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Ready-to-use artistic deep learning algorithms

Project description


A ready-to-use implementation of various Artistic Deep Learning Algorithms.

  • Image Style Transfer Using Convolutional Neural Networks, Gatys et. al, 2016


# 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 for instructions on PyTorch installation with another version of the toolkit.


Console entrypoint

# Then see the builtin help for usage details
neurartist --help


import neurartist

To be added.


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.


Project details

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Files for neurartist, version 0.1
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Filename, size neurartist-0.1-py2.py3-none-any.whl (20.1 kB) File type Wheel Python version py2.py3 Upload date Hashes View
Filename, size neurartist-0.1.tar.gz (7.2 kB) File type Source Python version None Upload date Hashes View

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