%global _empty_manifest_terminate_build 0 Name: python-ml4a Version: 0.1.3 Release: 1 Summary: A toolkit for making art with machine learning, including an API for popular deep learning models, recipes for combining them, and a suite of educational examples License: MIT URL: http://github.com/ml4a/ml4a Source0: https://mirrors.aliyun.com/pypi/web/packages/80/1a/7452b2ec23b55f8ad283d99c0ba57ecbcc332262bb2ca74837b78e446622/ml4a-0.1.3.tar.gz BuildArch: noarch Requires: python3-bs4 Requires: python3-dill Requires: python3-imutils Requires: python3-inflect Requires: python3-face-recognition Requires: python3-gdown Requires: python3-ipython Requires: python3-ipywidgets Requires: python3-librosa Requires: python3-lxml Requires: python3-matplotlib Requires: python3-moviepy Requires: python3-ninja Requires: python3-noise Requires: python3-numba Requires: python3-numpy Requires: python3-omegaconf Requires: python3-opencv-python Requires: python3-Pillow Requires: python3-pytorch-lightning Requires: python3-psutil Requires: python3-scikit-image Requires: python3-scikit-learn Requires: python3-tensorflow-gpu Requires: python3-torch Requires: python3-torchvision Requires: python3-tqdm Requires: python3-unidecode Requires: python3-yacs %description


ml4a
Machine Learning for Artists

[ml4a](https://ml4a.net) is a Python library for making art with machine learning. It features: * an API wrapping popular deep learning models with creative applications, including [StyleGAN2](https://github.com/NVLabs/stylegan2/), [SPADE](https://github.com/NVlabs/SPADE), [Neural Style Transfer](https://github.com/genekogan/neural_style), [DeepDream](https://github.com/genekogan/deepdream), and [many others](https://github.com/ml4a/ml4a/tree/master/ml4a/models/submodules). * a collection of [Jupyter notebooks](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/examples) explaining the basics of deep learning for beginners, and providing [recipes for using the materials creatively](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/examples/models). ## Example ml4a bundles the source code of various open source repositories as [git submodules](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/ml4a/models/submodules) and contains wrappers to streamline and simplify them. For example, to generate sample images with StyleGAN2: ``` from ml4a import image from ml4a.models import stylegan network_pkl = stylegan.get_pretrained_model('ffhq') stylegan.load_model(network_pkl) samples = stylegan.random_sample(3, labels=None, truncation=1.0) image.display(samples) ``` Every model in `ml4a.models`, including the `stylegan` module above, imports all of the original repository's code into its namespace, allowing low-level access. ## Support ml4a ### Become a sponsor You can support ml4a by [donating through GitHub sponsors](https://github.com/sponsors/ml4a/). ### How to contribute Start by joining the [Slack](https://join.slack.com/t/ml-4a/shared_invite/enQtNjA4MjgzODk1MjA3LTlhYjQ5NWQ2OTNlODZiMDRjZTFmNDZiYjlmZWYwNGM0YjIxNjE3Yjc0NWVjMmVlZjNmZDhmYTkzZjk0ZTg1ZGM%3E) or following us on [Twitter](https://www.twitter.com/ml4a_). Contribute to the codebase, or help write tutorials. ## License ml4a itself is [licensed MIT](https://github.com/ml4a/ml4a/blob/master/LICENSE), but you are also bound to the licenses of any [models](https://github.com/ml4a/ml4a/tree/master/ml4a/models/submodules) you use. %package -n python3-ml4a Summary: A toolkit for making art with machine learning, including an API for popular deep learning models, recipes for combining them, and a suite of educational examples Provides: python-ml4a BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-ml4a


ml4a
Machine Learning for Artists

[ml4a](https://ml4a.net) is a Python library for making art with machine learning. It features: * an API wrapping popular deep learning models with creative applications, including [StyleGAN2](https://github.com/NVLabs/stylegan2/), [SPADE](https://github.com/NVlabs/SPADE), [Neural Style Transfer](https://github.com/genekogan/neural_style), [DeepDream](https://github.com/genekogan/deepdream), and [many others](https://github.com/ml4a/ml4a/tree/master/ml4a/models/submodules). * a collection of [Jupyter notebooks](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/examples) explaining the basics of deep learning for beginners, and providing [recipes for using the materials creatively](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/examples/models). ## Example ml4a bundles the source code of various open source repositories as [git submodules](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/ml4a/models/submodules) and contains wrappers to streamline and simplify them. For example, to generate sample images with StyleGAN2: ``` from ml4a import image from ml4a.models import stylegan network_pkl = stylegan.get_pretrained_model('ffhq') stylegan.load_model(network_pkl) samples = stylegan.random_sample(3, labels=None, truncation=1.0) image.display(samples) ``` Every model in `ml4a.models`, including the `stylegan` module above, imports all of the original repository's code into its namespace, allowing low-level access. ## Support ml4a ### Become a sponsor You can support ml4a by [donating through GitHub sponsors](https://github.com/sponsors/ml4a/). ### How to contribute Start by joining the [Slack](https://join.slack.com/t/ml-4a/shared_invite/enQtNjA4MjgzODk1MjA3LTlhYjQ5NWQ2OTNlODZiMDRjZTFmNDZiYjlmZWYwNGM0YjIxNjE3Yjc0NWVjMmVlZjNmZDhmYTkzZjk0ZTg1ZGM%3E) or following us on [Twitter](https://www.twitter.com/ml4a_). Contribute to the codebase, or help write tutorials. ## License ml4a itself is [licensed MIT](https://github.com/ml4a/ml4a/blob/master/LICENSE), but you are also bound to the licenses of any [models](https://github.com/ml4a/ml4a/tree/master/ml4a/models/submodules) you use. %package help Summary: Development documents and examples for ml4a Provides: python3-ml4a-doc %description help


ml4a
Machine Learning for Artists

[ml4a](https://ml4a.net) is a Python library for making art with machine learning. It features: * an API wrapping popular deep learning models with creative applications, including [StyleGAN2](https://github.com/NVLabs/stylegan2/), [SPADE](https://github.com/NVlabs/SPADE), [Neural Style Transfer](https://github.com/genekogan/neural_style), [DeepDream](https://github.com/genekogan/deepdream), and [many others](https://github.com/ml4a/ml4a/tree/master/ml4a/models/submodules). * a collection of [Jupyter notebooks](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/examples) explaining the basics of deep learning for beginners, and providing [recipes for using the materials creatively](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/examples/models). ## Example ml4a bundles the source code of various open source repositories as [git submodules](https://github.com/ml4a/ml4a-guides/tree/ml4a.net/ml4a/models/submodules) and contains wrappers to streamline and simplify them. For example, to generate sample images with StyleGAN2: ``` from ml4a import image from ml4a.models import stylegan network_pkl = stylegan.get_pretrained_model('ffhq') stylegan.load_model(network_pkl) samples = stylegan.random_sample(3, labels=None, truncation=1.0) image.display(samples) ``` Every model in `ml4a.models`, including the `stylegan` module above, imports all of the original repository's code into its namespace, allowing low-level access. ## Support ml4a ### Become a sponsor You can support ml4a by [donating through GitHub sponsors](https://github.com/sponsors/ml4a/). ### How to contribute Start by joining the [Slack](https://join.slack.com/t/ml-4a/shared_invite/enQtNjA4MjgzODk1MjA3LTlhYjQ5NWQ2OTNlODZiMDRjZTFmNDZiYjlmZWYwNGM0YjIxNjE3Yjc0NWVjMmVlZjNmZDhmYTkzZjk0ZTg1ZGM%3E) or following us on [Twitter](https://www.twitter.com/ml4a_). Contribute to the codebase, or help write tutorials. ## License ml4a itself is [licensed MIT](https://github.com/ml4a/ml4a/blob/master/LICENSE), but you are also bound to the licenses of any [models](https://github.com/ml4a/ml4a/tree/master/ml4a/models/submodules) you use. %prep %autosetup -n ml4a-0.1.3 %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-ml4a -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Jun 20 2023 Python_Bot - 0.1.3-1 - Package Spec generated