docling/docs/examples/custom_convert.py
nuridol 6efa96c983
feat: add support for ocrmac OCR engine on macOS (#276)
* 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>
2024-11-20 12:51:19 +01:00

172 lines
5.9 KiB
Python

import json
import logging
import time
from pathlib import Path
from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
from docling.datamodel.base_models import InputFormat
from docling.datamodel.pipeline_options import PdfPipelineOptions
from docling.document_converter import DocumentConverter, PdfFormatOption
from docling.models.ocr_mac_model import OcrMacOptions
from docling.models.tesseract_ocr_cli_model import TesseractCliOcrOptions
from docling.models.tesseract_ocr_model import TesseractOcrOptions
_log = logging.getLogger(__name__)
def main():
logging.basicConfig(level=logging.INFO)
input_doc_path = Path("./tests/data/2206.01062.pdf")
###########################################################################
# The following sections contain a combination of PipelineOptions
# and PDF Backends for various configurations.
# Uncomment one section at the time to see the differences in the output.
# PyPdfium without EasyOCR
# --------------------
# pipeline_options = PdfPipelineOptions()
# pipeline_options.do_ocr = False
# pipeline_options.do_table_structure = True
# pipeline_options.table_structure_options.do_cell_matching = False
# doc_converter = DocumentConverter(
# format_options={
# InputFormat.PDF: PdfFormatOption(
# pipeline_options=pipeline_options, backend=PyPdfiumDocumentBackend
# )
# }
# )
# PyPdfium with EasyOCR
# -----------------
# pipeline_options = PdfPipelineOptions()
# pipeline_options.do_ocr = True
# pipeline_options.do_table_structure = True
# pipeline_options.table_structure_options.do_cell_matching = True
# doc_converter = DocumentConverter(
# format_options={
# InputFormat.PDF: PdfFormatOption(
# pipeline_options=pipeline_options, backend=PyPdfiumDocumentBackend
# )
# }
# )
# Docling Parse without EasyOCR
# -------------------------
# pipeline_options = PdfPipelineOptions()
# pipeline_options.do_ocr = False
# pipeline_options.do_table_structure = True
# pipeline_options.table_structure_options.do_cell_matching = True
# doc_converter = DocumentConverter(
# format_options={
# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
# }
# )
# Docling Parse with EasyOCR
# ----------------------
pipeline_options = PdfPipelineOptions()
pipeline_options.do_ocr = True
pipeline_options.do_table_structure = True
pipeline_options.table_structure_options.do_cell_matching = True
doc_converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
}
)
# Docling Parse with EasyOCR (CPU only)
# ----------------------
# pipeline_options = PdfPipelineOptions()
# pipeline_options.do_ocr = True
# pipeline_options.ocr_options.use_gpu = False # <-- set this.
# pipeline_options.do_table_structure = True
# pipeline_options.table_structure_options.do_cell_matching = True
# doc_converter = DocumentConverter(
# format_options={
# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
# }
# )
# Docling Parse with Tesseract
# ----------------------
# pipeline_options = PdfPipelineOptions()
# pipeline_options.do_ocr = True
# pipeline_options.do_table_structure = True
# pipeline_options.table_structure_options.do_cell_matching = True
# pipeline_options.ocr_options = TesseractOcrOptions()
# doc_converter = DocumentConverter(
# format_options={
# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
# }
# )
# Docling Parse with Tesseract CLI
# ----------------------
# pipeline_options = PdfPipelineOptions()
# pipeline_options.do_ocr = True
# pipeline_options.do_table_structure = True
# pipeline_options.table_structure_options.do_cell_matching = True
# pipeline_options.ocr_options = TesseractCliOcrOptions()
# doc_converter = DocumentConverter(
# format_options={
# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
# }
# )
# Docling Parse with ocrmac(Mac only)
# ----------------------
# pipeline_options = PdfPipelineOptions()
# pipeline_options.do_ocr = True
# pipeline_options.do_table_structure = True
# pipeline_options.table_structure_options.do_cell_matching = True
# pipeline_options.ocr_options = OcrMacOptions()
# doc_converter = DocumentConverter(
# format_options={
# InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
# }
# )
###########################################################################
start_time = time.time()
conv_result = doc_converter.convert(input_doc_path)
end_time = time.time() - start_time
_log.info(f"Document converted in {end_time:.2f} seconds.")
## Export results
output_dir = Path("scratch")
output_dir.mkdir(parents=True, exist_ok=True)
doc_filename = conv_result.input.file.stem
# Export Deep Search document JSON format:
with (output_dir / f"{doc_filename}.json").open("w", encoding="utf-8") as fp:
fp.write(json.dumps(conv_result.document.export_to_dict()))
# Export Text format:
with (output_dir / f"{doc_filename}.txt").open("w", encoding="utf-8") as fp:
fp.write(conv_result.document.export_to_text())
# Export Markdown format:
with (output_dir / f"{doc_filename}.md").open("w", encoding="utf-8") as fp:
fp.write(conv_result.document.export_to_markdown())
# Export Document Tags format:
with (output_dir / f"{doc_filename}.doctags").open("w", encoding="utf-8") as fp:
fp.write(conv_result.document.export_to_document_tokens())
if __name__ == "__main__":
main()