Spaces:
Paused
Paused
| # 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 os | |
| import random | |
| import xgboost as xgb | |
| from io import BytesIO | |
| import torch | |
| import re | |
| import pdfplumber | |
| import logging | |
| from PIL import Image, ImageDraw | |
| import numpy as np | |
| from timeit import default_timer as timer | |
| from pypdf import PdfReader as pdf2_read | |
| 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 | |
| logging.getLogger("pdfminer").setLevel(logging.WARNING) | |
| 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 torch.cuda.is_available(): | |
| self.updown_cnt_mdl.set_param({"device": "cuda"}) | |
| 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 as e: | |
| 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 | |
| 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.info("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-Z,.?;:!%%]", 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): | |
| print( | |
| b["text"], | |
| b_["text"], | |
| any(feats), | |
| any(concatting_feats), | |
| any(detach_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}$", down["text"]) \ | |
| or not down["text"].strip(): | |
| i += 1 | |
| continue | |
| if not down["text"].strip(): | |
| i += 1 | |
| continue | |
| if up["x1"] < down["x0"] - 10 * \ | |
| mw or up["x0"] > down["x1"] + 10 * mw: | |
| i += 1 | |
| continue | |
| if i - dp < 5 and up.get("layout_type") == "text": | |
| if up.get("layoutno", "1") == down.get( | |
| "layoutno", "2"): | |
| dfs(down, i + 1) | |
| boxes.pop(i) | |
| return | |
| i += 1 | |
| continue | |
| fea = self._updown_concat_features(up, down) | |
| if self.updown_cnt_mdl.predict( | |
| xgb.DMatrix([fea]))[0] <= 0.5: | |
| i += 1 | |
| continue | |
| dfs(down, i + 1) | |
| boxes.pop(i) | |
| return | |
| dfs(boxes[0], 1) | |
| boxes.pop(0) | |
| if chunks: | |
| blocks.append(chunks) | |
| # concat within each block | |
| boxes = [] | |
| for b in blocks: | |
| if len(b) == 1: | |
| boxes.append(b[0]) | |
| continue | |
| t = b[0] | |
| for c in b[1:]: | |
| t["text"] = t["text"].strip() | |
| c["text"] = c["text"].strip() | |
| if not c["text"]: | |
| continue | |
| if t["text"] and re.match( | |
| r"[0-9\.a-zA-Z]+$", 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 as e: | |
| 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) | |
| 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 as e: | |
| logging.error(str(e)) | |
| 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_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 as e: | |
| logging.error(str(e)) | |
| 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(f"Miss outlines") | |
| logging.info("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): | |
| 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) | |
| 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) | |
| 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.info("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 as e: | |
| logging.warning(f"Outlines exception: {e}") | |
| if not self.outlines: | |
| logging.warning(f"Miss outlines") | |
| return [(l, "") for l in lines], [] | |
| def crop(self, ck, need_position): | |
| raise NotImplementedError | |
| def remove_tag(txt): | |
| raise NotImplementedError | |
| if __name__ == "__main__": | |
| pass | |