🧹 sbb_textline_docker: Rename to sbb_textline_detector

Dockerfile

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+FROM python:3
+
+ADD main.py /
+ADD requirements.txt /
+
+RUN pip install --proxy=http-proxy.sbb.spk-berlin.de:3128 -r requirements.txt
+
+ENTRYPOINT ["python", "./main.py"]

README.md

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+# Textline-Recognition
+
+***
+
+# 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 ./
+```
+
+***
+
+Perform document structure and textline analysis on a
+scanned document image and save the result as PAGE XML.
+
+### Usage
+```
+text_line_recognition --help
+```
+
+

requirements.txt

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+opencv-python
+numpy<=1.14.5
+matplotlib
+seaborn
+tqdm
+keras
+shapely
+scikit-learn
+tensorflow-gpu < 2.0
+scipy

setup.py

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+from io import open
+from setuptools import find_packages, setup
+
+with open('requirements.txt') as fp:
+    install_requires = fp.read()
+
+setup(
+    name="qurator-sbb-textline",
+    version="0.0.1",
+    author="The Qurator Team",
+    author_email="qurator@sbb.spk-berlin.de",
+    description="Qurator",
+    long_description=open("README.md", "r", encoding='utf-8').read(),
+    long_description_content_type="text/markdown",
+    keywords='qurator',
+    license='Apache',
+    url="https://qurator.ai",
+    packages=find_packages(exclude=["*.tests", "*.tests.*",
+                                    "tests.*", "tests"]),
+    install_requires=install_requires,
+    entry_points={
+      'console_scripts': [
+        "text_line_recognition=main:main",
+      ]
+    },
+    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',
+    ],
+)