Docling/tests/test_e2e_ocr_conversion.py
Michele Dolfi f96ea86a00
feat: add options for choosing OCR engines (#118)
---------

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>
Signed-off-by: Peter Staar <taa@zurich.ibm.com>
Co-authored-by: Nikos Livathinos <nli@zurich.ibm.com>
Co-authored-by: Peter Staar <taa@zurich.ibm.com>
2024-10-08 19:07:08 +02:00

99 lines
2.8 KiB
Python

from pathlib import Path
from typing import List
from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
from docling.datamodel.document import ConversionResult
from docling.datamodel.pipeline_options import (
EasyOcrOptions,
OcrOptions,
PipelineOptions,
TesseractCliOcrOptions,
TesseractOcrOptions,
)
from docling.document_converter import DocumentConverter
from .verify_utils import verify_conversion_result
GENERATE = False
# Debug
def save_output(pdf_path: Path, doc_result: ConversionResult, engine: str):
r""" """
import json
import os
parent = pdf_path.parent
eng = "" if engine is None else f".{engine}"
dict_fn = os.path.join(parent, f"{pdf_path.stem}{eng}.json")
with open(dict_fn, "w") as fd:
json.dump(doc_result.render_as_dict(), fd)
pages_fn = os.path.join(parent, f"{pdf_path.stem}{eng}.pages.json")
pages = [p.model_dump() for p in doc_result.pages]
with open(pages_fn, "w") as fd:
json.dump(pages, fd)
doctags_fn = os.path.join(parent, f"{pdf_path.stem}{eng}.doctags.txt")
with open(doctags_fn, "w") as fd:
fd.write(doc_result.render_as_doctags())
md_fn = os.path.join(parent, f"{pdf_path.stem}{eng}.md")
with open(md_fn, "w") as fd:
fd.write(doc_result.render_as_markdown())
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 = PipelineOptions()
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(
pipeline_options=pipeline_options,
pdf_backend=DoclingParseDocumentBackend,
)
return converter
def test_e2e_conversions():
pdf_paths = get_pdf_paths()
engines: List[OcrOptions] = [
EasyOcrOptions(),
TesseractOcrOptions(),
TesseractCliOcrOptions(),
]
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_single(pdf_path)
# Save conversions
# save_output(pdf_path, doc_result, None)
# Debug
verify_conversion_result(
input_path=pdf_path,
doc_result=doc_result,
generate=GENERATE,
skip_cells=True,
)