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import copy
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import re
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from io import BytesIO
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from pptx import Presentation
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from deepdoc.parser import tokenize, is_english
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from rag.nlp import huqie
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from deepdoc.parser import PdfParser
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class Ppt(object):
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def __init__(self):
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super().__init__()
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def __extract(self, shape):
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if shape.shape_type == 19:
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tb = shape.table
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rows = []
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for i in range(1, len(tb.rows)):
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rows.append("; ".join([tb.cell(0, j).text + ": " + tb.cell(i, j).text for j in range(len(tb.columns)) if tb.cell(i, j)]))
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return "\n".join(rows)
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if shape.has_text_frame:
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return shape.text_frame.text
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if shape.shape_type == 6:
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texts = []
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for p in shape.shapes:
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t = self.__extract(p)
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if t: texts.append(t)
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return "\n".join(texts)
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def __call__(self, fnm, from_page, to_page, callback=None):
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ppt = Presentation(fnm) if isinstance(
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fnm, str) else Presentation(
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BytesIO(fnm))
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txts = []
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self.total_page = len(ppt.slides)
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for i, slide in enumerate(ppt.slides[from_page: to_page]):
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texts = []
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for shape in slide.shapes:
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txt = self.__extract(shape)
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if txt: texts.append(txt)
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txts.append("\n".join(texts))
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callback(0.5, "Text extraction finished.")
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import aspose.slides as slides
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import aspose.pydrawing as drawing
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imgs = []
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with slides.Presentation(BytesIO(fnm)) as presentation:
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for i, slide in enumerate(presentation.slides[from_page: to_page]):
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buffered = BytesIO()
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slide.get_thumbnail(0.5, 0.5).save(buffered, drawing.imaging.ImageFormat.jpeg)
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imgs.append(buffered.getvalue())
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assert len(imgs) == len(txts), "Slides text and image do not match: {} vs. {}".format(len(imgs), len(txts))
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callback(0.9, "Image extraction finished")
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self.is_english = is_english(txts)
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return [(txts[i], imgs[i]) for i in range(len(txts))]
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class Pdf(PdfParser):
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def __init__(self):
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super().__init__()
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def __garbage(self, txt):
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txt = txt.lower().strip()
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if re.match(r"[0-9\.,%/-]+$", txt): return True
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if len(txt) < 3:return True
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return False
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def __call__(self, filename, binary=None, from_page=0, to_page=100000, zoomin=3, callback=None):
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self.__images__(filename if not binary else binary, zoomin, from_page, to_page)
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callback(0.8, "Page {}~{}: OCR finished".format(from_page, min(to_page, self.total_page)))
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assert len(self.boxes) == len(self.page_images), "{} vs. {}".format(len(self.boxes), len(self.page_images))
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res = []
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for i in range(len(self.boxes)):
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lines = "\n".join([b["text"] for b in self.boxes[i] if not self.__garbage(b["text"])])
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res.append((lines, self.page_images[i]))
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callback(0.9, "Page {}~{}: Parsing finished".format(from_page, min(to_page, self.total_page)))
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return res
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def chunk(filename, binary=None, from_page=0, to_page=100000, callback=None, **kwargs):
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"""
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The supported file formats are pdf, pptx.
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Every page will be treated as a chunk. And the thumbnail of every page will be stored.
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PPT file will be parsed by using this method automatically, setting-up for every PPT file is not necessary.
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"""
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doc = {
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"docnm_kwd": filename,
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"title_tks": huqie.qie(re.sub(r"\.[a-zA-Z]+$", "", filename))
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}
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doc["title_sm_tks"] = huqie.qieqie(doc["title_tks"])
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res = []
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if re.search(r"\.pptx?$", filename, re.IGNORECASE):
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ppt_parser = Ppt()
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for txt,img in ppt_parser(filename if not binary else binary, from_page, 1000000, callback):
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d = copy.deepcopy(doc)
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d["image"] = img
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tokenize(d, txt, ppt_parser.is_english)
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res.append(d)
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return res
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elif re.search(r"\.pdf$", filename, re.IGNORECASE):
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pdf_parser = Pdf()
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for txt,img in pdf_parser(filename if not binary else binary, from_page=from_page, to_page=to_page, callback=callback):
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d = copy.deepcopy(doc)
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d["image"] = img
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tokenize(d, txt, pdf_parser.is_english)
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res.append(d)
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return res
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raise NotImplementedError("file type not supported yet(pptx, pdf supported)")
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if __name__== "__main__":
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import sys
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def dummy(a, b):
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pass
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chunk(sys.argv[1], callback=dummy)
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