# 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 logging
import os
import random
import xgboost as xgb
from io import BytesIO
import re
import pdfplumber
from PIL import Image
import numpy as np
from timeit import default_timer as timer
from pypdf import PdfReader as pdf2_read
from api import settings
from api.utils.file_utils import get_project_base_directory
from deepdoc.vision import OCR, Recognizer, LayoutRecognizer, TableStructureRecognizer
from rag.nlp import rag_tokenizer
from copy import deepcopy
from huggingface_hub import snapshot_download
class RAGFlowPdfParser:
def __init__(self):
self.ocr = OCR()
if hasattr(self, "model_speciess"):
self.layouter = LayoutRecognizer("layout." + self.model_speciess)
else:
self.layouter = LayoutRecognizer("layout")
self.tbl_det = TableStructureRecognizer()
self.updown_cnt_mdl = xgb.Booster()
if not settings.LIGHTEN:
try:
import torch
if torch.cuda.is_available():
self.updown_cnt_mdl.set_param({"device": "cuda"})
except Exception:
logging.exception("RAGFlowPdfParser __init__")
try:
model_dir = os.path.join(
get_project_base_directory(),
"rag/res/deepdoc")
self.updown_cnt_mdl.load_model(os.path.join(
model_dir, "updown_concat_xgb.model"))
except Exception:
model_dir = snapshot_download(
repo_id="InfiniFlow/text_concat_xgb_v1.0",
local_dir=os.path.join(get_project_base_directory(), "rag/res/deepdoc"),
local_dir_use_symlinks=False)
self.updown_cnt_mdl.load_model(os.path.join(
model_dir, "updown_concat_xgb.model"))
self.page_from = 0
"""
If you have trouble downloading HuggingFace models, -_^ this might help!!
For Linux:
export HF_ENDPOINT=https://hf-mirror.com
For Windows:
Good luck
^_-
"""
def __char_width(self, c):
return (c["x1"] - c["x0"]) // max(len(c["text"]), 1)
def __height(self, c):
return c["bottom"] - c["top"]
def _x_dis(self, a, b):
return min(abs(a["x1"] - b["x0"]), abs(a["x0"] - b["x1"]),
abs(a["x0"] + a["x1"] - b["x0"] - b["x1"]) / 2)
def _y_dis(
self, a, b):
return (
b["top"] + b["bottom"] - a["top"] - a["bottom"]) / 2
def _match_proj(self, b):
proj_patt = [
r"第[零一二三四五六七八九十百]+章",
r"第[零一二三四五六七八九十百]+[条节]",
r"[零一二三四五六七八九十百]+[、是 ]",
r"[\(（][零一二三四五六七八九十百]+[）\)]",
r"[\(（][0-9]+[）\)]",
r"[0-9]+(、|\.[ ]|）|\.[^0-9./a-zA-Z_%><-]{4,})",
r"[0-9]+\.[0-9.]+(、|\.[ ])",
r"[⚫•➢①② ]",
]
return any([re.match(p, b["text"]) for p in proj_patt])
def _updown_concat_features(self, up, down):
w = max(self.__char_width(up), self.__char_width(down))
h = max(self.__height(up), self.__height(down))
y_dis = self._y_dis(up, down)
LEN = 6
tks_down = rag_tokenizer.tokenize(down["text"][:LEN]).split()
tks_up = rag_tokenizer.tokenize(up["text"][-LEN:]).split()
tks_all = up["text"][-LEN:].strip() \
+ (" " if re.match(r"[a-zA-Z0-9]+",
up["text"][-1] + down["text"][0]) else "") \
+ down["text"][:LEN].strip()
tks_all = rag_tokenizer.tokenize(tks_all).split()
fea = [
up.get("R", -1) == down.get("R", -1),
y_dis / h,
down["page_number"] - up["page_number"],
up["layout_type"] == down["layout_type"],
up["layout_type"] == "text",
down["layout_type"] == "text",
up["layout_type"] == "table",
down["layout_type"] == "table",
True if re.search(
r"([。？！；!?;+)）]|[a-z]\.)$",
up["text"]) else False,
True if re.search(r"[，：‘“、0-9（+-]$", up["text"]) else False,
True if re.search(
r"(^.?[/,?;:\]，。；：’”？！》】）-])",
down["text"]) else False,
True if re.match(r"[\(（][^\(\)（）]+[）\)]$", up["text"]) else False,
True if re.search(r"[，,][^。.]+$", up["text"]) else False,
True if re.search(r"[，,][^。.]+$", up["text"]) else False,
True if re.search(r"[\(（][^\)）]+$", up["text"])
and re.search(r"[\)）]", down["text"]) else False,
self._match_proj(down),
True if re.match(r"[A-Z]", down["text"]) else False,
True if re.match(r"[A-Z]", up["text"][-1]) else False,
True if re.match(r"[a-z0-9]", up["text"][-1]) else False,
True if re.match(r"[0-9.%,-]+$", down["text"]) else False,
up["text"].strip()[-2:] == down["text"].strip()[-2:] if len(up["text"].strip()
) > 1 and len(
down["text"].strip()) > 1 else False,
up["x0"] > down["x1"],
abs(self.__height(up) - self.__height(down)) / min(self.__height(up),
self.__height(down)),
self._x_dis(up, down) / max(w, 0.000001),
(len(up["text"]) - len(down["text"])) /
max(len(up["text"]), len(down["text"])),
len(tks_all) - len(tks_up) - len(tks_down),
len(tks_down) - len(tks_up),
tks_down[-1] == tks_up[-1],
max(down["in_row"], up["in_row"]),
abs(down["in_row"] - up["in_row"]),
len(tks_down) == 1 and rag_tokenizer.tag(tks_down[0]).find("n") >= 0,
len(tks_up) == 1 and rag_tokenizer.tag(tks_up[0]).find("n") >= 0
]
return fea
@staticmethod
def sort_X_by_page(arr, threashold):
# sort using y1 first and then x1
arr = sorted(arr, key=lambda r: (r["page_number"], r["x0"], r["top"]))
for i in range(len(arr) - 1):
for j in range(i, -1, -1):
# restore the order using th
if abs(arr[j + 1]["x0"] - arr[j]["x0"]) < threashold \
and arr[j + 1]["top"] < arr[j]["top"] \
and arr[j + 1]["page_number"] == arr[j]["page_number"]:
tmp = arr[j]
arr[j] = arr[j + 1]
arr[j + 1] = tmp
return arr
def _has_color(self, o):
if o.get("ncs", "") == "DeviceGray":
if o["stroking_color"] and o["stroking_color"][0] == 1 and o["non_stroking_color"] and \
o["non_stroking_color"][0] == 1:
if re.match(r"[a-zT_\[\]\(\)-]+", o.get("text", "")):
return False
return True
def _table_transformer_job(self, ZM):
logging.debug("Table processing...")
imgs, pos = [], []
tbcnt = [0]
MARGIN = 10
self.tb_cpns = []
assert len(self.page_layout) == len(self.page_images)
for p, tbls in enumerate(self.page_layout): # for page
tbls = [f for f in tbls if f["type"] == "table"]
tbcnt.append(len(tbls))
if not tbls:
continue
for tb in tbls: # for table
left, top, right, bott = tb["x0"] - MARGIN, tb["top"] - MARGIN, \
tb["x1"] + MARGIN, tb["bottom"] + MARGIN
left *= ZM
top *= ZM
right *= ZM
bott *= ZM
pos.append((left, top))
imgs.append(self.page_images[p].crop((left, top, right, bott)))
assert len(self.page_images) == len(tbcnt) - 1
if not imgs:
return
recos = self.tbl_det(imgs)
tbcnt = np.cumsum(tbcnt)
for i in range(len(tbcnt) - 1): # for page
pg = []
for j, tb_items in enumerate(
recos[tbcnt[i]: tbcnt[i + 1]]): # for table
poss = pos[tbcnt[i]: tbcnt[i + 1]]
for it in tb_items: # for table components
it["x0"] = (it["x0"] + poss[j][0])
it["x1"] = (it["x1"] + poss[j][0])
it["top"] = (it["top"] + poss[j][1])
it["bottom"] = (it["bottom"] + poss[j][1])
for n in ["x0", "x1", "top", "bottom"]:
it[n] /= ZM
it["top"] += self.page_cum_height[i]
it["bottom"] += self.page_cum_height[i]
it["pn"] = i
it["layoutno"] = j
pg.append(it)
self.tb_cpns.extend(pg)
def gather(kwd, fzy=10, ption=0.6):
eles = Recognizer.sort_Y_firstly(
[r for r in self.tb_cpns if re.match(kwd, r["label"])], fzy)
eles = Recognizer.layouts_cleanup(self.boxes, eles, 5, ption)
return Recognizer.sort_Y_firstly(eles, 0)
# add R,H,C,SP tag to boxes within table layout
headers = gather(r".*header$")
rows = gather(r".* (row|header)")
spans = gather(r".*spanning")
clmns = sorted([r for r in self.tb_cpns if re.match(
r"table column$", r["label"])], key=lambda x: (x["pn"], x["layoutno"], x["x0"]))
clmns = Recognizer.layouts_cleanup(self.boxes, clmns, 5, 0.5)
for b in self.boxes:
if b.get("layout_type", "") != "table":
continue
ii = Recognizer.find_overlapped_with_threashold(b, rows, thr=0.3)
if ii is not None:
b["R"] = ii
b["R_top"] = rows[ii]["top"]
b["R_bott"] = rows[ii]["bottom"]
ii = Recognizer.find_overlapped_with_threashold(
b, headers, thr=0.3)
if ii is not None:
b["H_top"] = headers[ii]["top"]
b["H_bott"] = headers[ii]["bottom"]
b["H_left"] = headers[ii]["x0"]
b["H_right"] = headers[ii]["x1"]
b["H"] = ii
ii = Recognizer.find_horizontally_tightest_fit(b, clmns)
if ii is not None:
b["C"] = ii
b["C_left"] = clmns[ii]["x0"]
b["C_right"] = clmns[ii]["x1"]
ii = Recognizer.find_overlapped_with_threashold(b, spans, thr=0.3)
if ii is not None:
b["H_top"] = spans[ii]["top"]
b["H_bott"] = spans[ii]["bottom"]
b["H_left"] = spans[ii]["x0"]
b["H_right"] = spans[ii]["x1"]
b["SP"] = ii
def __ocr(self, pagenum, img, chars, ZM=3):
bxs = self.ocr.detect(np.array(img))
if not bxs:
self.boxes.append([])
return
bxs = [(line[0], line[1][0]) for line in bxs]
bxs = Recognizer.sort_Y_firstly(
[{"x0": b[0][0] / ZM, "x1": b[1][0] / ZM,
"top": b[0][1] / ZM, "text": "", "txt": t,
"bottom": b[-1][1] / ZM,
"page_number": pagenum} for b, t in bxs if b[0][0] <= b[1][0] and b[0][1] <= b[-1][1]],
self.mean_height[-1] / 3
)
# merge chars in the same rect
for c in Recognizer.sort_Y_firstly(
chars, self.mean_height[pagenum - 1] // 4):
ii = Recognizer.find_overlapped(c, bxs)
if ii is None:
self.lefted_chars.append(c)
continue
ch = c["bottom"] - c["top"]
bh = bxs[ii]["bottom"] - bxs[ii]["top"]
if abs(ch - bh) / max(ch, bh) >= 0.7 and c["text"] != ' ':
self.lefted_chars.append(c)
continue
if c["text"] == " " and bxs[ii]["text"]:
if re.match(r"[0-9a-zA-Zа-яА-Я,.?;:!%%]", bxs[ii]["text"][-1]):
bxs[ii]["text"] += " "
else:
bxs[ii]["text"] += c["text"]
for b in bxs:
if not b["text"]:
left, right, top, bott = b["x0"] * ZM, b["x1"] * \
ZM, b["top"] * ZM, b["bottom"] * ZM
b["text"] = self.ocr.recognize(np.array(img),
np.array([[left, top], [right, top], [right, bott], [left, bott]],
dtype=np.float32))
del b["txt"]
bxs = [b for b in bxs if b["text"]]
if self.mean_height[-1] == 0:
self.mean_height[-1] = np.median([b["bottom"] - b["top"]
for b in bxs])
self.boxes.append(bxs)
def _layouts_rec(self, ZM, drop=True):
assert len(self.page_images) == len(self.boxes)
self.boxes, self.page_layout = self.layouter(
self.page_images, self.boxes, ZM, drop=drop)
# cumlative Y
for i in range(len(self.boxes)):
self.boxes[i]["top"] += \
self.page_cum_height[self.boxes[i]["page_number"] - 1]
self.boxes[i]["bottom"] += \
self.page_cum_height[self.boxes[i]["page_number"] - 1]
def _text_merge(self):
# merge adjusted boxes
bxs = self.boxes
def end_with(b, txt):
txt = txt.strip()
tt = b.get("text", "").strip()
return tt and tt.find(txt) == len(tt) - len(txt)
def start_with(b, txts):
tt = b.get("text", "").strip()
return tt and any([tt.find(t.strip()) == 0 for t in txts])
# horizontally merge adjacent box with the same layout
i = 0
while i < len(bxs) - 1:
b = bxs[i]
b_ = bxs[i + 1]
if b.get("layoutno", "0") != b_.get("layoutno", "1") or b.get("layout_type", "") in ["table", "figure",
"equation"]:
i += 1
continue
if abs(self._y_dis(b, b_)
) < self.mean_height[bxs[i]["page_number"] - 1] / 3:
# merge
bxs[i]["x1"] = b_["x1"]
bxs[i]["top"] = (b["top"] + b_["top"]) / 2
bxs[i]["bottom"] = (b["bottom"] + b_["bottom"]) / 2
bxs[i]["text"] += b_["text"]
bxs.pop(i + 1)
continue
i += 1
continue
dis_thr = 1
dis = b["x1"] - b_["x0"]
if b.get("layout_type", "") != "text" or b_.get(
"layout_type", "") != "text":
if end_with(b, "，") or start_with(b_, "（，"):
dis_thr = -8
else:
i += 1
continue
if abs(self._y_dis(b, b_)) < self.mean_height[bxs[i]["page_number"] - 1] / 5 \
and dis >= dis_thr and b["x1"] < b_["x1"]:
# merge
bxs[i]["x1"] = b_["x1"]
bxs[i]["top"] = (b["top"] + b_["top"]) / 2
bxs[i]["bottom"] = (b["bottom"] + b_["bottom"]) / 2
bxs[i]["text"] += b_["text"]
bxs.pop(i + 1)
continue
i += 1
self.boxes = bxs
def _naive_vertical_merge(self):
bxs = Recognizer.sort_Y_firstly(
self.boxes, np.median(
self.mean_height) / 3)
i = 0
while i + 1 < len(bxs):
b = bxs[i]
b_ = bxs[i + 1]
if b["page_number"] < b_["page_number"] and re.match(
r"[0-9 •一—-]+$", b["text"]):
bxs.pop(i)
continue
if not b["text"].strip():
bxs.pop(i)
continue
concatting_feats = [
b["text"].strip()[-1] in ",;:'\"，、‘“；：-",
len(b["text"].strip()) > 1 and b["text"].strip(
)[-2] in ",;:'\"，‘“、；：",
b_["text"].strip() and b_["text"].strip()[0] in "。；？！?”）),，、：",
]
# features for not concating
feats = [
b.get("layoutno", 0) != b_.get("layoutno", 0),
b["text"].strip()[-1] in "。？！?",
self.is_english and b["text"].strip()[-1] in ".!?",
b["page_number"] == b_["page_number"] and b_["top"] -
b["bottom"] > self.mean_height[b["page_number"] - 1] * 1.5,
b["page_number"] < b_["page_number"] and abs(
b["x0"] - b_["x0"]) > self.mean_width[b["page_number"] - 1] * 4,
]
# split features
detach_feats = [b["x1"] < b_["x0"],
b["x0"] > b_["x1"]]
if (any(feats) and not any(concatting_feats)) or any(detach_feats):
logging.debug("{} {} {} {}".format(
b["text"],
b_["text"],
any(feats),
any(concatting_feats),
))
i += 1
continue
# merge up and down
b["bottom"] = b_["bottom"]
b["text"] += b_["text"]
b["x0"] = min(b["x0"], b_["x0"])
b["x1"] = max(b["x1"], b_["x1"])
bxs.pop(i + 1)
self.boxes = bxs
def _concat_downward(self, concat_between_pages=True):
# count boxes in the same row as a feature
for i in range(len(self.boxes)):
mh = self.mean_height[self.boxes[i]["page_number"] - 1]
self.boxes[i]["in_row"] = 0
j = max(0, i - 12)
while j < min(i + 12, len(self.boxes)):
if j == i:
j += 1
continue
ydis = self._y_dis(self.boxes[i], self.boxes[j]) / mh
if abs(ydis) < 1:
self.boxes[i]["in_row"] += 1
elif ydis > 0:
break
j += 1
# concat between rows
boxes = deepcopy(self.boxes)
blocks = []
while boxes:
chunks = []
def dfs(up, dp):
chunks.append(up)
i = dp
while i < min(dp + 12, len(boxes)):
ydis = self._y_dis(up, boxes[i])
smpg = up["page_number"] == boxes[i]["page_number"]
mh = self.mean_height[up["page_number"] - 1]
mw = self.mean_width[up["page_number"] - 1]
if smpg and ydis > mh * 4:
break
if not smpg and ydis > mh * 16:
break
down = boxes[i]
if not concat_between_pages and down["page_number"] > up["page_number"]:
break
if up.get("R", "") != down.get(
"R", "") and up["text"][-1] != "，":
i += 1
continue
if re.match(r"[0-9]{2,3}/[0-9]{3}$", up["text"]) \
or re.match(r"[0-9]{2,3}/[0-9]{3}$", down["text"]) \
or not down["text"].strip():
i += 1
continue
if not down["text"].strip() or not up["text"].strip():
i += 1
continue
if up["x1"] < down["x0"] - 10 * \
mw or up["x0"] > down["x1"] + 10 * mw:
i += 1
continue
if i - dp < 5 and up.get("layout_type") == "text":
if up.get("layoutno", "1") == down.get(
"layoutno", "2"):
dfs(down, i + 1)
boxes.pop(i)
return
i += 1
continue
fea = self._updown_concat_features(up, down)
if self.updown_cnt_mdl.predict(
xgb.DMatrix([fea]))[0] <= 0.5:
i += 1
continue
dfs(down, i + 1)
boxes.pop(i)
return
dfs(boxes[0], 1)
boxes.pop(0)
if chunks:
blocks.append(chunks)
# concat within each block
boxes = []
for b in blocks:
if len(b) == 1:
boxes.append(b[0])
continue
t = b[0]
for c in b[1:]:
t["text"] = t["text"].strip()
c["text"] = c["text"].strip()
if not c["text"]:
continue
if t["text"] and re.match(
r"[0-9\.a-zA-Z]+$", t["text"][-1] + c["text"][-1]):
t["text"] += " "
t["text"] += c["text"]
t["x0"] = min(t["x0"], c["x0"])
t["x1"] = max(t["x1"], c["x1"])
t["page_number"] = min(t["page_number"], c["page_number"])
t["bottom"] = c["bottom"]
if not t["layout_type"] \
and c["layout_type"]:
t["layout_type"] = c["layout_type"]
boxes.append(t)
self.boxes = Recognizer.sort_Y_firstly(boxes, 0)
def _filter_forpages(self):
if not self.boxes:
return
findit = False
i = 0
while i < len(self.boxes):
if not re.match(r"(contents|目录|目次|table of contents|致谢|acknowledge)$",
re.sub(r"( | |\u3000)+", "", self.boxes[i]["text"].lower())):
i += 1
continue
findit = True
eng = re.match(
r"[0-9a-zA-Z :'.-]{5,}",
self.boxes[i]["text"].strip())
self.boxes.pop(i)
if i >= len(self.boxes):
break
prefix = self.boxes[i]["text"].strip()[:3] if not eng else " ".join(
self.boxes[i]["text"].strip().split()[:2])
while not prefix:
self.boxes.pop(i)
if i >= len(self.boxes):
break
prefix = self.boxes[i]["text"].strip()[:3] if not eng else " ".join(
self.boxes[i]["text"].strip().split()[:2])
self.boxes.pop(i)
if i >= len(self.boxes) or not prefix:
break
for j in range(i, min(i + 128, len(self.boxes))):
if not re.match(prefix, self.boxes[j]["text"]):
continue
for k in range(i, j):
self.boxes.pop(i)
break
if findit:
return
page_dirty = [0] * len(self.page_images)
for b in self.boxes:
if re.search(r"(··|··|··)", b["text"]):
page_dirty[b["page_number"] - 1] += 1
page_dirty = set([i + 1 for i, t in enumerate(page_dirty) if t > 3])
if not page_dirty:
return
i = 0
while i < len(self.boxes):
if self.boxes[i]["page_number"] in page_dirty:
self.boxes.pop(i)
continue
i += 1
def _merge_with_same_bullet(self):
i = 0
while i + 1 < len(self.boxes):
b = self.boxes[i]
b_ = self.boxes[i + 1]
if not b["text"].strip():
self.boxes.pop(i)
continue
if not b_["text"].strip():
self.boxes.pop(i + 1)
continue
if b["text"].strip()[0] != b_["text"].strip()[0] \
or b["text"].strip()[0].lower() in set("qwertyuopasdfghjklzxcvbnm") \
or rag_tokenizer.is_chinese(b["text"].strip()[0]) \
or b["top"] > b_["bottom"]:
i += 1
continue
b_["text"] = b["text"] + "\n" + b_["text"]
b_["x0"] = min(b["x0"], b_["x0"])
b_["x1"] = max(b["x1"], b_["x1"])
b_["top"] = b["top"]
self.boxes.pop(i)
def _extract_table_figure(self, need_image, ZM,
return_html, need_position):
tables = {}
figures = {}
# extract figure and table boxes
i = 0
lst_lout_no = ""
nomerge_lout_no = []
while i < len(self.boxes):
if "layoutno" not in self.boxes[i]:
i += 1
continue
lout_no = str(self.boxes[i]["page_number"]) + \
"-" + str(self.boxes[i]["layoutno"])
if TableStructureRecognizer.is_caption(self.boxes[i]) or self.boxes[i]["layout_type"] in ["table caption",
"title",
"figure caption",
"reference"]:
nomerge_lout_no.append(lst_lout_no)
if self.boxes[i]["layout_type"] == "table":
if re.match(r"(数据|资料|图表)*来源[:： ]", self.boxes[i]["text"]):
self.boxes.pop(i)
continue
if lout_no not in tables:
tables[lout_no] = []
tables[lout_no].append(self.boxes[i])
self.boxes.pop(i)
lst_lout_no = lout_no
continue
if need_image and self.boxes[i]["layout_type"] == "figure":
if re.match(r"(数据|资料|图表)*来源[:： ]", self.boxes[i]["text"]):
self.boxes.pop(i)
continue
if lout_no not in figures:
figures[lout_no] = []
figures[lout_no].append(self.boxes[i])
self.boxes.pop(i)
lst_lout_no = lout_no
continue
i += 1
# merge table on different pages
nomerge_lout_no = set(nomerge_lout_no)
tbls = sorted([(k, bxs) for k, bxs in tables.items()],
key=lambda x: (x[1][0]["top"], x[1][0]["x0"]))
i = len(tbls) - 1
while i - 1 >= 0:
k0, bxs0 = tbls[i - 1]
k, bxs = tbls[i]
i -= 1
if k0 in nomerge_lout_no:
continue
if bxs[0]["page_number"] == bxs0[0]["page_number"]:
continue
if bxs[0]["page_number"] - bxs0[0]["page_number"] > 1:
continue
mh = self.mean_height[bxs[0]["page_number"] - 1]
if self._y_dis(bxs0[-1], bxs[0]) > mh * 23:
continue
tables[k0].extend(tables[k])
del tables[k]
def x_overlapped(a, b):
return not any([a["x1"] < b["x0"], a["x0"] > b["x1"]])
# find captions and pop out
i = 0
while i < len(self.boxes):
c = self.boxes[i]
# mh = self.mean_height[c["page_number"]-1]
if not TableStructureRecognizer.is_caption(c):
i += 1
continue
# find the nearest layouts
def nearest(tbls):
nonlocal c
mink = ""
minv = 1000000000
for k, bxs in tbls.items():
for b in bxs:
if b.get("layout_type", "").find("caption") >= 0:
continue
y_dis = self._y_dis(c, b)
x_dis = self._x_dis(
c, b) if not x_overlapped(
c, b) else 0
dis = y_dis * y_dis + x_dis * x_dis
if dis < minv:
mink = k
minv = dis
return mink, minv
tk, tv = nearest(tables)
fk, fv = nearest(figures)
# if min(tv, fv) > 2000:
# i += 1
# continue
if tv < fv and tk:
tables[tk].insert(0, c)
logging.debug(
"TABLE:" +
self.boxes[i]["text"] +
"; Cap: " +
tk)
elif fk:
figures[fk].insert(0, c)
logging.debug(
"FIGURE:" +
self.boxes[i]["text"] +
"; Cap: " +
tk)
self.boxes.pop(i)
res = []
positions = []
def cropout(bxs, ltype, poss):
nonlocal ZM
pn = set([b["page_number"] - 1 for b in bxs])
if len(pn) < 2:
pn = list(pn)[0]
ht = self.page_cum_height[pn]
b = {
"x0": np.min([b["x0"] for b in bxs]),
"top": np.min([b["top"] for b in bxs]) - ht,
"x1": np.max([b["x1"] for b in bxs]),
"bottom": np.max([b["bottom"] for b in bxs]) - ht
}
louts = [l for l in self.page_layout[pn] if l["type"] == ltype]
ii = Recognizer.find_overlapped(b, louts, naive=True)
if ii is not None:
b = louts[ii]
else:
logging.warning(
f"Missing layout match: {pn + 1},%s" %
(bxs[0].get(
"layoutno", "")))
left, top, right, bott = b["x0"], b["top"], b["x1"], b["bottom"]
if right < left: right = left + 1
poss.append((pn + self.page_from, left, right, top, bott))
return self.page_images[pn] \
.crop((left * ZM, top * ZM,
right * ZM, bott * ZM))
pn = {}
for b in bxs:
p = b["page_number"] - 1
if p not in pn:
pn[p] = []
pn[p].append(b)
pn = sorted(pn.items(), key=lambda x: x[0])
imgs = [cropout(arr, ltype, poss) for p, arr in pn]
pic = Image.new("RGB",
(int(np.max([i.size[0] for i in imgs])),
int(np.sum([m.size[1] for m in imgs]))),
(245, 245, 245))
height = 0
for img in imgs:
pic.paste(img, (0, int(height)))
height += img.size[1]
return pic
# crop figure out and add caption
for k, bxs in figures.items():
txt = "\n".join([b["text"] for b in bxs])
if not txt:
continue
poss = []
res.append(
(cropout(
bxs,
"figure", poss),
[txt]))
positions.append(poss)
for k, bxs in tables.items():
if not bxs:
continue
bxs = Recognizer.sort_Y_firstly(bxs, np.mean(
[(b["bottom"] - b["top"]) / 2 for b in bxs]))
poss = []
res.append((cropout(bxs, "table", poss),
self.tbl_det.construct_table(bxs, html=return_html, is_english=self.is_english)))
positions.append(poss)
assert len(positions) == len(res)
if need_position:
return list(zip(res, positions))
return res
def proj_match(self, line):
if len(line) <= 2:
return
if re.match(r"[0-9 ().,%%+/-]+$", line):
return False
for p, j in [
(r"第[零一二三四五六七八九十百]+章", 1),
(r"第[零一二三四五六七八九十百]+[条节]", 2),
(r"[零一二三四五六七八九十百]+[、 ]", 3),
(r"[\(（][零一二三四五六七八九十百]+[）\)]", 4),
(r"[0-9]+(、|\.[ ]|\.[^0-9])", 5),
(r"[0-9]+\.[0-9]+(、|[. ]|[^0-9])", 6),
(r"[0-9]+\.[0-9]+\.[0-9]+(、|[ ]|[^0-9])", 7),
(r"[0-9]+\.[0-9]+\.[0-9]+\.[0-9]+(、|[ ]|[^0-9])", 8),
(r".{,48}[：:?？]$", 9),
(r"[0-9]+）", 10),
(r"[\(（][0-9]+[）\)]", 11),
(r"[零一二三四五六七八九十百]+是", 12),
(r"[⚫•➢✓]", 12)
]:
if re.match(p, line):
return j
return
def _line_tag(self, bx, ZM):
pn = [bx["page_number"]]
top = bx["top"] - self.page_cum_height[pn[0] - 1]
bott = bx["bottom"] - self.page_cum_height[pn[0] - 1]
page_images_cnt = len(self.page_images)
if pn[-1] - 1 >= page_images_cnt: return ""
while bott * ZM > self.page_images[pn[-1] - 1].size[1]:
bott -= self.page_images[pn[-1] - 1].size[1] / ZM
pn.append(pn[-1] + 1)
if pn[-1] - 1 >= page_images_cnt:
return ""
return "@@{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}##" \
.format("-".join([str(p) for p in pn]),
bx["x0"], bx["x1"], top, bott)
def __filterout_scraps(self, boxes, ZM):
def width(b):
return b["x1"] - b["x0"]
def height(b):
return b["bottom"] - b["top"]
def usefull(b):
if b.get("layout_type"):
return True
if width(
b) > self.page_images[b["page_number"] - 1].size[0] / ZM / 3:
return True
if b["bottom"] - b["top"] > self.mean_height[b["page_number"] - 1]:
return True
return False
res = []
while boxes:
lines = []
widths = []
pw = self.page_images[boxes[0]["page_number"] - 1].size[0] / ZM
mh = self.mean_height[boxes[0]["page_number"] - 1]
mj = self.proj_match(
boxes[0]["text"]) or boxes[0].get(
"layout_type",
"") == "title"
def dfs(line, st):
nonlocal mh, pw, lines, widths
lines.append(line)
widths.append(width(line))
width_mean = np.mean(widths)
mmj = self.proj_match(
line["text"]) or line.get(
"layout_type",
"") == "title"
for i in range(st + 1, min(st + 20, len(boxes))):
if (boxes[i]["page_number"] - line["page_number"]) > 0:
break
if not mmj and self._y_dis(
line, boxes[i]) >= 3 * mh and height(line) < 1.5 * mh:
break
if not usefull(boxes[i]):
continue
if mmj or \
(self._x_dis(boxes[i], line) < pw / 10): \
# and abs(width(boxes[i])-width_mean)/max(width(boxes[i]),width_mean)<0.5):
# concat following
dfs(boxes[i], i)
boxes.pop(i)
break
try:
if usefull(boxes[0]):
dfs(boxes[0], 0)
else:
logging.debug("WASTE: " + boxes[0]["text"])
except Exception:
pass
boxes.pop(0)
mw = np.mean(widths)
if mj or mw / pw >= 0.35 or mw > 200:
res.append(
"\n".join([c["text"] + self._line_tag(c, ZM) for c in lines]))
else:
logging.debug("REMOVED: " +
"<<".join([c["text"] for c in lines]))
return "\n\n".join(res)
@staticmethod
def total_page_number(fnm, binary=None):
try:
pdf = pdfplumber.open(
fnm) if not binary else pdfplumber.open(BytesIO(binary))
return len(pdf.pages)
except Exception:
logging.exception("total_page_number")
def __images__(self, fnm, zoomin=3, page_from=0,
page_to=299, callback=None):
self.lefted_chars = []
self.mean_height = []
self.mean_width = []
self.boxes = []
self.garbages = {}
self.page_cum_height = [0]
self.page_layout = []
self.page_from = page_from
st = timer()
try:
self.pdf = pdfplumber.open(fnm) if isinstance(
fnm, str) else pdfplumber.open(BytesIO(fnm))
self.page_images = [p.to_image(resolution=72 * zoomin).annotated for i, p in
enumerate(self.pdf.pages[page_from:page_to])]
self.page_images_x2 = [p.to_image(resolution=72 * zoomin * 2).annotated for i, p in
enumerate(self.pdf.pages[page_from:page_to])]
self.page_chars = [[{**c, 'top': c['top'], 'bottom': c['bottom']} for c in page.dedupe_chars().chars if self._has_color(c)] for page in
self.pdf.pages[page_from:page_to]]
self.total_page = len(self.pdf.pages)
except Exception:
logging.exception("RAGFlowPdfParser __images__")
self.outlines = []
try:
self.pdf = pdf2_read(fnm if isinstance(fnm, str) else BytesIO(fnm))
outlines = self.pdf.outline
def dfs(arr, depth):
for a in arr:
if isinstance(a, dict):
self.outlines.append((a["/Title"], depth))
continue
dfs(a, depth + 1)
dfs(outlines, 0)
except Exception as e:
logging.warning(f"Outlines exception: {e}")
if not self.outlines:
logging.warning("Miss outlines")
logging.debug("Images converted.")
self.is_english = [re.search(r"[a-zA-Z0-9,/¸;:'\[\]\(\)!@#$%^&*\"?<>._-]{30,}", "".join(
random.choices([c["text"] for c in self.page_chars[i]], k=min(100, len(self.page_chars[i]))))) for i in
range(len(self.page_chars))]
if sum([1 if e else 0 for e in self.is_english]) > len(
self.page_images) / 2:
self.is_english = True
else:
self.is_english = False
st = timer()
for i, img in enumerate(self.page_images_x2):
chars = self.page_chars[i] if not self.is_english else []
self.mean_height.append(
np.median(sorted([c["height"] for c in chars])) if chars else 0
)
self.mean_width.append(
np.median(sorted([c["width"] for c in chars])) if chars else 8
)
self.page_cum_height.append(img.size[1] / zoomin/2)
j = 0
while j + 1 < len(chars):
if chars[j]["text"] and chars[j + 1]["text"] \
and re.match(r"[0-9a-zA-Z,.:;!%]+", chars[j]["text"] + chars[j + 1]["text"]) \
and chars[j + 1]["x0"] - chars[j]["x1"] >= min(chars[j + 1]["width"],
chars[j]["width"]) / 2:
chars[j]["text"] += " "
j += 1
self.__ocr(i + 1, img, chars, zoomin*2)
if callback and i % 6 == 5:
callback(prog=(i + 1) * 0.6 / len(self.page_images), msg="")
# print("OCR:", timer()-st)
if not self.is_english and not any(
[c for c in self.page_chars]) and self.boxes:
bxes = [b for bxs in self.boxes for b in bxs]
self.is_english = re.search(r"[\na-zA-Z0-9,/¸;:'\[\]\(\)!@#$%^&*\"?<>._-]{30,}",
"".join([b["text"] for b in random.choices(bxes, k=min(30, len(bxes)))]))
logging.debug("Is it English:", self.is_english)
self.page_cum_height = np.cumsum(self.page_cum_height)
assert len(self.page_cum_height) == len(self.page_images) + 1
if len(self.boxes) == 0 and zoomin < 9: self.__images__(fnm, zoomin * 3, page_from,
page_to, callback)
def __call__(self, fnm, need_image=True, zoomin=3, return_html=False):
self.__images__(fnm, zoomin)
self._layouts_rec(zoomin)
self._table_transformer_job(zoomin)
self._text_merge()
self._concat_downward()
self._filter_forpages()
tbls = self._extract_table_figure(
need_image, zoomin, return_html, False)
return self.__filterout_scraps(deepcopy(self.boxes), zoomin), tbls
def remove_tag(self, txt):
return re.sub(r"@@[\t0-9.-]+?##", "", txt)
def crop(self, text, ZM=3, need_position=False):
imgs = []
poss = []
for tag in re.findall(r"@@[0-9-]+\t[0-9.\t]+##", text):
pn, left, right, top, bottom = tag.strip(
"#").strip("@").split("\t")
left, right, top, bottom = float(left), float(
right), float(top), float(bottom)
poss.append(([int(p) - 1 for p in pn.split("-")],
left, right, top, bottom))
if not poss:
if need_position:
return None, None
return
max_width = max(
np.max([right - left for (_, left, right, _, _) in poss]), 6)
GAP = 6
pos = poss[0]
poss.insert(0, ([pos[0][0]], pos[1], pos[2], max(
0, pos[3] - 120), max(pos[3] - GAP, 0)))
pos = poss[-1]
poss.append(([pos[0][-1]], pos[1], pos[2], min(self.page_images[pos[0][-1]].size[1] / ZM, pos[4] + GAP),
min(self.page_images[pos[0][-1]].size[1] / ZM, pos[4] + 120)))
positions = []
for ii, (pns, left, right, top, bottom) in enumerate(poss):
right = left + max_width
bottom *= ZM
for pn in pns[1:]:
bottom += self.page_images[pn - 1].size[1]
imgs.append(
self.page_images[pns[0]].crop((left * ZM, top * ZM,
right *
ZM, min(
bottom, self.page_images[pns[0]].size[1])
))
)
if 0 < ii < len(poss) - 1:
positions.append((pns[0] + self.page_from, left, right, top, min(
bottom, self.page_images[pns[0]].size[1]) / ZM))
bottom -= self.page_images[pns[0]].size[1]
for pn in pns[1:]:
imgs.append(
self.page_images[pn].crop((left * ZM, 0,
right * ZM,
min(bottom,
self.page_images[pn].size[1])
))
)
if 0 < ii < len(poss) - 1:
positions.append((pn + self.page_from, left, right, 0, min(
bottom, self.page_images[pn].size[1]) / ZM))
bottom -= self.page_images[pn].size[1]
if not imgs:
if need_position:
return None, None
return
height = 0
for img in imgs:
height += img.size[1] + GAP
height = int(height)
width = int(np.max([i.size[0] for i in imgs]))
pic = Image.new("RGB",
(width, height),
(245, 245, 245))
height = 0
for ii, img in enumerate(imgs):
if ii == 0 or ii + 1 == len(imgs):
img = img.convert('RGBA')
overlay = Image.new('RGBA', img.size, (0, 0, 0, 0))
overlay.putalpha(128)
img = Image.alpha_composite(img, overlay).convert("RGB")
pic.paste(img, (0, int(height)))
height += img.size[1] + GAP
if need_position:
return pic, positions
return pic
def get_position(self, bx, ZM):
poss = []
pn = bx["page_number"]
top = bx["top"] - self.page_cum_height[pn - 1]
bott = bx["bottom"] - self.page_cum_height[pn - 1]
poss.append((pn, bx["x0"], bx["x1"], top, min(
bott, self.page_images[pn - 1].size[1] / ZM)))
while bott * ZM > self.page_images[pn - 1].size[1]:
bott -= self.page_images[pn - 1].size[1] / ZM
top = 0
pn += 1
poss.append((pn, bx["x0"], bx["x1"], top, min(
bott, self.page_images[pn - 1].size[1] / ZM)))
return poss
class PlainParser(object):
def __call__(self, filename, from_page=0, to_page=100000, **kwargs):
self.outlines = []
lines = []
try:
self.pdf = pdf2_read(
filename if isinstance(
filename, str) else BytesIO(filename))
for page in self.pdf.pages[from_page:to_page]:
lines.extend([t for t in page.extract_text().split("\n")])
outlines = self.pdf.outline
def dfs(arr, depth):
for a in arr:
if isinstance(a, dict):
self.outlines.append((a["/Title"], depth))
continue
dfs(a, depth + 1)
dfs(outlines, 0)
except Exception:
logging.exception("Outlines exception")
if not self.outlines:
logging.warning("Miss outlines")
return [(l, "") for l in lines], []
def crop(self, ck, need_position):
raise NotImplementedError
@staticmethod
def remove_tag(txt):
raise NotImplementedError
if __name__ == "__main__":
pass