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docs: Introduce example with custom models for RapidOCR
Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>
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docs/examples/rapidocr_with_custom_models.py
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58
docs/examples/rapidocr_with_custom_models.py
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import os
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from huggingface_hub import snapshot_download
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from docling.datamodel.pipeline_options import PdfPipelineOptions, RapidOcrOptions
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from docling.document_converter import (
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ConversionResult,
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DocumentConverter,
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InputFormat,
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PdfFormatOption,
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)
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def main():
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# Source document to convert
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source = "https://arxiv.org/pdf/2408.09869v4"
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# Download RappidOCR models from HuggingFace
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print("Downloading RapidOCR models")
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download_path = snapshot_download(repo_id="SWHL/RapidOCR")
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# Setup RapidOcrOptions for english detection
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det_model_path = os.path.join(
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download_path, "PP-OCRv4", "en_PP-OCRv3_det_infer.onnx"
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)
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rec_model_path = os.path.join(
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download_path, "PP-OCRv4", "ch_PP-OCRv4_rec_server_infer.onnx"
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)
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cls_model_path = os.path.join(
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download_path, "PP-OCRv3", "ch_ppocr_mobile_v2.0_cls_train.onnx"
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)
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ocr_options = RapidOcrOptions(
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det_model_path=det_model_path,
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rec_model_path=rec_model_path,
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cls_model_path=cls_model_path,
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)
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pipeline_options = PdfPipelineOptions(
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ocr_options=ocr_options,
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)
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# Convert the document
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converter = DocumentConverter(
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format_options={
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InputFormat.PDF: PdfFormatOption(
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pipeline_options=pipeline_options,
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),
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},
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)
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conversion_result: ConversionResult = converter.convert(source=source)
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doc = conversion_result.document
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md = doc.export_to_markdown()
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print(md)
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if __name__ == "__main__":
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main()
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@ -77,6 +77,7 @@ nav:
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- "Multimodal export": examples/export_multimodal.py
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- "Force full page OCR": examples/full_page_ocr.py
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- "Automatic OCR language detection with tesseract": examples/tesseract_lang_detection.py
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- "RapidOCR with custom OCR models": examples/rapidocr_with_custom_models.py
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- "Accelerator options": examples/run_with_accelerator.py
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- "Simple translation": examples/translate.py
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- examples/backend_xml_rag.ipynb
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