING: pass - # NOTE(alan): Patching this to fix a bug in pdfminer.six. Submitted this PR into pdfminer.six to fix # the bug: https://github.com/pdfminer/pdfminer.six/pull/885 psparser.PSBaseParser._parse_keyword = parse_keyword # type: ignore @@ -140,10 +139,11 @@ def partition_pdf( metadata_last_modified: Optional[str] = None, chunking_strategy: Optional[str] = None, # used by decorator links: Sequence[Link] = [], + hi_res_model_name: Optional[str] = None, extract_images_in_pdf: bool = False, extract_element_types: Optional[List[str]] = None, image_output_dir_path: Optional[str] = None, - hi_res_model_name: Optional[str] = None, + extract_to_payload: bool = False, **kwargs, ) -> List[Element]: """Parses a pdf document into a list of interpreted elements. @@ -173,18 +173,29 @@ def partition_pdf( with Tesseract, you'll first need to install the appropriate Tesseract language pack. metadata_last_modified The last modified date for the document. - extract_images_in_pdf - Only applicable if `strategy=hi_res`. - If `True`, any detected images will be saved in the path specified by - image_output_dir_path. - extract_element_types - Only applicable if `strategy=hi_res`. - Images of the element type(s) defined in this list will be saved to `image_output_dir_path`. - image_output_dir_path - Only applicable if `strategy=hi_res`. - The path for saving images when using `extract_images_in_pdf` or `extract_element_types`. hi_res_model_name The layout detection model used when partitioning strategy is set to `hi_res`. + extract_images_in_pdf + Only applicable if `strategy=hi_res`. + If True, any detected images will be saved in the path specified by 'image_output_dir_path' + or stored as base64 encoded data within metadata fields. + Deprecation Note: This parameter is marked for deprecation. Future versions will use + 'extract_element_types' for broader extraction capabilities. + extract_element_types + Only applicable if `strategy=hi_res`. + Images of the element type(s) specified in this list (e.g., ["Image", "Table"]) will be + saved in the path specified by 'image_output_dir_path' or stored as base64 encoded data + within metadata fields. + extract_to_payload + Only applicable if `strategy=hi_res`. + If True, images of the element type(s) defined in 'extract_element_types' will be encoded + as base64 data and stored in two metadata fields: 'image_base64' and 'image_mime_type'. + This parameter facilitates the inclusion of element data directly within the payload, + especially for web-based applications or APIs. + image_output_dir_path + Only applicable if `strategy=hi_res` and `extract_to_payload=False`. + The filesystem path for saving images of the element type(s) + specified in 'extract_element_types'. """ exactly_one(filename=filename, file=file) @@ -199,10 +210,11 @@ def partition_pdf( infer_table_structure=infer_table_structure, languages=languages, metadata_last_modified=metadata_last_modified, + hi_res_model_name=hi_res_model_name, extract_images_in_pdf=extract_images_in_pdf, extract_element_types=extract_element_types, image_output_dir_path=image_output_dir_path, - hi_res_model_name=hi_res_model_name, + extract_to_payload=extract_to_payload, **kwargs, ) @@ -249,13 +261,14 @@ def _partition_pdf_or_image_local( languages: Optional[List[str]] = None, ocr_mode: str = OCRMode.FULL_PAGE.value, model_name: Optional[str] = None, # to be deprecated in favor of `hi_res_model_name` + hi_res_model_name: Optional[str] = None, + pdf_image_dpi: Optional[int] = None, metadata_last_modified: Optional[str] = None, pdf_text_extractable: bool = False, extract_images_in_pdf: bool = False, extract_element_types: Optional[List[str]] = None, image_output_dir_path: Optional[str] = None, - pdf_image_dpi: Optional[int] = None, - hi_res_model_name: Optional[str] = None, + extract_to_payload: bool = False, analysis: bool = False, analyzed_image_output_dir_path: Optional[str] = None, **kwargs, @@ -402,7 +415,9 @@ def _partition_pdf_or_image_local( element_category_to_save=ElementType.IMAGE, filename=filename, file=file, + is_image=is_image, pdf_image_dpi=pdf_image_dpi, + extract_to_payload=extract_to_payload, output_dir_path=image_output_dir_path, ) @@ -415,7 +430,9 @@ def _partition_pdf_or_image_local( element_category_to_save=el_type, filename=filename, file=file, + is_image=is_image, pdf_image_dpi=pdf_image_dpi, + extract_to_payload=extract_to_payload, output_dir_path=image_output_dir_path, ) @@ -425,10 +442,12 @@ def _partition_pdf_or_image_local( continue if isinstance(el, Image): - # NOTE(crag): small chunks of text from Image elements tend to be garbage - if not el.metadata.image_path and ( - el.text is None or len(el.text) < 24 or el.text.find(" ") == -1 + if ( + not extract_images_in_pdf + and ElementType.IMAGE not in extract_element_types + and (el.text is None or len(el.text) < 24 or el.text.find(" ") == -1) ): + # NOTE(crag): small chunks of text from Image elements tend to be garbage continue else: out_elements.append(cast(Element, el)) @@ -457,10 +476,11 @@ def partition_pdf_or_image( ocr_languages: Optional[str] = None, languages: Optional[List[str]] = None, metadata_last_modified: Optional[str] = None, + hi_res_model_name: Optional[str] = None, extract_images_in_pdf: bool = False, extract_element_types: Optional[List[str]] = None, image_output_dir_path: Optional[str] = None, - hi_res_model_name: Optional[str] = None, + extract_to_payload: bool = False, **kwargs, ) -> List[Element]: """Parses a pdf or image document into a list of interpreted elements.""" @@ -518,11 +538,12 @@ def partition_pdf_or_image( include_page_breaks=include_page_breaks, languages=languages, metadata_last_modified=metadata_last_modified or last_modification_date, + hi_res_model_name=hi_res_model_name, pdf_text_extractable=pdf_text_extractable, extract_images_in_pdf=extract_images_in_pdf, extract_element_types=extract_element_types, image_output_dir_path=image_output_dir_path, - hi_res_model_name=hi_res_model_name, + extract_to_payload=extract_to_payload, **kwargs, ) out_elements = _process_uncategorized_text_elements(elements) diff --git a/unstructured/partition/pdf_image/pdf_image_utils.py b/unstructured/partition/pdf_image/pdf_image_utils.py index ee9c9d29f..5ffd8d07f 100644 --- a/unstructured/partition/pdf_image/pdf_image_utils.py +++ b/unstructured/partition/pdf_image/pdf_image_utils.py @@ -1,5 +1,7 @@ +import base64 import os import tempfile +from io import BytesIO from pathlib import PurePath from typing import TYPE_CHECKING, BinaryIO, List, Optional, Union, cast @@ -79,11 +81,17 @@ def save_elements( pdf_image_dpi: int, filename: str = "", file: Optional[Union[bytes, BinaryIO]] = None, + is_image: bool = False, + extract_to_payload: bool = False, output_dir_path: Optional[str] = None, ): """ - Extract and save images from the page. This method iterates through the layout elements - of the page, identifies image regions, and extracts and saves them as separate image files. + Saves specific elements from a PDF as images either to a directory or embeds them in the + element's payload. + + This function processes a list of elements partitioned from a PDF file. For each element of + a specified category, it extracts and saves the image. The images can either be saved to + a specified directory or embedded into the element's payload as a base64-encoded string. """ if not output_dir_path: @@ -91,14 +99,25 @@ def save_elements( os.makedirs(output_dir_path, exist_ok=True) with tempfile.TemporaryDirectory() as temp_dir: - _image_paths = convert_pdf_to_image( - filename, - file, - pdf_image_dpi, - output_folder=temp_dir, - path_only=True, - ) - image_paths = cast(List[str], _image_paths) + if is_image: + if file is None: + image_paths = [filename] + else: + if hasattr(file, "seek"): + file.seek(0) + temp_file = tempfile.NamedTemporaryFile(delete=False, dir=temp_dir) + temp_file.write(file.read() if hasattr(file, "read") else file) + temp_file.flush() + image_paths = [temp_file.name] + else: + _image_paths = convert_pdf_to_image( + filename, + file, + pdf_image_dpi, + output_folder=temp_dir, + path_only=True, + ) + image_paths = cast(List[str], _image_paths) figure_number = 0 for el in elements: @@ -124,9 +143,17 @@ def save_elements( image_path = image_paths[page_number - 1] image = Image.open(image_path) cropped_image = image.crop((x1, y1, x2, y2)) - write_image(cropped_image, output_f_path) - # add image path to element metadata - el.metadata.image_path = output_f_path + if extract_to_payload: + buffered = BytesIO() + cropped_image.save(buffered, format="JPEG") + img_base64 = base64.b64encode(buffered.getvalue()) + img_base64_str = img_base64.decode() + el.metadata.image_base64 = img_base64_str + el.metadata.image_mime_type = "image/jpeg" + else: + write_image(cropped_image, output_f_path) + # add image path to element metadata + el.metadata.image_path = output_f_path except (ValueError, IOError): logger.warning("Image Extraction Error: Skipping the failed image", exc_info=True)