File size: 5,274 Bytes
cdba7f7 e6acaf6 b085dec 41c7a59 b085dec e6acaf6 b085dec e6acaf6 cdba7f7 e6acaf6 64a0633 e6acaf6 b83edb4 279ca43 e6acaf6 cdba7f7 b83edb4 e6acaf6 b83edb4 e6acaf6 79ada0b e6acaf6 79ada0b a8294f2 e6acaf6 79ada0b e6acaf6 cdba7f7 e6acaf6 79ada0b e6acaf6 b085dec e6acaf6 79ada0b 64a0633 79ada0b b085dec e6acaf6 79ada0b e6acaf6 79ada0b e6acaf6 407b252 79ada0b e6acaf6 b085dec 79ada0b e6acaf6 51482f3 79ada0b b085dec 79ada0b bcb7249 79ada0b e6acaf6 79ada0b bcb7249 b085dec e6acaf6 79ada0b b83edb4 51482f3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 |
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import copy
import re
from io import BytesIO
from rag.nlp import bullets_category, is_english, tokenize, remove_contents_table, \
hierarchical_merge, make_colon_as_title, naive_merge, random_choices, tokenize_table, add_positions, tokenize_chunks
from rag.nlp import huqie
from deepdoc.parser import PdfParser, DocxParser, PlainParser
class Pdf(PdfParser):
def __call__(self, filename, binary=None, from_page=0,
to_page=100000, zoomin=3, callback=None):
callback(msg="OCR is running...")
self.__images__(
filename if not binary else binary,
zoomin,
from_page,
to_page,
callback)
callback(msg="OCR finished")
from timeit import default_timer as timer
start = timer()
self._layouts_rec(zoomin)
callback(0.67, "Layout analysis finished")
print("paddle layouts:", timer() - start)
self._table_transformer_job(zoomin)
callback(0.68, "Table analysis finished")
self._text_merge()
tbls = self._extract_table_figure(True, zoomin, True, True)
self._naive_vertical_merge()
self._filter_forpages()
self._merge_with_same_bullet()
callback(0.75, "Text merging finished.")
callback(0.8, "Text extraction finished")
return [(b["text"] + self._line_tag(b, zoomin), b.get("layoutno", ""))
for b in self.boxes], tbls
def chunk(filename, binary=None, from_page=0, to_page=100000,
lang="Chinese", callback=None, **kwargs):
"""
Supported file formats are docx, pdf, txt.
Since a book is long and not all the parts are useful, if it's a PDF,
please setup the page ranges for every book in order eliminate negative effects and save elapsed computing time.
"""
doc = {
"docnm_kwd": filename,
"title_tks": huqie.qie(re.sub(r"\.[a-zA-Z]+$", "", filename))
}
doc["title_sm_tks"] = huqie.qieqie(doc["title_tks"])
pdf_parser = None
sections, tbls = [], []
if re.search(r"\.docx?$", filename, re.IGNORECASE):
callback(0.1, "Start to parse.")
doc_parser = DocxParser()
# TODO: table of contents need to be removed
sections, tbls = doc_parser(
binary if binary else filename, from_page=from_page, to_page=to_page)
remove_contents_table(sections, eng=is_english(
random_choices([t for t, _ in sections], k=200)))
callback(0.8, "Finish parsing.")
elif re.search(r"\.pdf$", filename, re.IGNORECASE):
pdf_parser = Pdf() if kwargs.get(
"parser_config", {}).get(
"layout_recognize", True) else PlainParser()
sections, tbls = pdf_parser(filename if not binary else binary,
from_page=from_page, to_page=to_page, callback=callback)
elif re.search(r"\.txt$", filename, re.IGNORECASE):
callback(0.1, "Start to parse.")
txt = ""
if binary:
txt = binary.decode("utf-8")
else:
with open(filename, "r") as f:
while True:
l = f.readline()
if not l:
break
txt += l
sections = txt.split("\n")
sections = [(l, "") for l in sections if l]
remove_contents_table(sections, eng=is_english(
random_choices([t for t, _ in sections], k=200)))
callback(0.8, "Finish parsing.")
else:
raise NotImplementedError(
"file type not supported yet(docx, pdf, txt supported)")
make_colon_as_title(sections)
bull = bullets_category(
[t for t in random_choices([t for t, _ in sections], k=100)])
if bull >= 0:
chunks = ["\n".join(ck)
for ck in hierarchical_merge(bull, sections, 3)]
else:
sections = [s.split("@") for s, _ in sections]
sections = [(pr[0], "@" + pr[1]) for pr in sections if len(pr) == 2]
chunks = naive_merge(
sections, kwargs.get(
"chunk_token_num", 256), kwargs.get(
"delimer", "\n。;!?"))
# is it English
# is_english(random_choices([t for t, _ in sections], k=218))
eng = lang.lower() == "english"
res = tokenize_table(tbls, doc, eng)
res.extend(tokenize_chunks(chunks, doc, eng, pdf_parser))
return res
if __name__ == "__main__":
import sys
def dummy(prog=None, msg=""):
pass
chunk(sys.argv[1], from_page=1, to_page=10, callback=dummy)
|