import glob import re import os from io import StringIO from pathlib import Path import numpy as np import click import pandas as pd import requests from lxml import etree as ET from ocrd_models.ocrd_page import parse from ocrd_utils import bbox_from_points from qurator.utils.tsv import read_tsv, write_tsv, extract_doc_links from .ocr import get_conf_color from qurator.utils.ner import ner from qurator.utils.ned import ned @click.command() @click.argument('tsv-file', type=click.Path(exists=True), required=True, nargs=1) @click.argument('url-file', type=click.Path(exists=False), required=True, nargs=1) def extract_document_links(tsv_file, url_file): parts = extract_doc_links(tsv_file) urls = [part['url'] for part in parts] urls = pd.DataFrame(urls, columns=['url']) urls.to_csv(url_file, sep="\t", quoting=3, index=False) @click.command() @click.argument('tsv-file', type=click.Path(exists=True), required=True, nargs=1) @click.argument('annotated-tsv-file', type=click.Path(exists=False), required=True, nargs=1) def annotate_tsv(tsv_file, annotated_tsv_file): parts = extract_doc_links(tsv_file) annotated_parts = [] for part in parts: part_data = StringIO(part['header'] + part['text']) df = pd.read_csv(part_data, sep="\t", comment='#', quoting=3) df['url_id'] = len(annotated_parts) annotated_parts.append(df) df = pd.concat(annotated_parts) df.to_csv(annotated_tsv_file, sep="\t", quoting=3, index=False) @click.command() @click.argument('page-xml-file', type=click.Path(exists=True), required=True, nargs=1) @click.argument('tsv-out-file', type=click.Path(), required=True, nargs=1) @click.option('--purpose', type=click.Choice(['NERD', 'OCR'], case_sensitive=False), default="NERD", help="Purpose of output tsv file. " "\n\nNERD: NER/NED application/ground-truth creation. " "\n\nOCR: OCR application/ground-truth creation. " "\n\ndefault: NERD.") @click.option('--image-url', type=str, default='http://empty') @click.option('--ner-rest-endpoint', type=str, default=None, help="REST endpoint of sbb_ner service. See https://github.com/qurator-spk/sbb_ner for details. " "Only applicable in case of NERD.") @click.option('--ned-rest-endpoint', type=str, default=None, help="REST endpoint of sbb_ned service. See https://github.com/qurator-spk/sbb_ned for details. " "Only applicable in case of NERD.") @click.option('--noproxy', type=bool, is_flag=True, help='disable proxy. default: enabled.') @click.option('--scale-factor', type=float, default=1.0, help='default: 1.0') @click.option('--ned-threshold', type=float, default=None) @click.option('--min-confidence', type=float, default=None) @click.option('--max-confidence', type=float, default=None) @click.option('--ned-priority', type=int, default=1) def page2tsv(page_xml_file, tsv_out_file, purpose, image_url, ner_rest_endpoint, ned_rest_endpoint, noproxy, scale_factor, ned_threshold, min_confidence, max_confidence, ned_priority): if purpose == "NERD": out_columns = ['No.', 'TOKEN', 'NE-TAG', 'NE-EMB', 'ID', 'url_id', 'left', 'right', 'top', 'bottom', 'conf'] elif purpose == "OCR": out_columns = ['TEXT', 'url_id', 'left', 'right', 'top', 'bottom', 'conf', 'line_id'] if min_confidence is not None and max_confidence is not None: out_columns += ['ocrconf'] else: raise RuntimeError("Unknown purpose.") if noproxy: os.environ['no_proxy'] = '*' urls = [] if os.path.exists(tsv_out_file): parts = extract_doc_links(tsv_out_file) urls = [part['url'] for part in parts] else: pd.DataFrame([], columns=out_columns).to_csv(tsv_out_file, sep="\t", quoting=3, index=False) pcgts = parse(page_xml_file) tsv = [] line_info = [] for region_idx, region in enumerate(pcgts.get_Page().get_AllRegions(classes=['Text'], order='reading-order')): for text_line in region.get_TextLine(): left, top, right, bottom = [int(scale_factor * x) for x in bbox_from_points(text_line.get_Coords().points)] if min_confidence is not None and max_confidence is not None: conf = np.max([textequiv.conf for textequiv in text_line.get_TextEquiv()]) else: conf = np.nan line_info.append((len(urls), left, right, top, bottom, conf, text_line.id)) words = [word for word in text_line.get_Word()] if len(words) <= 0: for text_equiv in text_line.get_TextEquiv(): # transform OCR coordinates using `scale_factor` to derive # correct coordinates for the web presentation image left, top, right, bottom = [int(scale_factor * x) for x in bbox_from_points(text_line.get_Coords().points)] tsv.append((region_idx, len(line_info) - 1, left + (right - left) / 2.0, text_equiv.get_Unicode(), len(urls), left, right, top, bottom, text_line.id)) else: for word in words: for text_equiv in word.get_TextEquiv(): # transform OCR coordinates using `scale_factor` to derive # correct coordinates for the web presentation image left, top, right, bottom = [int(scale_factor * x) for x in bbox_from_points(word.get_Coords().points)] tsv.append((region_idx, len(line_info) - 1, left + (right - left) / 2.0, text_equiv.get_Unicode(), len(urls), left, right, top, bottom, text_line.id)) line_info = pd.DataFrame(line_info, columns=['url_id', 'left', 'right', 'top', 'bottom', 'conf', 'line_id']) if min_confidence is not None and max_confidence is not None: line_info['ocrconf'] = line_info.conf.map(lambda x: get_conf_color(x, min_confidence, max_confidence)) tsv = pd.DataFrame(tsv, columns=['rid', 'line', 'hcenter'] + ['TEXT', 'url_id', 'left', 'right', 'top', 'bottom', 'line_id']) if len(tsv) == 0: return with open(tsv_out_file, 'a') as f: f.write('# ' + image_url + '\n') vlinecenter = pd.DataFrame(tsv[['line', 'top']].groupby('line', sort=False).mean().top + (tsv[['line', 'bottom']].groupby('line', sort=False).mean().bottom - tsv[['line', 'top']].groupby('line', sort=False).mean().top) / 2, columns=['vlinecenter']) tsv = tsv.merge(vlinecenter, left_on='line', right_index=True) regions = [region.sort_values(['vlinecenter', 'hcenter']) for rid, region in tsv.groupby('rid', sort=False)] tsv = pd.concat(regions) if purpose == 'NERD': tsv['No.'] = 0 tsv['NE-TAG'] = 'O' tsv['NE-EMB'] = 'O' tsv['ID'] = '-' tsv['conf'] = '-' tsv = tsv.rename(columns={'TEXT': 'TOKEN'}) elif purpose == 'OCR': tsv = pd.DataFrame([(line, " ".join(part.TEXT.to_list())) for line, part in tsv.groupby('line')], columns=['line', 'TEXT']) tsv = tsv.merge(line_info, left_on='line', right_index=True) tsv = tsv[out_columns].reset_index(drop=True) try: if purpose == 'NERD' and ner_rest_endpoint is not None: tsv, ner_result = ner(tsv, ner_rest_endpoint) if ned_rest_endpoint is not None: tsv, _ = ned(tsv, ner_result, ned_rest_endpoint, threshold=ned_threshold, priority=ned_priority) tsv.to_csv(tsv_out_file, sep="\t", quoting=3, index=False, mode='a', header=False) except requests.HTTPError as e: print(e) @click.command() @click.option('--output-filename', '-o', help="Output filename. " "If omitted, PAGE-XML filename with .corrected.xml extension") @click.option('--keep-words', '-k', is_flag=True, help="Keep (out-of-date) Words of TextLines") @click.argument('page-file') @click.argument('tsv-file') def tsv2page(output_filename, keep_words, page_file, tsv_file): if not output_filename: output_filename = Path(page_file).stem + '.corrected.xml' ns = {'pc': 'http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15'} tsv = pd.read_csv(tsv_file, sep='\t', comment='#', quoting=3) tree = ET.parse(page_file) for _, row in tsv.iterrows(): el_textline = tree.find(f'//pc:TextLine[@id="{row.line_id}"]', namespaces=ns) el_textline.find('pc:TextEquiv/pc:Unicode', namespaces=ns).text = row.TEXT if not keep_words: for el_word in el_textline.findall('pc:Word', namespaces=ns): el_textline.remove(el_word) with open(output_filename, 'w', encoding='utf-8') as f: f.write(ET.tostring(tree, pretty_print=True).decode('utf-8')) @click.command() @click.option('--xls-file', type=click.Path(exists=True), default=None, help="Read parameters from xls-file. Expected columns: Filename, iiif_url, scale_factor.") @click.option('--directory', type=click.Path(exists=True), default=None, help="Search directory for PPN**/*.xml files. Extract PPN and file number into image-url.") @click.option('--purpose', type=click.Choice(['NERD', 'OCR'], case_sensitive=False), default="NERD", help="Purpose of output tsv file. " "\n\nNERD: NER/NED application/ground-truth creation. " "\n\nOCR: OCR application/ground-truth creation. " "\n\ndefault: NERD.") def make_page2tsv_commands(xls_file, directory, purpose): if xls_file is not None: if xls_file.endswith(".xls"): df = pd.read_excel(xls_file) else: df = pd.read_excel(xls_file, engine='openpyxl') df = df.dropna(how='all') for _, row in df.iterrows(): print('page2tsv $(OPTIONS) {}.xml {}.tsv --image-url={} --scale-factor={} --purpose={}'. format(row.Filename, row.Filename, row.iiif_url.replace('/full/full', '/left,top,width,height/full'), row.scale_factor, purpose)) elif directory is not None: for file in glob.glob('{}/**/*.xml'.format(directory), recursive=True): ma = re.match('(.*/(PPN[0-9X]+)/.*?([0-9]+).*?).xml', file) if ma: print('page2tsv {} {}.tsv ' '--image-url=https://content.staatsbibliothek-berlin.de/dc/' '{}-{:08d}/left,top,width,height/full/0/default.jpg --scale-factor=1.0 --purpose={}'. format(file, ma.group(1), ma.group(2), int(ma.group(3)), purpose))