extract TSV Tools from qurator-spk/neath
cneud
4 years ago
parent
92a81a869c
commit
59a1e81243
@ -1,2 +1,61 @@
|
||||
# page2tsv
|
||||
PAGE-XML to TSV
|
||||
# TSV - Processing Tools
|
||||
|
||||
## Installation:
|
||||
|
||||
Setup virtual environment:
|
||||
```
|
||||
virtualenv --python=python3.6 venv
|
||||
```
|
||||
|
||||
Activate virtual environment:
|
||||
```
|
||||
source venv/bin/activate
|
||||
```
|
||||
|
||||
Upgrade pip:
|
||||
```
|
||||
pip install -U pip
|
||||
```
|
||||
|
||||
Install package together with its dependencies in development mode:
|
||||
```
|
||||
pip install -e ./
|
||||
```
|
||||
|
||||
## PAGE-XML to TSV Transformation:
|
||||
|
||||
Create a TSV file from OCR in PAGE-XML format (with word segmentation):
|
||||
|
||||
```
|
||||
page2tsv PAGE1.xml PAGE.tsv --image-url=http://link-to-corresponding-image-1
|
||||
```
|
||||
|
||||
In order to create a TSV file for multiple PAGE XML files just perform successive calls
|
||||
of the tool using the same TSV file:
|
||||
|
||||
```
|
||||
page2tsv PAGE1.xml PAGE.tsv --image-url=http://link-to-corresponding-image-1
|
||||
page2tsv PAGE2.xml PAGE.tsv --image-url=http://link-to-corresponding-image-2
|
||||
page2tsv PAGE3.xml PAGE.tsv --image-url=http://link-to-corresponding-image-3
|
||||
page2tsv PAGE4.xml PAGE.tsv --image-url=http://link-to-corresponding-image-4
|
||||
page2tsv PAGE5.xml PAGE.tsv --image-url=http://link-to-corresponding-image-5
|
||||
...
|
||||
...
|
||||
...
|
||||
```
|
||||
|
||||
For instance, for the file assets/example.xml:
|
||||
|
||||
```
|
||||
page2tsv example.xml example.tsv --image-url=http://content.staatsbibliothek-berlin.de/zefys/SNP27646518-18800101-0-3-0-0/left,top,width,height/full/0/default.jpg
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Processing of already existing TSV files:
|
||||
|
||||
Create a URL-annotated TSV file from an existing TSV file:
|
||||
|
||||
```
|
||||
annotate-tsv enp_DE.tsv enp_DE-annotated.tsv
|
||||
```
|
||||
|
||||
@ -0,0 +1,198 @@
|
||||
import re
|
||||
import click
|
||||
import pandas as pd
|
||||
from io import StringIO
|
||||
import os
|
||||
import xml.etree.ElementTree as ET
|
||||
import requests
|
||||
import unicodedata
|
||||
import json
|
||||
|
||||
|
||||
@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)
|
||||
|
||||
|
||||
def extract_doc_links(tsv_file):
|
||||
|
||||
parts = []
|
||||
|
||||
header = None
|
||||
|
||||
with open(tsv_file, 'r') as f:
|
||||
|
||||
text = []
|
||||
url = None
|
||||
|
||||
for line in f:
|
||||
|
||||
if header is None:
|
||||
header = "\t".join(line.split()) + '\n'
|
||||
continue
|
||||
|
||||
urls = [url for url in
|
||||
re.findall(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', line)]
|
||||
|
||||
if len(urls) > 0:
|
||||
if url is not None:
|
||||
parts.append({"url": url, 'header': header, 'text': "".join(text)})
|
||||
text = []
|
||||
|
||||
url = urls[-1]
|
||||
else:
|
||||
if url is None:
|
||||
continue
|
||||
|
||||
line = '\t'.join(line.split())
|
||||
|
||||
if line.count('\t') == 2:
|
||||
|
||||
line = "\t" + line
|
||||
|
||||
if line.count('\t') >= 3:
|
||||
|
||||
text.append(line + '\n')
|
||||
|
||||
continue
|
||||
|
||||
if line.startswith('#'):
|
||||
continue
|
||||
|
||||
if len(line) == 0:
|
||||
continue
|
||||
|
||||
print('Line error: |', line, '|Number of Tabs: ', line.count('\t'))
|
||||
|
||||
if url is not None:
|
||||
parts.append({"url": url, 'header': header, 'text': "".join(text)})
|
||||
|
||||
return parts
|
||||
|
||||
|
||||
def ner(tsv, ner_rest_endpoint):
|
||||
|
||||
resp = requests.post(url=ner_rest_endpoint, json={'text': " ".join(tsv.TOKEN.tolist())})
|
||||
|
||||
def iterate_ner_results(result_sentences):
|
||||
|
||||
for sen in result_sentences:
|
||||
|
||||
for token in sen:
|
||||
|
||||
yield unicodedata.normalize('NFC', token['word']), token['prediction'], False
|
||||
|
||||
yield '', '', True
|
||||
|
||||
result_sequence = iterate_ner_results(json.loads(resp.content))
|
||||
|
||||
tsv_result = []
|
||||
for idx, row in tsv.iterrows():
|
||||
|
||||
row_token = unicodedata.normalize('NFC', row.TOKEN.replace(' ', ''))
|
||||
|
||||
ner_token_concat = ''
|
||||
while row_token != ner_token_concat:
|
||||
|
||||
ner_token, ner_tag, sentence_break = next(result_sequence)
|
||||
ner_token_concat += ner_token
|
||||
|
||||
assert len(row_token) >= len(ner_token_concat)
|
||||
|
||||
if sentence_break:
|
||||
tsv_result.append((0, '', 'O', 'O', '-', row.url_id, row.left, row.right, row.top, row.bottom))
|
||||
else:
|
||||
tsv_result.append((0, ner_token, ner_tag, 'O', '-', row.url_id, row.left, row.right, row.top,
|
||||
row.bottom))
|
||||
|
||||
return pd.DataFrame(tsv_result, columns=['No.', 'TOKEN', 'NE-TAG', 'NE-EMB', 'GND-ID', 'url_id',
|
||||
'left', 'right', 'top', 'bottom'])
|
||||
|
||||
|
||||
@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('--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.")
|
||||
@click.option('--noproxy', type=bool, is_flag=True, help='disable proxy. default: enabled.')
|
||||
def page2tsv(page_xml_file, tsv_out_file, image_url, ner_rest_endpoint, noproxy):
|
||||
|
||||
if noproxy:
|
||||
os.environ['no_proxy'] = '*'
|
||||
|
||||
tree = ET.parse(page_xml_file)
|
||||
xmlns = tree.getroot().tag.split('}')[0].strip('{')
|
||||
|
||||
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=['No.', 'TOKEN', 'NE-TAG', 'NE-EMB', 'GND-ID', 'url_id', 'left', 'right', 'top',
|
||||
'bottom']). to_csv(tsv_out_file, sep="\t", quoting=3, index=False)
|
||||
|
||||
tsv = []
|
||||
for words in tree.findall('.//{%s}Word' % xmlns):
|
||||
for word in words.findall('.//{%s}Unicode' % xmlns):
|
||||
text = word.text
|
||||
for coords in words.findall('.//{%s}Coords' % xmlns):
|
||||
|
||||
# transform the OCR coordinates by 0.5685 to derive the correct coords for the web presentation image
|
||||
points = [int(0.5685 * float(pos)) for p in coords.attrib['points'].split(' ') for pos in p.split(',')]
|
||||
|
||||
x_points = [points[i] for i in range(0, len(points), 2)]
|
||||
y_points = [points[i] for i in range(1, len(points), 2)]
|
||||
|
||||
left = min(x_points)
|
||||
right = max(x_points)
|
||||
top = min(y_points)
|
||||
bottom = max(y_points)
|
||||
|
||||
tsv.append((0, text, 'O', 'O', '-', len(urls), left, right, top, bottom))
|
||||
|
||||
with open(tsv_out_file, 'a') as f:
|
||||
|
||||
f.write('# ' + image_url + '\n')
|
||||
|
||||
tsv = pd.DataFrame(tsv, columns=['No.', 'TOKEN', 'NE-TAG', 'NE-EMB', 'GND-ID',
|
||||
'url_id', 'left', 'right', 'top', 'bottom'])
|
||||
|
||||
if ner_rest_endpoint is not None:
|
||||
tsv = ner(tsv, ner_rest_endpoint)
|
||||
|
||||
tsv.to_csv(tsv_out_file, sep="\t", quoting=3, index=False, mode='a', header=False)
|
||||
@ -0,0 +1,4 @@
|
||||
numpy
|
||||
pandas
|
||||
click
|
||||
requests
|
||||
@ -0,0 +1,36 @@
|
||||
from io import open
|
||||
from setuptools import find_packages, setup
|
||||
|
||||
with open('requirements.txt') as fp:
|
||||
install_requires = fp.read()
|
||||
|
||||
setup(
|
||||
name="neath",
|
||||
version="0.0.1",
|
||||
author="",
|
||||
author_email="qurator@sbb.spk-berlin.de",
|
||||
description="neath",
|
||||
long_description=open("README.md", "r", encoding='utf-8').read(),
|
||||
long_description_content_type="text/markdown",
|
||||
keywords='qurator',
|
||||
license='Apache License 2.0',
|
||||
url="https://github.com/qurator-spk/neath",
|
||||
packages=find_packages(exclude=["*.tests", "*.tests.*",
|
||||
"tests.*", "tests"]),
|
||||
install_requires=install_requires,
|
||||
entry_points={
|
||||
'console_scripts': [
|
||||
"extract-doc-links=cli:extract_document_links",
|
||||
"annotate-tsv=cli:annotate_tsv",
|
||||
"page2tsv=cli:page2tsv"
|
||||
]
|
||||
},
|
||||
python_requires='>=3.6.0',
|
||||
tests_require=['pytest'],
|
||||
classifiers=[
|
||||
'Intended Audience :: Science/Research',
|
||||
'License :: OSI Approved :: Apache Software License',
|
||||
'Programming Language :: Python :: 3',
|
||||
'Topic :: Scientific/Engineering :: Artificial Intelligence',
|
||||
],
|
||||
)
|
||||
Loading…
Reference in New Issue