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import os |
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import re |
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from collections import Counter |
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from copy import deepcopy |
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import numpy as np |
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from huggingface_hub import snapshot_download |
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from api.utils.file_utils import get_project_base_directory |
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from deepdoc.vision import Recognizer |
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class LayoutRecognizer(Recognizer): |
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labels = [ |
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"_background_", |
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"Text", |
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"Title", |
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"Figure", |
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"Figure caption", |
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"Table", |
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"Table caption", |
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"Header", |
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"Footer", |
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"Reference", |
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"Equation", |
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] |
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def __init__(self, domain): |
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try: |
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model_dir = os.path.join( |
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get_project_base_directory(), |
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"rag/res/deepdoc") |
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super().__init__(self.labels, domain, model_dir) |
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except Exception as e: |
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model_dir = snapshot_download(repo_id="InfiniFlow/deepdoc", |
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local_dir=os.path.join(get_project_base_directory(), "rag/res/deepdoc"), |
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local_dir_use_symlinks=False) |
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super().__init__(self.labels, domain, model_dir) |
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self.garbage_layouts = ["footer", "header", "reference"] |
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def __call__(self, image_list, ocr_res, scale_factor=3, |
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thr=0.2, batch_size=16, drop=True): |
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def __is_garbage(b): |
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patt = [r"^•+$", r"(版权归©|免责条款|地址[::])", r"\.{3,}", "^[0-9]{1,2} / ?[0-9]{1,2}$", |
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r"^[0-9]{1,2} of [0-9]{1,2}$", "^http://[^ ]{12,}", |
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"(资料|数据)来源[::]", "[0-9a-z._-]+@[a-z0-9-]+\\.[a-z]{2,3}", |
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"\\(cid *: *[0-9]+ *\\)" |
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] |
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return any([re.search(p, b["text"]) for p in patt]) |
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layouts = super().__call__(image_list, thr, batch_size) |
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assert len(image_list) == len(ocr_res) |
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boxes = [] |
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assert len(image_list) == len(layouts) |
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garbages = {} |
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page_layout = [] |
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for pn, lts in enumerate(layouts): |
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bxs = ocr_res[pn] |
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lts = [{"type": b["type"], |
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"score": float(b["score"]), |
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"x0": b["bbox"][0] / scale_factor, "x1": b["bbox"][2] / scale_factor, |
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"top": b["bbox"][1] / scale_factor, "bottom": b["bbox"][-1] / scale_factor, |
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"page_number": pn, |
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} for b in lts if float(b["score"]) >= 0.8 or b["type"] not in self.garbage_layouts] |
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lts = self.sort_Y_firstly(lts, np.mean( |
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[l["bottom"] - l["top"] for l in lts]) / 2) |
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lts = self.layouts_cleanup(bxs, lts) |
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page_layout.append(lts) |
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def findLayout(ty): |
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nonlocal bxs, lts, self |
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lts_ = [lt for lt in lts if lt["type"] == ty] |
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i = 0 |
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while i < len(bxs): |
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if bxs[i].get("layout_type"): |
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i += 1 |
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continue |
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if __is_garbage(bxs[i]): |
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bxs.pop(i) |
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continue |
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ii = self.find_overlapped_with_threashold(bxs[i], lts_, |
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thr=0.4) |
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if ii is None: |
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bxs[i]["layout_type"] = "" |
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i += 1 |
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continue |
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lts_[ii]["visited"] = True |
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keep_feats = [ |
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lts_[ |
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ii]["type"] == "footer" and bxs[i]["bottom"] < image_list[pn].size[1] * 0.9 / scale_factor, |
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lts_[ |
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ii]["type"] == "header" and bxs[i]["top"] > image_list[pn].size[1] * 0.1 / scale_factor, |
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] |
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if drop and lts_[ |
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ii]["type"] in self.garbage_layouts and not any(keep_feats): |
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if lts_[ii]["type"] not in garbages: |
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garbages[lts_[ii]["type"]] = [] |
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garbages[lts_[ii]["type"]].append(bxs[i]["text"]) |
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bxs.pop(i) |
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continue |
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bxs[i]["layoutno"] = f"{ty}-{ii}" |
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bxs[i]["layout_type"] = lts_[ii]["type"] if lts_[ |
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ii]["type"] != "equation" else "figure" |
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i += 1 |
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for lt in ["footer", "header", "reference", "figure caption", |
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"table caption", "title", "table", "text", "figure", "equation"]: |
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findLayout(lt) |
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for i, lt in enumerate( |
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[lt for lt in lts if lt["type"] in ["figure", "equation"]]): |
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if lt.get("visited"): |
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continue |
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lt = deepcopy(lt) |
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del lt["type"] |
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lt["text"] = "" |
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lt["layout_type"] = "figure" |
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lt["layoutno"] = f"figure-{i}" |
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bxs.append(lt) |
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boxes.extend(bxs) |
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ocr_res = boxes |
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garbag_set = set() |
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for k in garbages.keys(): |
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garbages[k] = Counter(garbages[k]) |
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for g, c in garbages[k].items(): |
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if c > 1: |
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garbag_set.add(g) |
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ocr_res = [b for b in ocr_res if b["text"].strip() not in garbag_set] |
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return ocr_res, page_layout |
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