- # 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.warn(
- 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
|