Remove extras_requires by using TF > 2.0

As the code runs with any tensorflow version from 2.0 to 2.5, the
tensorflow-gpu package is only needed if it isn't possible to use
TF>=2.1 for some external reason. In that case, it's up to the user to
install the gpu version, as this simplifies installation for all other
cases.

README.md

@@ -4,10 +4,11 @@
 
 Python dependencies are specified in `requirements.txt` / `setup.py`.
 
-You must install the package via pip with either `ocr4all_pixel_classifier[tf_cpu]` to
-use CPU version of tensorflow or `ocr4all_pixel_classifier[tf_gpu]` to use GPU (CUDA)
-version of tensorflow. For the latter, your system should be set up with CUDA 9
-and CuDNN 7.
+The package is tested with Tensorflow 2.0 up to 2.5. If you want to use a GPU,
+you'll have to set up your system with the CUDA and CuDNN versions [matching
+your used Tensorflow version](https://www.tensorflow.org/install/source#gpu).
+If using Tensorflow older than 2.1 for some reason, you'll additionaly have to
+replace the `tensorflow` package with `tensorflow-gpu` manually.
 
 ## Usage
 

requirements.in

@@ -8,4 +8,4 @@ dataclasses
 efficientnet
 lxml
 ocr4all-pylib>=0.2.0
-tensorflow>=2.0.0
+tensorflow >= 2.0.0, <= 2.5.0

setup.py

@@ -14,11 +14,7 @@ setup(
     author="Christoph Wick, Alexander Hartelt, Alexander Gehrke",
     author_email="christoph.wick@informatik.uni-wuerzburg.de, alexander.hartelt@informatik.uni-wuerzburg.de, alexander.gehrke@informatik.uni-wuerzburg.de",
     url="https://gitlab2.informatik.uni-wuerzburg.de/chw71yx/page-segmentation.git",
-    install_requires=open("requirements.in").read().split(),
-    extras_require={
-        'tf_cpu': ['tensorflow>=2.0.0,<2.1.0'],
-        'tf_gpu': ['tensorflow-gpu>=2.0.0,<2.1.0'],
-    },
+    install_requires=open("requirements.in").read().split("\n"),
     classifiers=[
         "Programming Language :: Python :: 3",
         "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",