Metadata-Version: 1.2
Name: neurartist
Version: 0.2
Summary: Ready-to-use artistic deep learning algorithms
Home-page: https://github.com/gjorando/style-transfer
Author: Guillaume Jorandon
License: UNKNOWN
Description: Neurartist
        ==========
        
        A ready-to-use implementation of various Artistic Deep Learning
        Algorithms.
        
        -  *Image Style Transfer Using Convolutional Neural Networks*, Gatys et.
           al, 2016
        
        Installation
        ============
        
        ::
        
           # It is recommended to install torch/torchvision manually before this command, according to your hardware configuration (see below)
           pip install neurartist
        
        Please note that the use of a GPU is recommended, as CNN computations
        are pretty slow on a CPU.
        
        NB for GPU users: pip ships ``torch``/``torchvision`` with the Cuda
        Toolkit 9.0. If you use a more recent version of the Cuda Toolkit, see
        the `PyTorch website <https://pytorch.org/get-started/locally/>`__ for
        instructions on PyTorch installation with another version of the
        toolkit.
        
        Usage
        =====
        
        Console entrypoint
        ------------------
        
        ::
        
           # Then see the builtin help for usage details
           neurartist --help
        
        Library
        -------
        
        ::
        
           import neurartist
        
        To be added.
        
        Development
        ===========
        
        Anaconda is strongly recommended:
        
        ::
        
           conda create python=3.7 --name neurartist_env
           conda activate neurartist_env
        
           # with gpu
           conda install pytorch torchvision cudatoolkit=<your cudatoolkit version> -c pytorch
           conda install --file requirements.txt
        
           # with cpu
           conda install pytorch-cpu torchvision-cpu -c pytorch
           conda install --file requirements.txt
        
        You can then run the main entrypoint directly using:
        
        ::
        
           python -m neurartist --help
        
        Or build and install the wheel file with the ``--editable`` flag.
        
        TODO
        ----
        
        -  Documentation.
        -  Implement the remaining parts of the jupyter notebook.
        -  `Semantic segmentation as described in this article as to limit
           spillovers <https://arxiv.org/pdf/1703.07511.pdf>`__: different
           approach than guided gram matrices, but same idea of using spatial
           guidance channels that describe a semantic segmentation of our
           images.
        -  More deep-artistic algorithms.
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Artistic Software
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3
