Files
DB-GPT/pilot/source_embedding/pdf_loader.py
2023-06-25 15:32:41 +08:00

56 lines
2.1 KiB
Python

"""Loader that loads image files."""
import os
from typing import List
import fitz
from langchain.document_loaders.unstructured import UnstructuredFileLoader
from paddleocr import PaddleOCR
class UnstructuredPaddlePDFLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load image files, such as PNGs and JPGs."""
def _get_elements(self) -> List:
def pdf_ocr_txt(filepath, dir_path="tmp_files"):
full_dir_path = os.path.join(os.path.dirname(filepath), dir_path)
if not os.path.exists(full_dir_path):
os.makedirs(full_dir_path)
filename = os.path.split(filepath)[-1]
ocr = PaddleOCR(lang="ch", use_gpu=False, show_log=False)
doc = fitz.open(filepath)
txt_file_path = os.path.join(full_dir_path, "%s.txt" % (filename))
img_name = os.path.join(full_dir_path, ".tmp.png")
with open(txt_file_path, "w", encoding="utf-8") as fout:
for i in range(doc.page_count):
page = doc[i]
text = page.get_text("")
fout.write(text)
fout.write("\n")
img_list = page.get_images()
for img in img_list:
pix = fitz.Pixmap(doc, img[0])
pix.save(img_name)
result = ocr.ocr(img_name)
ocr_result = [i[1][0] for line in result for i in line]
fout.write("\n".join(ocr_result))
os.remove(img_name)
return txt_file_path
txt_file_path = pdf_ocr_txt(self.file_path)
from unstructured.partition.text import partition_text
return partition_text(filename=txt_file_path, **self.unstructured_kwargs)
if __name__ == "__main__":
filepath = os.path.join(
os.path.dirname(os.path.dirname(__file__)), "content", "samples", "test_py.pdf"
)
loader = UnstructuredPaddlePDFLoader(filepath, mode="elements")
docs = loader.load()
for doc in docs:
print(doc)