File size: 4,728 Bytes
96a1a44 f666f56 7d85666 cdba7f7 96a1a44 cdba7f7 f666f56 96a1a44 7d85666 64a0633 96a1a44 b83edb4 279ca43 7d85666 96a1a44 cdba7f7 b83edb4 96a1a44 b83edb4 96a1a44 7d85666 08bab63 96a1a44 b83edb4 96a1a44 7d85666 08bab63 7d85666 89444d3 7d85666 96a1a44 41c7a59 a8294f2 96a1a44 7d85666 96a1a44 6224edc 96a1a44 41c7a59 96a1a44 7d85666 96a1a44 7d85666 64a0633 96a1a44 7d85666 96a1a44 7d85666 96a1a44 7d85666 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 |
import copy
import re
from api.db import ParserType
from rag.nlp import huqie, tokenize, tokenize_table, add_positions, bullets_category, title_frequency
from deepdoc.parser import PdfParser
from rag.utils import num_tokens_from_string
class Pdf(PdfParser):
def __init__(self):
self.model_speciess = ParserType.MANUAL.value
super().__init__()
def __call__(self, filename, binary=None, from_page=0,
to_page=100000, zoomin=3, callback=None):
from timeit import default_timer as timer
start = timer()
callback(msg="OCR is running...")
self.__images__(
filename if not binary else binary,
zoomin,
from_page,
to_page,
callback
)
callback(msg="OCR finished.")
#for bb in self.boxes:
# for b in bb:
# print(b)
print("OCR:", timer()-start)
def tag(pn, left, right, top, bottom):
return "@@{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}##" \
.format(pn, left, right, top, bottom)
self._layouts_rec(zoomin)
callback(0.65, "Layout analysis finished.")
print("paddle layouts:", timer() - start)
self._table_transformer_job(zoomin)
callback(0.67, "Table analysis finished.")
self._text_merge()
tbls = self._extract_table_figure(True, zoomin, True, True)
self._concat_downward()
self._filter_forpages()
callback(0.68, "Text merging finished")
# clean mess
for b in self.boxes:
b["text"] = re.sub(r"([\t ]|\u3000){2,}", " ", b["text"].strip())
# set pivot using the most frequent type of title,
# then merge between 2 pivot
bull = bullets_category([b["text"] for b in self.boxes])
most_level, levels = title_frequency(bull, [(b["text"], b.get("layout_no","")) for b in self.boxes])
assert len(self.boxes) == len(levels)
sec_ids = []
sid = 0
for i, lvl in enumerate(levels):
if lvl <= most_level: sid += 1
sec_ids.append(sid)
#print(lvl, self.boxes[i]["text"], most_level)
sections = [(b["text"], sec_ids[i], self.get_position(b, zoomin)) for i, b in enumerate(self.boxes)]
for (img, rows), poss in tbls:
sections.append((rows if isinstance(rows, str) else rows[0], -1, [(p[0]+1-from_page, p[1], p[2], p[3], p[4]) for p in poss]))
chunks = []
last_sid = -2
for txt, sec_id, poss in sorted(sections, key=lambda x: (x[-1][0][0], x[-1][0][3], x[-1][0][1])):
poss = "\t".join([tag(*pos) for pos in poss])
if sec_id == last_sid or sec_id == -1:
if chunks:
chunks[-1] += "\n" + txt + poss
continue
chunks.append(txt + poss)
if sec_id >-1: last_sid = sec_id
return chunks
def chunk(filename, binary=None, from_page=0, to_page=100000, lang="Chinese", callback=None, **kwargs):
"""
Only pdf is supported.
"""
pdf_parser = None
if re.search(r"\.pdf$", filename, re.IGNORECASE):
pdf_parser = Pdf()
cks = pdf_parser(filename if not binary else binary,
from_page=from_page, to_page=to_page, callback=callback)
else: raise NotImplementedError("file type not supported yet(pdf supported)")
doc = {
"docnm_kwd": filename
}
doc["title_tks"] = huqie.qie(re.sub(r"\.[a-zA-Z]+$", "", doc["docnm_kwd"]))
doc["title_sm_tks"] = huqie.qieqie(doc["title_tks"])
# is it English
eng = lang.lower() == "english"#pdf_parser.is_english
i = 0
chunk = []
tk_cnt = 0
res = []
def add_chunk():
nonlocal chunk, res, doc, pdf_parser, tk_cnt
d = copy.deepcopy(doc)
ck = "\n".join(chunk)
tokenize(d, pdf_parser.remove_tag(ck), eng)
d["image"], poss = pdf_parser.crop(ck, need_position=True)
add_positions(d, poss)
res.append(d)
chunk = []
tk_cnt = 0
while i < len(cks):
if tk_cnt > 256: add_chunk()
txt = cks[i]
txt_ = pdf_parser.remove_tag(txt)
i += 1
cnt = num_tokens_from_string(txt_)
chunk.append(txt)
tk_cnt += cnt
if chunk: add_chunk()
for i, d in enumerate(res):
print(d)
# d["image"].save(f"./logs/{i}.jpg")
return res
if __name__ == "__main__":
import sys
def dummy(prog=None, msg=""):
pass
chunk(sys.argv[1], callback=dummy)
|