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%global _empty_manifest_terminate_build 0
Name: python-lucidsonicdreams
Version: 0.4
Release: 1
Summary: Syncs GAN-generated visuals to music
License: MIT License
URL: https://github.com/mikaelalafriz/lucid-sonic-dreams
Source0: https://mirrors.aliyun.com/pypi/web/packages/4a/01/91ff8de2866a78435231966bf006eca06d7624c3f7cecce5b8c9b351d97d/lucidsonicdreams-0.4.tar.gz
BuildArch: noarch
%description
# Lucid Sonic Dreams
Lucid Sonic Dreams syncs GAN-generated visuals to music. By default, it uses [NVLabs StyleGAN2](https://github.com/NVlabs/stylegan2), with pre-trained models lifted from [Justin Pinkney's consolidated repository](https://github.com/justinpinkney/awesome-pretrained-stylegan2). Custom weights and other GAN architectures can be used as well.
Sample output can be found on [YouTube](https://youtu.be/l-nGC-ve7sI) and [Instagram](https://www.instagram.com/lucidsonicdreams/).
## Installation
This implementation has been teston on Python 3.6 and 3.7. As per NVLabs' TensorFlow implementation of StyleGAN2, TensorFlow 1.15 is required. TensorFlow 2.x is not supported.
To install, simply run:
```pip install lucidsonicdreams```
## Usage
You may refer to the [Lucid Sonic Dreams Tutorial Notebook](https://colab.research.google.com/drive/1Y5i50xSFIuN3V4Md8TB30_GOAtts7RQD?usp=sharing) for full parameter descriptions and sample code templates. A basic visualization snippet is also found below.
### Basic Visualization
```
from lucidsonicdreams import LucidSonicDream
L = LucidSonicDream(song = 'song.mp3',
style = 'abstract photos')
L.hallucinate(file_name = 'song.mp4')
```
%package -n python3-lucidsonicdreams
Summary: Syncs GAN-generated visuals to music
Provides: python-lucidsonicdreams
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-lucidsonicdreams
# Lucid Sonic Dreams
Lucid Sonic Dreams syncs GAN-generated visuals to music. By default, it uses [NVLabs StyleGAN2](https://github.com/NVlabs/stylegan2), with pre-trained models lifted from [Justin Pinkney's consolidated repository](https://github.com/justinpinkney/awesome-pretrained-stylegan2). Custom weights and other GAN architectures can be used as well.
Sample output can be found on [YouTube](https://youtu.be/l-nGC-ve7sI) and [Instagram](https://www.instagram.com/lucidsonicdreams/).
## Installation
This implementation has been teston on Python 3.6 and 3.7. As per NVLabs' TensorFlow implementation of StyleGAN2, TensorFlow 1.15 is required. TensorFlow 2.x is not supported.
To install, simply run:
```pip install lucidsonicdreams```
## Usage
You may refer to the [Lucid Sonic Dreams Tutorial Notebook](https://colab.research.google.com/drive/1Y5i50xSFIuN3V4Md8TB30_GOAtts7RQD?usp=sharing) for full parameter descriptions and sample code templates. A basic visualization snippet is also found below.
### Basic Visualization
```
from lucidsonicdreams import LucidSonicDream
L = LucidSonicDream(song = 'song.mp3',
style = 'abstract photos')
L.hallucinate(file_name = 'song.mp4')
```
%package help
Summary: Development documents and examples for lucidsonicdreams
Provides: python3-lucidsonicdreams-doc
%description help
# Lucid Sonic Dreams
Lucid Sonic Dreams syncs GAN-generated visuals to music. By default, it uses [NVLabs StyleGAN2](https://github.com/NVlabs/stylegan2), with pre-trained models lifted from [Justin Pinkney's consolidated repository](https://github.com/justinpinkney/awesome-pretrained-stylegan2). Custom weights and other GAN architectures can be used as well.
Sample output can be found on [YouTube](https://youtu.be/l-nGC-ve7sI) and [Instagram](https://www.instagram.com/lucidsonicdreams/).
## Installation
This implementation has been teston on Python 3.6 and 3.7. As per NVLabs' TensorFlow implementation of StyleGAN2, TensorFlow 1.15 is required. TensorFlow 2.x is not supported.
To install, simply run:
```pip install lucidsonicdreams```
## Usage
You may refer to the [Lucid Sonic Dreams Tutorial Notebook](https://colab.research.google.com/drive/1Y5i50xSFIuN3V4Md8TB30_GOAtts7RQD?usp=sharing) for full parameter descriptions and sample code templates. A basic visualization snippet is also found below.
### Basic Visualization
```
from lucidsonicdreams import LucidSonicDream
L = LucidSonicDream(song = 'song.mp3',
style = 'abstract photos')
L.hallucinate(file_name = 'song.mp4')
```
%prep
%autosetup -n lucidsonicdreams-0.4
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-lucidsonicdreams -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4-1
- Package Spec generated
|
