docling/tests/test_e2e_ocr_conversion.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

90 lines
2.6 KiB
Python

import sys
from pathlib import Path
from typing import List
from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
from docling.datamodel.base_models import InputFormat
from docling.datamodel.document import ConversionResult
from docling.datamodel.pipeline_options import (
EasyOcrOptions,
OcrMacOptions,
OcrOptions,
PdfPipelineOptions,
TesseractCliOcrOptions,
TesseractOcrOptions,
)
from docling.document_converter import DocumentConverter, PdfFormatOption
from .verify_utils import verify_conversion_result_v1, verify_conversion_result_v2
GENERATE_V1 = False
GENERATE_V2 = False
def get_pdf_paths():
# Define the directory you want to search
directory = Path("./tests/data_scanned")
# List all PDF files in the directory and its subdirectories
pdf_files = sorted(directory.rglob("*.pdf"))
return pdf_files
def get_converter(ocr_options: OcrOptions):
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 = ocr_options
converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(
pipeline_options=pipeline_options,
backend=DoclingParseDocumentBackend,
)
}
)
return converter
def test_e2e_conversions():
pdf_paths = get_pdf_paths()
engines: List[OcrOptions] = [
EasyOcrOptions(),
TesseractOcrOptions(),
TesseractCliOcrOptions(),
EasyOcrOptions(force_full_page_ocr=True),
TesseractOcrOptions(force_full_page_ocr=True),
TesseractCliOcrOptions(force_full_page_ocr=True),
]
# only works on mac
if "darwin" == sys.platform:
engines.append(OcrMacOptions())
engines.append(OcrMacOptions(force_full_page_ocr=True))
for ocr_options in engines:
print(f"Converting with ocr_engine: {ocr_options.kind}")
converter = get_converter(ocr_options=ocr_options)
for pdf_path in pdf_paths:
print(f"converting {pdf_path}")
doc_result: ConversionResult = converter.convert(pdf_path)
verify_conversion_result_v1(
input_path=pdf_path,
doc_result=doc_result,
generate=GENERATE_V1,
fuzzy=True,
)
verify_conversion_result_v2(
input_path=pdf_path,
doc_result=doc_result,
generate=GENERATE_V2,
fuzzy=True,
)