38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
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from typing import List
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from langchain.document_loaders.unstructured import UnstructuredFileLoader
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class RapidOCRPDFLoader(UnstructuredFileLoader):
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def _get_elements(self) -> List:
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def pdf2text(filepath):
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import fitz
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from rapidocr_onnxruntime import RapidOCR
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import numpy as np
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ocr = RapidOCR()
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doc = fitz.open(filepath)
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resp = ""
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for page in doc:
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# TODO: 依据文本与图片顺序调整处理方式
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text = page.get_text("")
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resp += text + "\n"
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img_list = page.get_images()
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for img in img_list:
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pix = fitz.Pixmap(doc, img[0])
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img_array = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.height, pix.width, -1)
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result, _ = ocr(img_array)
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if result:
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ocr_result = [line[1] for line in result]
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resp += "\n".join(ocr_result)
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return resp
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text = pdf2text(self.file_path)
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from unstructured.partition.text import partition_text
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return partition_text(text=text, **self.unstructured_kwargs)
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if __name__ == "__main__":
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loader = RapidOCRPDFLoader(file_path="../tests/samples/ocr_test.pdf")
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docs = loader.load()
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print(docs)
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