docling/docs/examples/rapidocr_with_custom_models.py
Nikos Livathinos 6d3fea0196
docs: Introduce example with custom models for RapidOCR (#874)
* docs: Introduce example with custom models for RapidOCR

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* chore: Exclude the example with custom RapidOCR models from the examples to run in github actions

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

---------

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>
2025-02-04 10:07:00 +01:00

59 lines
1.5 KiB
Python

import os
from huggingface_hub import snapshot_download
from docling.datamodel.pipeline_options import PdfPipelineOptions, RapidOcrOptions
from docling.document_converter import (
ConversionResult,
DocumentConverter,
InputFormat,
PdfFormatOption,
)
def main():
# Source document to convert
source = "https://arxiv.org/pdf/2408.09869v4"
# Download RappidOCR models from HuggingFace
print("Downloading RapidOCR models")
download_path = snapshot_download(repo_id="SWHL/RapidOCR")
# Setup RapidOcrOptions for english detection
det_model_path = os.path.join(
download_path, "PP-OCRv4", "en_PP-OCRv3_det_infer.onnx"
)
rec_model_path = os.path.join(
download_path, "PP-OCRv4", "ch_PP-OCRv4_rec_server_infer.onnx"
)
cls_model_path = os.path.join(
download_path, "PP-OCRv3", "ch_ppocr_mobile_v2.0_cls_train.onnx"
)
ocr_options = RapidOcrOptions(
det_model_path=det_model_path,
rec_model_path=rec_model_path,
cls_model_path=cls_model_path,
)
pipeline_options = PdfPipelineOptions(
ocr_options=ocr_options,
)
# Convert the document
converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(
pipeline_options=pipeline_options,
),
},
)
conversion_result: ConversionResult = converter.convert(source=source)
doc = conversion_result.document
md = doc.export_to_markdown()
print(md)
if __name__ == "__main__":
main()