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pdf_parser.py 41KB

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  1. # -*- coding: utf-8 -*-
  2. import random
  3. import fitz
  4. import xgboost as xgb
  5. from io import BytesIO
  6. import torch
  7. import re
  8. import pdfplumber
  9. import logging
  10. from PIL import Image, ImageDraw
  11. import numpy as np
  12. from api.db import ParserType
  13. from deepdoc.vision import OCR, Recognizer, LayoutRecognizer, TableStructureRecognizer
  14. from rag.nlp import huqie
  15. from copy import deepcopy
  16. from huggingface_hub import hf_hub_download
  17. logging.getLogger("pdfminer").setLevel(logging.WARNING)
  18. class HuParser:
  19. def __init__(self):
  20. self.ocr = OCR()
  21. if hasattr(self, "model_speciess"):
  22. self.layouter = LayoutRecognizer("layout."+self.model_speciess)
  23. else:
  24. self.layouter = LayoutRecognizer("layout")
  25. self.tbl_det = TableStructureRecognizer()
  26. self.updown_cnt_mdl = xgb.Booster()
  27. if torch.cuda.is_available():
  28. self.updown_cnt_mdl.set_param({"device": "cuda"})
  29. self.updown_cnt_mdl.load_model(hf_hub_download(repo_id="InfiniFlow/text_concat_xgb_v1.0",
  30. filename="updown_concat_xgb.model"))
  31. self.page_from = 0
  32. """
  33. If you have trouble downloading HuggingFace models, -_^ this might help!!
  34. For Linux:
  35. export HF_ENDPOINT=https://hf-mirror.com
  36. For Windows:
  37. Good luck
  38. ^_-
  39. """
  40. def __char_width(self, c):
  41. return (c["x1"] - c["x0"]) // len(c["text"])
  42. def __height(self, c):
  43. return c["bottom"] - c["top"]
  44. def _x_dis(self, a, b):
  45. return min(abs(a["x1"] - b["x0"]), abs(a["x0"] - b["x1"]),
  46. abs(a["x0"] + a["x1"] - b["x0"] - b["x1"]) / 2)
  47. def _y_dis(
  48. self, a, b):
  49. return (
  50. b["top"] + b["bottom"] - a["top"] - a["bottom"]) / 2
  51. def _match_proj(self, b):
  52. proj_patt = [
  53. r"第[零一二三四五六七八九十百]+章",
  54. r"第[零一二三四五六七八九十百]+[条节]",
  55. r"[零一二三四五六七八九十百]+[、是  ]",
  56. r"[\((][零一二三四五六七八九十百]+[)\)]",
  57. r"[\((][0-9]+[)\)]",
  58. r"[0-9]+(、|\.[  ]|)|\.[^0-9./a-zA-Z_%><-]{4,})",
  59. r"[0-9]+\.[0-9.]+(、|\.[  ])",
  60. r"[⚫•➢①② ]",
  61. ]
  62. return any([re.match(p, b["text"]) for p in proj_patt])
  63. def _updown_concat_features(self, up, down):
  64. w = max(self.__char_width(up), self.__char_width(down))
  65. h = max(self.__height(up), self.__height(down))
  66. y_dis = self._y_dis(up, down)
  67. LEN = 6
  68. tks_down = huqie.qie(down["text"][:LEN]).split(" ")
  69. tks_up = huqie.qie(up["text"][-LEN:]).split(" ")
  70. tks_all = up["text"][-LEN:].strip() \
  71. + (" " if re.match(r"[a-zA-Z0-9]+",
  72. up["text"][-1] + down["text"][0]) else "") \
  73. + down["text"][:LEN].strip()
  74. tks_all = huqie.qie(tks_all).split(" ")
  75. fea = [
  76. up.get("R", -1) == down.get("R", -1),
  77. y_dis / h,
  78. down["page_number"] - up["page_number"],
  79. up["layout_type"] == down["layout_type"],
  80. up["layout_type"] == "text",
  81. down["layout_type"] == "text",
  82. up["layout_type"] == "table",
  83. down["layout_type"] == "table",
  84. True if re.search(
  85. r"([。?!;!?;+))]|[a-z]\.)$",
  86. up["text"]) else False,
  87. True if re.search(r"[,:‘“、0-9(+-]$", up["text"]) else False,
  88. True if re.search(
  89. r"(^.?[/,?;:\],。;:’”?!》】)-])",
  90. down["text"]) else False,
  91. True if re.match(r"[\((][^\(\)()]+[)\)]$", up["text"]) else False,
  92. True if re.search(r"[,,][^。.]+$", up["text"]) else False,
  93. True if re.search(r"[,,][^。.]+$", up["text"]) else False,
  94. True if re.search(r"[\((][^\))]+$", up["text"])
  95. and re.search(r"[\))]", down["text"]) else False,
  96. self._match_proj(down),
  97. True if re.match(r"[A-Z]", down["text"]) else False,
  98. True if re.match(r"[A-Z]", up["text"][-1]) else False,
  99. True if re.match(r"[a-z0-9]", up["text"][-1]) else False,
  100. True if re.match(r"[0-9.%,-]+$", down["text"]) else False,
  101. up["text"].strip()[-2:] == down["text"].strip()[-2:] if len(up["text"].strip()
  102. ) > 1 and len(
  103. down["text"].strip()) > 1 else False,
  104. up["x0"] > down["x1"],
  105. abs(self.__height(up) - self.__height(down)) / min(self.__height(up),
  106. self.__height(down)),
  107. self._x_dis(up, down) / max(w, 0.000001),
  108. (len(up["text"]) - len(down["text"])) /
  109. max(len(up["text"]), len(down["text"])),
  110. len(tks_all) - len(tks_up) - len(tks_down),
  111. len(tks_down) - len(tks_up),
  112. tks_down[-1] == tks_up[-1],
  113. max(down["in_row"], up["in_row"]),
  114. abs(down["in_row"] - up["in_row"]),
  115. len(tks_down) == 1 and huqie.tag(tks_down[0]).find("n") >= 0,
  116. len(tks_up) == 1 and huqie.tag(tks_up[0]).find("n") >= 0
  117. ]
  118. return fea
  119. @staticmethod
  120. def sort_X_by_page(arr, threashold):
  121. # sort using y1 first and then x1
  122. arr = sorted(arr, key=lambda r: (r["page_number"], r["x0"], r["top"]))
  123. for i in range(len(arr) - 1):
  124. for j in range(i, -1, -1):
  125. # restore the order using th
  126. if abs(arr[j + 1]["x0"] - arr[j]["x0"]) < threashold \
  127. and arr[j + 1]["top"] < arr[j]["top"]\
  128. and arr[j + 1]["page_number"] == arr[j]["page_number"]:
  129. tmp = arr[j]
  130. arr[j] = arr[j + 1]
  131. arr[j + 1] = tmp
  132. return arr
  133. def _has_color(self, o):
  134. if o.get("ncs", "") == "DeviceGray":
  135. if o["stroking_color"] and o["stroking_color"][0] == 1 and o["non_stroking_color"] and \
  136. o["non_stroking_color"][0] == 1:
  137. if re.match(r"[a-zT_\[\]\(\)-]+", o.get("text", "")):
  138. return False
  139. return True
  140. def _table_transformer_job(self, ZM):
  141. logging.info("Table processing...")
  142. imgs, pos = [], []
  143. tbcnt = [0]
  144. MARGIN = 10
  145. self.tb_cpns = []
  146. assert len(self.page_layout) == len(self.page_images)
  147. for p, tbls in enumerate(self.page_layout): # for page
  148. tbls = [f for f in tbls if f["type"] == "table"]
  149. tbcnt.append(len(tbls))
  150. if not tbls:
  151. continue
  152. for tb in tbls: # for table
  153. left, top, right, bott = tb["x0"] - MARGIN, tb["top"] - MARGIN, \
  154. tb["x1"] + MARGIN, tb["bottom"] + MARGIN
  155. left *= ZM
  156. top *= ZM
  157. right *= ZM
  158. bott *= ZM
  159. pos.append((left, top))
  160. imgs.append(self.page_images[p].crop((left, top, right, bott)))
  161. assert len(self.page_images) == len(tbcnt) - 1
  162. if not imgs:
  163. return
  164. recos = self.tbl_det(imgs)
  165. tbcnt = np.cumsum(tbcnt)
  166. for i in range(len(tbcnt) - 1): # for page
  167. pg = []
  168. for j, tb_items in enumerate(
  169. recos[tbcnt[i]: tbcnt[i + 1]]): # for table
  170. poss = pos[tbcnt[i]: tbcnt[i + 1]]
  171. for it in tb_items: # for table components
  172. it["x0"] = (it["x0"] + poss[j][0])
  173. it["x1"] = (it["x1"] + poss[j][0])
  174. it["top"] = (it["top"] + poss[j][1])
  175. it["bottom"] = (it["bottom"] + poss[j][1])
  176. for n in ["x0", "x1", "top", "bottom"]:
  177. it[n] /= ZM
  178. it["top"] += self.page_cum_height[i]
  179. it["bottom"] += self.page_cum_height[i]
  180. it["pn"] = i
  181. it["layoutno"] = j
  182. pg.append(it)
  183. self.tb_cpns.extend(pg)
  184. def gather(kwd, fzy=10, ption=0.6):
  185. eles = Recognizer.sort_Y_firstly(
  186. [r for r in self.tb_cpns if re.match(kwd, r["label"])], fzy)
  187. eles = Recognizer.layouts_cleanup(self.boxes, eles, 5, ption)
  188. return Recognizer.sort_Y_firstly(eles, 0)
  189. # add R,H,C,SP tag to boxes within table layout
  190. headers = gather(r".*header$")
  191. rows = gather(r".* (row|header)")
  192. spans = gather(r".*spanning")
  193. clmns = sorted([r for r in self.tb_cpns if re.match(
  194. r"table column$", r["label"])], key=lambda x: (x["pn"], x["layoutno"], x["x0"]))
  195. clmns = Recognizer.layouts_cleanup(self.boxes, clmns, 5, 0.5)
  196. for b in self.boxes:
  197. if b.get("layout_type", "") != "table":
  198. continue
  199. ii = Recognizer.find_overlapped_with_threashold(b, rows, thr=0.3)
  200. if ii is not None:
  201. b["R"] = ii
  202. b["R_top"] = rows[ii]["top"]
  203. b["R_bott"] = rows[ii]["bottom"]
  204. ii = Recognizer.find_overlapped_with_threashold(b, headers, thr=0.3)
  205. if ii is not None:
  206. b["H_top"] = headers[ii]["top"]
  207. b["H_bott"] = headers[ii]["bottom"]
  208. b["H_left"] = headers[ii]["x0"]
  209. b["H_right"] = headers[ii]["x1"]
  210. b["H"] = ii
  211. ii = Recognizer.find_horizontally_tightest_fit(b, clmns)
  212. if ii is not None:
  213. b["C"] = ii
  214. b["C_left"] = clmns[ii]["x0"]
  215. b["C_right"] = clmns[ii]["x1"]
  216. ii = Recognizer.find_overlapped_with_threashold(b, spans, thr=0.3)
  217. if ii is not None:
  218. b["H_top"] = spans[ii]["top"]
  219. b["H_bott"] = spans[ii]["bottom"]
  220. b["H_left"] = spans[ii]["x0"]
  221. b["H_right"] = spans[ii]["x1"]
  222. b["SP"] = ii
  223. def __ocr(self, pagenum, img, chars, ZM=3):
  224. bxs = self.ocr.detect(np.array(img))
  225. if not bxs:
  226. self.boxes.append([])
  227. return
  228. bxs = [(line[0], line[1][0]) for line in bxs]
  229. bxs = Recognizer.sort_Y_firstly(
  230. [{"x0": b[0][0] / ZM, "x1": b[1][0] / ZM,
  231. "top": b[0][1] / ZM, "text": "", "txt": t,
  232. "bottom": b[-1][1] / ZM,
  233. "page_number": pagenum} for b, t in bxs if b[0][0] <= b[1][0] and b[0][1] <= b[-1][1]],
  234. self.mean_height[-1] / 3
  235. )
  236. # merge chars in the same rect
  237. for c in Recognizer.sort_X_firstly(chars, self.mean_width[pagenum - 1] // 4):
  238. ii = Recognizer.find_overlapped(c, bxs)
  239. if ii is None:
  240. self.lefted_chars.append(c)
  241. continue
  242. ch = c["bottom"] - c["top"]
  243. bh = bxs[ii]["bottom"] - bxs[ii]["top"]
  244. if abs(ch - bh) / max(ch, bh) >= 0.7 and c["text"] != ' ':
  245. self.lefted_chars.append(c)
  246. continue
  247. if c["text"] == " " and bxs[ii]["text"]:
  248. if re.match(r"[0-9a-zA-Z,.?;:!%%]", bxs[ii]["text"][-1]): bxs[ii]["text"] += " "
  249. else:
  250. bxs[ii]["text"] += c["text"]
  251. for b in bxs:
  252. if not b["text"]:
  253. left, right, top, bott = b["x0"]*ZM, b["x1"]*ZM, b["top"]*ZM, b["bottom"]*ZM
  254. b["text"] = self.ocr.recognize(np.array(img), np.array([[left, top], [right, top], [right, bott], [left, bott]], dtype=np.float32))
  255. del b["txt"]
  256. bxs = [b for b in bxs if b["text"]]
  257. if self.mean_height[-1] == 0:
  258. self.mean_height[-1] = np.median([b["bottom"] - b["top"]
  259. for b in bxs])
  260. self.boxes.append(bxs)
  261. def _layouts_rec(self, ZM):
  262. assert len(self.page_images) == len(self.boxes)
  263. self.boxes, self.page_layout = self.layouter(self.page_images, self.boxes, ZM)
  264. # cumlative Y
  265. for i in range(len(self.boxes)):
  266. self.boxes[i]["top"] += \
  267. self.page_cum_height[self.boxes[i]["page_number"] - 1]
  268. self.boxes[i]["bottom"] += \
  269. self.page_cum_height[self.boxes[i]["page_number"] - 1]
  270. def _text_merge(self):
  271. # merge adjusted boxes
  272. bxs = self.boxes
  273. def end_with(b, txt):
  274. txt = txt.strip()
  275. tt = b.get("text", "").strip()
  276. return tt and tt.find(txt) == len(tt) - len(txt)
  277. def start_with(b, txts):
  278. tt = b.get("text", "").strip()
  279. return tt and any([tt.find(t.strip()) == 0 for t in txts])
  280. # horizontally merge adjacent box with the same layout
  281. i = 0
  282. while i < len(bxs) - 1:
  283. b = bxs[i]
  284. b_ = bxs[i + 1]
  285. if b.get("layoutno", "0") != b_.get("layoutno", "1") or b.get("layout_type", "") in ["table", "figure", "equation"]:
  286. i += 1
  287. continue
  288. if abs(self._y_dis(b, b_)) < self.mean_height[bxs[i]["page_number"] - 1] / 3:
  289. # merge
  290. bxs[i]["x1"] = b_["x1"]
  291. bxs[i]["top"] = (b["top"] + b_["top"]) / 2
  292. bxs[i]["bottom"] = (b["bottom"] + b_["bottom"]) / 2
  293. bxs[i]["text"] += b_["text"]
  294. bxs.pop(i + 1)
  295. continue
  296. i += 1
  297. continue
  298. dis_thr = 1
  299. dis = b["x1"] - b_["x0"]
  300. if b.get("layout_type", "") != "text" or b_.get(
  301. "layout_type", "") != "text":
  302. if end_with(b, ",") or start_with(b_, "(,"):
  303. dis_thr = -8
  304. else:
  305. i += 1
  306. continue
  307. if abs(self._y_dis(b, b_)) < self.mean_height[bxs[i]["page_number"] - 1] / 5 \
  308. and dis >= dis_thr and b["x1"] < b_["x1"]:
  309. # merge
  310. bxs[i]["x1"] = b_["x1"]
  311. bxs[i]["top"] = (b["top"] + b_["top"]) / 2
  312. bxs[i]["bottom"] = (b["bottom"] + b_["bottom"]) / 2
  313. bxs[i]["text"] += b_["text"]
  314. bxs.pop(i + 1)
  315. continue
  316. i += 1
  317. self.boxes = bxs
  318. def _naive_vertical_merge(self):
  319. bxs = Recognizer.sort_Y_firstly(self.boxes, np.median(self.mean_height) / 3)
  320. i = 0
  321. while i + 1 < len(bxs):
  322. b = bxs[i]
  323. b_ = bxs[i + 1]
  324. if b["page_number"] < b_["page_number"] and re.match(r"[0-9 •一—-]+$", b["text"]):
  325. bxs.pop(i)
  326. continue
  327. if not b["text"].strip():
  328. bxs.pop(i)
  329. continue
  330. concatting_feats = [
  331. b["text"].strip()[-1] in ",;:'\",、‘“;:-",
  332. len(b["text"].strip()) > 1 and b["text"].strip()[-2] in ",;:'\",‘“、;:",
  333. b["text"].strip()[0] in "。;?!?”)),,、:",
  334. ]
  335. # features for not concating
  336. feats = [
  337. b.get("layoutno", 0) != b.get("layoutno", 0),
  338. b["text"].strip()[-1] in "。?!?",
  339. self.is_english and b["text"].strip()[-1] in ".!?",
  340. b["page_number"] == b_["page_number"] and b_["top"] - \
  341. b["bottom"] > self.mean_height[b["page_number"] - 1] * 1.5,
  342. b["page_number"] < b_["page_number"] and abs(
  343. b["x0"] - b_["x0"]) > self.mean_width[b["page_number"] - 1] * 4
  344. ]
  345. if any(feats) and not any(concatting_feats):
  346. i += 1
  347. continue
  348. # merge up and down
  349. b["bottom"] = b_["bottom"]
  350. b["text"] += b_["text"]
  351. b["x0"] = min(b["x0"], b_["x0"])
  352. b["x1"] = max(b["x1"], b_["x1"])
  353. bxs.pop(i + 1)
  354. self.boxes = bxs
  355. def _concat_downward(self, concat_between_pages=True):
  356. # count boxes in the same row as a feature
  357. for i in range(len(self.boxes)):
  358. mh = self.mean_height[self.boxes[i]["page_number"] - 1]
  359. self.boxes[i]["in_row"] = 0
  360. j = max(0, i - 12)
  361. while j < min(i + 12, len(self.boxes)):
  362. if j == i:
  363. j += 1
  364. continue
  365. ydis = self._y_dis(self.boxes[i], self.boxes[j]) / mh
  366. if abs(ydis) < 1:
  367. self.boxes[i]["in_row"] += 1
  368. elif ydis > 0:
  369. break
  370. j += 1
  371. # concat between rows
  372. boxes = deepcopy(self.boxes)
  373. blocks = []
  374. while boxes:
  375. chunks = []
  376. def dfs(up, dp):
  377. chunks.append(up)
  378. i = dp
  379. while i < min(dp + 12, len(boxes)):
  380. ydis = self._y_dis(up, boxes[i])
  381. smpg = up["page_number"] == boxes[i]["page_number"]
  382. mh = self.mean_height[up["page_number"] - 1]
  383. mw = self.mean_width[up["page_number"] - 1]
  384. if smpg and ydis > mh * 4:
  385. break
  386. if not smpg and ydis > mh * 16:
  387. break
  388. down = boxes[i]
  389. if not concat_between_pages and down["page_number"] > up["page_number"]:
  390. break
  391. if up.get("R", "") != down.get(
  392. "R", "") and up["text"][-1] != ",":
  393. i += 1
  394. continue
  395. if re.match(r"[0-9]{2,3}/[0-9]{3}$", up["text"]) \
  396. or re.match(r"[0-9]{2,3}/[0-9]{3}$", down["text"]):
  397. i += 1
  398. continue
  399. if not down["text"].strip():
  400. i += 1
  401. continue
  402. if up["x1"] < down["x0"] - 10 * \
  403. mw or up["x0"] > down["x1"] + 10 * mw:
  404. i += 1
  405. continue
  406. if i - dp < 5 and up.get("layout_type") == "text":
  407. if up.get("layoutno", "1") == down.get(
  408. "layoutno", "2"):
  409. dfs(down, i + 1)
  410. boxes.pop(i)
  411. return
  412. i += 1
  413. continue
  414. fea = self._updown_concat_features(up, down)
  415. if self.updown_cnt_mdl.predict(
  416. xgb.DMatrix([fea]))[0] <= 0.5:
  417. i += 1
  418. continue
  419. dfs(down, i + 1)
  420. boxes.pop(i)
  421. return
  422. dfs(boxes[0], 1)
  423. boxes.pop(0)
  424. if chunks:
  425. blocks.append(chunks)
  426. # concat within each block
  427. boxes = []
  428. for b in blocks:
  429. if len(b) == 1:
  430. boxes.append(b[0])
  431. continue
  432. t = b[0]
  433. for c in b[1:]:
  434. t["text"] = t["text"].strip()
  435. c["text"] = c["text"].strip()
  436. if not c["text"]:
  437. continue
  438. if t["text"] and re.match(
  439. r"[0-9\.a-zA-Z]+$", t["text"][-1] + c["text"][-1]):
  440. t["text"] += " "
  441. t["text"] += c["text"]
  442. t["x0"] = min(t["x0"], c["x0"])
  443. t["x1"] = max(t["x1"], c["x1"])
  444. t["page_number"] = min(t["page_number"], c["page_number"])
  445. t["bottom"] = c["bottom"]
  446. if not t["layout_type"] \
  447. and c["layout_type"]:
  448. t["layout_type"] = c["layout_type"]
  449. boxes.append(t)
  450. self.boxes = Recognizer.sort_Y_firstly(boxes, 0)
  451. def _filter_forpages(self):
  452. if not self.boxes:
  453. return
  454. findit = False
  455. i = 0
  456. while i < len(self.boxes):
  457. 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())):
  458. i += 1
  459. continue
  460. findit = True
  461. eng = re.match(r"[0-9a-zA-Z :'.-]{5,}", self.boxes[i]["text"].strip())
  462. self.boxes.pop(i)
  463. if i >= len(self.boxes): break
  464. prefix = self.boxes[i]["text"].strip()[:3] if not eng else " ".join(self.boxes[i]["text"].strip().split(" ")[:2])
  465. while not prefix:
  466. self.boxes.pop(i)
  467. if i >= len(self.boxes): break
  468. prefix = self.boxes[i]["text"].strip()[:3] if not eng else " ".join(self.boxes[i]["text"].strip().split(" ")[:2])
  469. self.boxes.pop(i)
  470. if i >= len(self.boxes) or not prefix: break
  471. for j in range(i, min(i + 128, len(self.boxes))):
  472. if not re.match(prefix, self.boxes[j]["text"]):
  473. continue
  474. for k in range(i, j): self.boxes.pop(i)
  475. break
  476. if findit:return
  477. page_dirty = [0] * len(self.page_images)
  478. for b in self.boxes:
  479. if re.search(r"(··|··|··)", b["text"]):
  480. page_dirty[b["page_number"]-1] += 1
  481. page_dirty = set([i+1 for i, t in enumerate(page_dirty) if t > 3])
  482. if not page_dirty: return
  483. i = 0
  484. while i < len(self.boxes):
  485. if self.boxes[i]["page_number"] in page_dirty:
  486. self.boxes.pop(i)
  487. continue
  488. i += 1
  489. def _merge_with_same_bullet(self):
  490. i = 0
  491. while i + 1 < len(self.boxes):
  492. b = self.boxes[i]
  493. b_ = self.boxes[i + 1]
  494. if not b["text"].strip():
  495. self.boxes.pop(i)
  496. continue
  497. if not b_["text"].strip():
  498. self.boxes.pop(i+1)
  499. continue
  500. if b["text"].strip()[0] != b_["text"].strip()[0] \
  501. or b["text"].strip()[0].lower() in set("qwertyuopasdfghjklzxcvbnm") \
  502. or huqie.is_chinese(b["text"].strip()[0]) \
  503. or b["top"] > b_["bottom"]:
  504. i += 1
  505. continue
  506. b_["text"] = b["text"] + "\n" + b_["text"]
  507. b_["x0"] = min(b["x0"], b_["x0"])
  508. b_["x1"] = max(b["x1"], b_["x1"])
  509. b_["top"] = b["top"]
  510. self.boxes.pop(i)
  511. def _extract_table_figure(self, need_image, ZM, return_html, need_position):
  512. tables = {}
  513. figures = {}
  514. # extract figure and table boxes
  515. i = 0
  516. lst_lout_no = ""
  517. nomerge_lout_no = []
  518. while i < len(self.boxes):
  519. if "layoutno" not in self.boxes[i]:
  520. i += 1
  521. continue
  522. lout_no = str(self.boxes[i]["page_number"]) + \
  523. "-" + str(self.boxes[i]["layoutno"])
  524. if TableStructureRecognizer.is_caption(self.boxes[i]) or self.boxes[i]["layout_type"] in ["table caption", "title",
  525. "figure caption", "reference"]:
  526. nomerge_lout_no.append(lst_lout_no)
  527. if self.boxes[i]["layout_type"] == "table":
  528. if re.match(r"(数据|资料|图表)*来源[:: ]", self.boxes[i]["text"]):
  529. self.boxes.pop(i)
  530. continue
  531. if lout_no not in tables:
  532. tables[lout_no] = []
  533. tables[lout_no].append(self.boxes[i])
  534. self.boxes.pop(i)
  535. lst_lout_no = lout_no
  536. continue
  537. if need_image and self.boxes[i]["layout_type"] == "figure":
  538. if re.match(r"(数据|资料|图表)*来源[:: ]", self.boxes[i]["text"]):
  539. self.boxes.pop(i)
  540. continue
  541. if lout_no not in figures:
  542. figures[lout_no] = []
  543. figures[lout_no].append(self.boxes[i])
  544. self.boxes.pop(i)
  545. lst_lout_no = lout_no
  546. continue
  547. i += 1
  548. # merge table on different pages
  549. nomerge_lout_no = set(nomerge_lout_no)
  550. tbls = sorted([(k, bxs) for k, bxs in tables.items()],
  551. key=lambda x: (x[1][0]["top"], x[1][0]["x0"]))
  552. i = len(tbls) - 1
  553. while i - 1 >= 0:
  554. k0, bxs0 = tbls[i - 1]
  555. k, bxs = tbls[i]
  556. i -= 1
  557. if k0 in nomerge_lout_no:
  558. continue
  559. if bxs[0]["page_number"] == bxs0[0]["page_number"]:
  560. continue
  561. if bxs[0]["page_number"] - bxs0[0]["page_number"] > 1:
  562. continue
  563. mh = self.mean_height[bxs[0]["page_number"] - 1]
  564. if self._y_dis(bxs0[-1], bxs[0]) > mh * 23:
  565. continue
  566. tables[k0].extend(tables[k])
  567. del tables[k]
  568. def x_overlapped(a, b):
  569. return not any([a["x1"] < b["x0"], a["x0"] > b["x1"]])
  570. # find captions and pop out
  571. i = 0
  572. while i < len(self.boxes):
  573. c = self.boxes[i]
  574. # mh = self.mean_height[c["page_number"]-1]
  575. if not TableStructureRecognizer.is_caption(c):
  576. i += 1
  577. continue
  578. # find the nearest layouts
  579. def nearest(tbls):
  580. nonlocal c
  581. mink = ""
  582. minv = 1000000000
  583. for k, bxs in tbls.items():
  584. for b in bxs:
  585. if b.get("layout_type", "").find("caption") >= 0:
  586. continue
  587. y_dis = self._y_dis(c, b)
  588. x_dis = self._x_dis(
  589. c, b) if not x_overlapped(
  590. c, b) else 0
  591. dis = y_dis * y_dis + x_dis * x_dis
  592. if dis < minv:
  593. mink = k
  594. minv = dis
  595. return mink, minv
  596. tk, tv = nearest(tables)
  597. fk, fv = nearest(figures)
  598. #if min(tv, fv) > 2000:
  599. # i += 1
  600. # continue
  601. if tv < fv and tk:
  602. tables[tk].insert(0, c)
  603. logging.debug(
  604. "TABLE:" +
  605. self.boxes[i]["text"] +
  606. "; Cap: " +
  607. tk)
  608. elif fk:
  609. figures[fk].insert(0, c)
  610. logging.debug(
  611. "FIGURE:" +
  612. self.boxes[i]["text"] +
  613. "; Cap: " +
  614. tk)
  615. self.boxes.pop(i)
  616. res = []
  617. positions = []
  618. def cropout(bxs, ltype, poss):
  619. nonlocal ZM
  620. pn = set([b["page_number"] - 1 for b in bxs])
  621. if len(pn) < 2:
  622. pn = list(pn)[0]
  623. ht = self.page_cum_height[pn]
  624. b = {
  625. "x0": np.min([b["x0"] for b in bxs]),
  626. "top": np.min([b["top"] for b in bxs]) - ht,
  627. "x1": np.max([b["x1"] for b in bxs]),
  628. "bottom": np.max([b["bottom"] for b in bxs]) - ht
  629. }
  630. louts = [l for l in self.page_layout[pn] if l["type"] == ltype]
  631. ii = Recognizer.find_overlapped(b, louts, naive=True)
  632. if ii is not None:
  633. b = louts[ii]
  634. else:
  635. logging.warn(
  636. f"Missing layout match: {pn + 1},%s" %
  637. (bxs[0].get(
  638. "layoutno", "")))
  639. left, top, right, bott = b["x0"], b["top"], b["x1"], b["bottom"]
  640. poss.append((pn+self.page_from, left, right, top, bott))
  641. return self.page_images[pn] \
  642. .crop((left * ZM, top * ZM,
  643. right * ZM, bott * ZM))
  644. pn = {}
  645. for b in bxs:
  646. p = b["page_number"] - 1
  647. if p not in pn:
  648. pn[p] = []
  649. pn[p].append(b)
  650. pn = sorted(pn.items(), key=lambda x: x[0])
  651. imgs = [cropout(arr, ltype, poss) for p, arr in pn]
  652. pic = Image.new("RGB",
  653. (int(np.max([i.size[0] for i in imgs])),
  654. int(np.sum([m.size[1] for m in imgs]))),
  655. (245, 245, 245))
  656. height = 0
  657. for img in imgs:
  658. pic.paste(img, (0, int(height)))
  659. height += img.size[1]
  660. return pic
  661. # crop figure out and add caption
  662. for k, bxs in figures.items():
  663. txt = "\n".join([b["text"] for b in bxs])
  664. if not txt:
  665. continue
  666. poss = []
  667. res.append(
  668. (cropout(
  669. bxs,
  670. "figure", poss),
  671. [txt]))
  672. positions.append(poss)
  673. for k, bxs in tables.items():
  674. if not bxs:
  675. continue
  676. bxs = Recognizer.sort_Y_firstly(bxs, np.mean([(b["bottom"]-b["top"])/2 for b in bxs]))
  677. poss = []
  678. res.append((cropout(bxs, "table", poss),
  679. self.tbl_det.construct_table(bxs, html=return_html, is_english=self.is_english)))
  680. positions.append(poss)
  681. assert len(positions) == len(res)
  682. if need_position: return list(zip(res, positions))
  683. return res
  684. def proj_match(self, line):
  685. if len(line) <= 2:
  686. return
  687. if re.match(r"[0-9 ().,%%+/-]+$", line):
  688. return False
  689. for p, j in [
  690. (r"第[零一二三四五六七八九十百]+章", 1),
  691. (r"第[零一二三四五六七八九十百]+[条节]", 2),
  692. (r"[零一二三四五六七八九十百]+[、  ]", 3),
  693. (r"[\((][零一二三四五六七八九十百]+[)\)]", 4),
  694. (r"[0-9]+(、|\.[  ]|\.[^0-9])", 5),
  695. (r"[0-9]+\.[0-9]+(、|[.  ]|[^0-9])", 6),
  696. (r"[0-9]+\.[0-9]+\.[0-9]+(、|[  ]|[^0-9])", 7),
  697. (r"[0-9]+\.[0-9]+\.[0-9]+\.[0-9]+(、|[  ]|[^0-9])", 8),
  698. (r".{,48}[::??]$", 9),
  699. (r"[0-9]+)", 10),
  700. (r"[\((][0-9]+[)\)]", 11),
  701. (r"[零一二三四五六七八九十百]+是", 12),
  702. (r"[⚫•➢✓]", 12)
  703. ]:
  704. if re.match(p, line):
  705. return j
  706. return
  707. def _line_tag(self, bx, ZM):
  708. pn = [bx["page_number"]]
  709. top = bx["top"] - self.page_cum_height[pn[0] - 1]
  710. bott = bx["bottom"] - self.page_cum_height[pn[0] - 1]
  711. while bott * ZM > self.page_images[pn[-1] - 1].size[1]:
  712. bott -= self.page_images[pn[-1] - 1].size[1] / ZM
  713. pn.append(pn[-1] + 1)
  714. return "@@{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}##" \
  715. .format("-".join([str(p) for p in pn]),
  716. bx["x0"], bx["x1"], top, bott)
  717. def __filterout_scraps(self, boxes, ZM):
  718. def width(b):
  719. return b["x1"] - b["x0"]
  720. def height(b):
  721. return b["bottom"] - b["top"]
  722. def usefull(b):
  723. if b.get("layout_type"):
  724. return True
  725. if width(
  726. b) > self.page_images[b["page_number"] - 1].size[0] / ZM / 3:
  727. return True
  728. if b["bottom"] - b["top"] > self.mean_height[b["page_number"] - 1]:
  729. return True
  730. return False
  731. res = []
  732. while boxes:
  733. lines = []
  734. widths = []
  735. pw = self.page_images[boxes[0]["page_number"] - 1].size[0] / ZM
  736. mh = self.mean_height[boxes[0]["page_number"] - 1]
  737. mj = self.proj_match(
  738. boxes[0]["text"]) or boxes[0].get(
  739. "layout_type",
  740. "") == "title"
  741. def dfs(line, st):
  742. nonlocal mh, pw, lines, widths
  743. lines.append(line)
  744. widths.append(width(line))
  745. width_mean = np.mean(widths)
  746. mmj = self.proj_match(
  747. line["text"]) or line.get(
  748. "layout_type",
  749. "") == "title"
  750. for i in range(st + 1, min(st + 20, len(boxes))):
  751. if (boxes[i]["page_number"] - line["page_number"]) > 0:
  752. break
  753. if not mmj and self._y_dis(
  754. line, boxes[i]) >= 3 * mh and height(line) < 1.5 * mh:
  755. break
  756. if not usefull(boxes[i]):
  757. continue
  758. if mmj or \
  759. (self._x_dis(boxes[i], line) < pw / 10): \
  760. # and abs(width(boxes[i])-width_mean)/max(width(boxes[i]),width_mean)<0.5):
  761. # concat following
  762. dfs(boxes[i], i)
  763. boxes.pop(i)
  764. break
  765. try:
  766. if usefull(boxes[0]):
  767. dfs(boxes[0], 0)
  768. else:
  769. logging.debug("WASTE: " + boxes[0]["text"])
  770. except Exception as e:
  771. pass
  772. boxes.pop(0)
  773. mw = np.mean(widths)
  774. if mj or mw / pw >= 0.35 or mw > 200:
  775. res.append("\n".join([c["text"] + self._line_tag(c, ZM) for c in lines]))
  776. else:
  777. logging.debug("REMOVED: " +
  778. "<<".join([c["text"] for c in lines]))
  779. return "\n\n".join(res)
  780. @staticmethod
  781. def total_page_number(fnm, binary=None):
  782. try:
  783. pdf = pdfplumber.open(fnm) if not binary else pdfplumber.open(BytesIO(binary))
  784. return len(pdf.pages)
  785. except Exception as e:
  786. pdf = fitz.open(fnm) if not binary else fitz.open(stream=fnm, filetype="pdf")
  787. return len(pdf)
  788. def __images__(self, fnm, zoomin=3, page_from=0, page_to=299, callback=None):
  789. self.lefted_chars = []
  790. self.mean_height = []
  791. self.mean_width = []
  792. self.boxes = []
  793. self.garbages = {}
  794. self.page_cum_height = [0]
  795. self.page_layout = []
  796. self.page_from = page_from
  797. try:
  798. self.pdf = pdfplumber.open(fnm) if isinstance(fnm, str) else pdfplumber.open(BytesIO(fnm))
  799. self.page_images = [p.to_image(resolution=72 * zoomin).annotated for i, p in
  800. enumerate(self.pdf.pages[page_from:page_to])]
  801. self.page_chars = [[c for c in page.chars if self._has_color(c)] for page in self.pdf.pages[page_from:page_to]]
  802. self.total_page = len(self.pdf.pages)
  803. except Exception as e:
  804. self.pdf = fitz.open(fnm) if isinstance(fnm, str) else fitz.open(stream=fnm, filetype="pdf")
  805. self.page_images = []
  806. self.page_chars = []
  807. mat = fitz.Matrix(zoomin, zoomin)
  808. self.total_page = len(self.pdf)
  809. for i, page in enumerate(self.pdf):
  810. if i < page_from:continue
  811. if i >= page_to:break
  812. pix = page.get_pixmap(matrix=mat)
  813. img = Image.frombytes("RGB", [pix.width, pix.height],
  814. pix.samples)
  815. self.page_images.append(img)
  816. self.page_chars.append([])
  817. logging.info("Images converted.")
  818. 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))]
  819. if sum([1 if e else 0 for e in self.is_english]) > len(self.page_images) / 2:
  820. self.is_english = True
  821. else:
  822. self.is_english = False
  823. for i, img in enumerate(self.page_images):
  824. chars = self.page_chars[i] if not self.is_english else []
  825. self.mean_height.append(
  826. np.median(sorted([c["height"] for c in chars])) if chars else 0
  827. )
  828. self.mean_width.append(
  829. np.median(sorted([c["width"] for c in chars])) if chars else 8
  830. )
  831. self.page_cum_height.append(img.size[1] / zoomin)
  832. j = 0
  833. while j + 1 < len(chars):
  834. if chars[j]["text"] and chars[j + 1]["text"] \
  835. and re.match(r"[0-9a-zA-Z,.:;!%]+", chars[j]["text"] + chars[j + 1]["text"]) \
  836. and chars[j + 1]["x0"] - chars[j]["x1"] >= min(chars[j + 1]["width"],
  837. chars[j]["width"]) / 2:
  838. chars[j]["text"] += " "
  839. j += 1
  840. # if i > 0:
  841. # if not chars:
  842. # self.page_cum_height.append(img.size[1] / zoomin)
  843. # else:
  844. # self.page_cum_height.append(
  845. # np.max([c["bottom"] for c in chars]))
  846. self.__ocr(i + 1, img, chars, zoomin)
  847. if callback: callback(prog=(i+1)*0.6/len(self.page_images), msg="")
  848. if not self.is_english and not any([c for c in self.page_chars]) and self.boxes:
  849. bxes = [b for bxs in self.boxes for b in bxs]
  850. 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)))]))
  851. logging.info("Is it English:", self.is_english)
  852. self.page_cum_height = np.cumsum(self.page_cum_height)
  853. assert len(self.page_cum_height) == len(self.page_images) + 1
  854. def __call__(self, fnm, need_image=True, zoomin=3, return_html=False):
  855. self.__images__(fnm, zoomin)
  856. self._layouts_rec(zoomin)
  857. self._table_transformer_job(zoomin)
  858. self._text_merge()
  859. self._concat_downward()
  860. self._filter_forpages()
  861. tbls = self._extract_table_figure(need_image, zoomin, return_html, False)
  862. return self.__filterout_scraps(deepcopy(self.boxes), zoomin), tbls
  863. def remove_tag(self, txt):
  864. return re.sub(r"@@[\t0-9.-]+?##", "", txt)
  865. def crop(self, text, ZM=3, need_position=False):
  866. imgs = []
  867. poss = []
  868. for tag in re.findall(r"@@[0-9-]+\t[0-9.\t]+##", text):
  869. pn, left, right, top, bottom = tag.strip(
  870. "#").strip("@").split("\t")
  871. left, right, top, bottom = float(left), float(
  872. right), float(top), float(bottom)
  873. poss.append(([int(p) - 1 for p in pn.split("-")], left, right, top, bottom))
  874. if not poss:
  875. if need_position: return None, None
  876. return
  877. max_width = np.max([right-left for (_, left, right, _, _) in poss])
  878. GAP = 6
  879. pos = poss[0]
  880. poss.insert(0, ([pos[0][0]], pos[1], pos[2], max(0, pos[3]-120), max(pos[3]-GAP, 0)))
  881. pos = poss[-1]
  882. 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)))
  883. positions = []
  884. for ii, (pns, left, right, top, bottom) in enumerate(poss):
  885. right = left + max_width
  886. bottom *= ZM
  887. for pn in pns[1:]:
  888. bottom += self.page_images[pn - 1].size[1]
  889. imgs.append(
  890. self.page_images[pns[0]].crop((left * ZM, top * ZM,
  891. right *
  892. ZM, min(
  893. bottom, self.page_images[pns[0]].size[1])
  894. ))
  895. )
  896. if 0 < ii < len(poss)-1:
  897. positions.append((pns[0]+self.page_from, left, right, top, min(
  898. bottom, self.page_images[pns[0]].size[1])/ZM))
  899. bottom -= self.page_images[pns[0]].size[1]
  900. for pn in pns[1:]:
  901. imgs.append(
  902. self.page_images[pn].crop((left * ZM, 0,
  903. right * ZM,
  904. min(bottom,
  905. self.page_images[pn].size[1])
  906. ))
  907. )
  908. if 0 < ii < len(poss) - 1:
  909. positions.append((pn+self.page_from, left, right, 0, min(
  910. bottom, self.page_images[pn].size[1]) / ZM))
  911. bottom -= self.page_images[pn].size[1]
  912. if not imgs:
  913. if need_position: return None, None
  914. return
  915. height = 0
  916. for img in imgs:
  917. height += img.size[1] + GAP
  918. height = int(height)
  919. width = int(np.max([i.size[0] for i in imgs]))
  920. pic = Image.new("RGB",
  921. (width, height),
  922. (245, 245, 245))
  923. height = 0
  924. for ii, img in enumerate(imgs):
  925. if ii == 0 or ii + 1 == len(imgs):
  926. img = img.convert('RGBA')
  927. overlay = Image.new('RGBA', img.size, (0, 0, 0, 0))
  928. overlay.putalpha(128)
  929. img = Image.alpha_composite(img, overlay).convert("RGB")
  930. pic.paste(img, (0, int(height)))
  931. height += img.size[1] + GAP
  932. if need_position:
  933. return pic, positions
  934. return pic
  935. if __name__ == "__main__":
  936. pass