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* Update .py examples with clearer guidance, update out of date imports and calls Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com> * Fix minimal.py string error, fix ruff format error Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com> * fix more CI issues Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com> --------- Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com>
80 lines
2.6 KiB
Python
Vendored
80 lines
2.6 KiB
Python
Vendored
# %% [markdown]
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# Use RapidOCR with custom ONNX models to OCR a PDF page and print Markdown.
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#
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# What this example does
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# - Downloads RapidOCR models from Hugging Face via ModelScope.
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# - Configures `RapidOcrOptions` with explicit det/rec/cls model paths.
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# - Runs the PDF pipeline with RapidOCR and prints Markdown output.
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#
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# Prerequisites
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# - Install Docling, `modelscope`, and have network access to download models.
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# - Ensure your environment can import `docling` and `modelscope`.
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#
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# How to run
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# - From the repo root: `python docs/examples/rapidocr_with_custom_models.py`.
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# - The script prints the recognized text as Markdown to stdout.
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#
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# Notes
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# - The default `source` points to an arXiv PDF URL; replace with a local path if desired.
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# - Model paths are derived from the downloaded snapshot directory.
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# - ModelScope caches downloads (typically under `~/.cache/modelscope`); set a proxy
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# or pre-download models if running in a restricted network environment.
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# %%
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import os
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from modelscope import snapshot_download
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.document import ConversionResult
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from docling.datamodel.pipeline_options import PdfPipelineOptions, RapidOcrOptions
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from docling.document_converter import DocumentConverter, PdfFormatOption
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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 RapidOCR models from Hugging Face
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print("Downloading RapidOCR models")
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download_path = snapshot_download(repo_id="RapidAI/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, "onnx", "PP-OCRv5", "det", "ch_PP-OCRv5_server_det.onnx"
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)
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rec_model_path = os.path.join(
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download_path, "onnx", "PP-OCRv5", "rec", "ch_PP-OCRv5_rec_server_infer.onnx"
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)
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cls_model_path = os.path.join(
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download_path, "onnx", "PP-OCRv4", "cls", "ch_ppocr_mobile_v2.0_cls_infer.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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