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* feat: add support for `ocrmac` OCR engine on macOS - Integrates `ocrmac` as an OCR engine option for macOS users. - Adds configuration options and dependencies for `ocrmac`. - Updates documentation to reflect new engine support. This change allows macOS users to utilize `ocrmac` for improved OCR performance and compatibility. Signed-off-by: Suhwan Seo <nuridol@gmail.com> * updated the poetry lock Signed-off-by: Suhwan Seo <nuridol@gmail.com> * Fix linting issues, update CLI docs, and add error for ocrmac use on non-Mac systems - Resolved formatting and linting issues - Updated `--ocr-engine` CLI option documentation for `ocrmac` - Added RuntimeError for attempts to use `ocrmac` on non-Mac platforms Signed-off-by: Suhwan Seo <nuridol@gmail.com> * feat: add support for `ocrmac` OCR engine on macOS - Integrates `ocrmac` as an OCR engine option for macOS users. - Adds configuration options and dependencies for `ocrmac`. - Updates documentation to reflect new engine support. This change allows macOS users to utilize `ocrmac` for improved OCR performance and compatibility. Signed-off-by: Suhwan Seo <nuridol@gmail.com> * docs: update examples and installation for ocrmac support - Added `OcrMacOptions` to `custom_convert.py` and `full_page_ocr.py` examples. - Included usage comments and examples for `OcrMacOptions` in OCR pipelines. - Updated installation guide to include instructions for installing `ocrmac`, noting macOS version requirements (10.15+). - Highlighted that `ocrmac` leverages Apple's Vision framework as an OCR backend. This enhances documentation for users working on macOS to leverage `ocrmac` effectively. Signed-off-by: Suhwan Seo <nuridol@gmail.com> * fix: update `ocrmac` dependency with macOS-specific marker - Added `sys_platform == 'darwin'` marker to the `ocrmac` dependency in `pyproject.toml` to specify macOS compatibility. - Updated the content hash in `poetry.lock` to reflect the changes. This ensures the `ocrmac` dependency is only installed on macOS systems. Signed-off-by: Suhwan Seo <nuridol@gmail.com> --------- Signed-off-by: Suhwan Seo <nuridol@gmail.com> Co-authored-by: Suhwan Seo <nuridol@gmail.com>
172 lines
5.9 KiB
Python
172 lines
5.9 KiB
Python
import json
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import logging
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import time
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from pathlib import Path
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from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
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from docling.datamodel.base_models import InputFormat
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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.models.ocr_mac_model import OcrMacOptions
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from docling.models.tesseract_ocr_cli_model import TesseractCliOcrOptions
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from docling.models.tesseract_ocr_model import TesseractOcrOptions
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_log = logging.getLogger(__name__)
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def main():
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logging.basicConfig(level=logging.INFO)
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input_doc_path = Path("./tests/data/2206.01062.pdf")
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###########################################################################
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# The following sections contain a combination of PipelineOptions
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# and PDF Backends for various configurations.
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# Uncomment one section at the time to see the differences in the output.
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# PyPdfium without EasyOCR
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# --------------------
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# pipeline_options = PdfPipelineOptions()
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# pipeline_options.do_ocr = False
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# pipeline_options.do_table_structure = True
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# pipeline_options.table_structure_options.do_cell_matching = False
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# doc_converter = DocumentConverter(
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# format_options={
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# InputFormat.PDF: PdfFormatOption(
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# pipeline_options=pipeline_options, backend=PyPdfiumDocumentBackend
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# )
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# }
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# )
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# PyPdfium with EasyOCR
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# -----------------
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# pipeline_options = PdfPipelineOptions()
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# pipeline_options.do_ocr = True
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# pipeline_options.do_table_structure = True
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# pipeline_options.table_structure_options.do_cell_matching = True
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# doc_converter = DocumentConverter(
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# format_options={
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# InputFormat.PDF: PdfFormatOption(
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# pipeline_options=pipeline_options, backend=PyPdfiumDocumentBackend
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# )
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# }
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# )
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# Docling Parse without EasyOCR
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# -------------------------
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# pipeline_options = PdfPipelineOptions()
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# pipeline_options.do_ocr = False
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# pipeline_options.do_table_structure = True
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# pipeline_options.table_structure_options.do_cell_matching = True
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# doc_converter = DocumentConverter(
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# format_options={
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# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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# }
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# )
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# Docling Parse with EasyOCR
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# ----------------------
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pipeline_options = PdfPipelineOptions()
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pipeline_options.do_ocr = True
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pipeline_options.do_table_structure = True
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pipeline_options.table_structure_options.do_cell_matching = True
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doc_converter = DocumentConverter(
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format_options={
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InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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}
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)
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# Docling Parse with EasyOCR (CPU only)
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# ----------------------
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# pipeline_options = PdfPipelineOptions()
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# pipeline_options.do_ocr = True
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# pipeline_options.ocr_options.use_gpu = False # <-- set this.
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# pipeline_options.do_table_structure = True
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# pipeline_options.table_structure_options.do_cell_matching = True
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# doc_converter = DocumentConverter(
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# format_options={
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# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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# }
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# )
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# Docling Parse with Tesseract
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# ----------------------
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# pipeline_options = PdfPipelineOptions()
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# pipeline_options.do_ocr = True
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# pipeline_options.do_table_structure = True
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# pipeline_options.table_structure_options.do_cell_matching = True
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# pipeline_options.ocr_options = TesseractOcrOptions()
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# doc_converter = DocumentConverter(
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# format_options={
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# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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# }
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# )
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# Docling Parse with Tesseract CLI
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# ----------------------
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# pipeline_options = PdfPipelineOptions()
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# pipeline_options.do_ocr = True
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# pipeline_options.do_table_structure = True
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# pipeline_options.table_structure_options.do_cell_matching = True
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# pipeline_options.ocr_options = TesseractCliOcrOptions()
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# doc_converter = DocumentConverter(
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# format_options={
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# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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# }
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# )
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# Docling Parse with ocrmac(Mac only)
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# ----------------------
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# pipeline_options = PdfPipelineOptions()
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# pipeline_options.do_ocr = True
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# pipeline_options.do_table_structure = True
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# pipeline_options.table_structure_options.do_cell_matching = True
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# pipeline_options.ocr_options = OcrMacOptions()
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# doc_converter = DocumentConverter(
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# format_options={
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# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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# }
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# )
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###########################################################################
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start_time = time.time()
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conv_result = doc_converter.convert(input_doc_path)
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end_time = time.time() - start_time
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_log.info(f"Document converted in {end_time:.2f} seconds.")
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## Export results
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output_dir = Path("scratch")
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output_dir.mkdir(parents=True, exist_ok=True)
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doc_filename = conv_result.input.file.stem
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# Export Deep Search document JSON format:
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with (output_dir / f"{doc_filename}.json").open("w", encoding="utf-8") as fp:
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fp.write(json.dumps(conv_result.document.export_to_dict()))
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# Export Text format:
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with (output_dir / f"{doc_filename}.txt").open("w", encoding="utf-8") as fp:
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fp.write(conv_result.document.export_to_text())
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# Export Markdown format:
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with (output_dir / f"{doc_filename}.md").open("w", encoding="utf-8") as fp:
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fp.write(conv_result.document.export_to_markdown())
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# Export Document Tags format:
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with (output_dir / f"{doc_filename}.doctags").open("w", encoding="utf-8") as fp:
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fp.write(conv_result.document.export_to_document_tokens())
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if __name__ == "__main__":
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main()
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