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authorCoprDistGit <infra@openeuler.org>2023-05-05 15:07:41 +0000
committerCoprDistGit <infra@openeuler.org>2023-05-05 15:07:41 +0000
commitb720cacd373e65da33167fa79108d91ba2bbc730 (patch)
treec3c3cab8740691d01b761e5fa52895a4c3064d48
parenta24572c2e1289416bdafbbb363d82cef018e3da0 (diff)
automatic import of python-keras-unet-collectionopeneuler20.03
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-rw-r--r--python-keras-unet-collection.spec117
-rw-r--r--sources1
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+/keras-unet-collection-0.1.13.tar.gz
diff --git a/python-keras-unet-collection.spec b/python-keras-unet-collection.spec
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+%global _empty_manifest_terminate_build 0
+Name: python-keras-unet-collection
+Version: 0.1.13
+Release: 1
+Summary: The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.
+License: MIT License
+URL: https://github.com/yingkaisha/keras-unet-collection
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/de/ff/327b15609e498354cc15909280953b72f35854d33bc5fb9554e300e7968a/keras-unet-collection-0.1.13.tar.gz
+BuildArch: noarch
+
+
+%description
+`keras_unet_collection.models` contains functions that configure keras models with hyper-parameter options.
+* Pre-trained ImageNet backbones are supported for U-net, U-net++, UNET 3+, Attention U-net, and TransUNET.
+* Deep supervision is supported for U-net++, UNET 3+, and U^2-Net.
+* See the [User guide](https://github.com/yingkaisha/keras-unet-collection/blob/main/examples/user_guide_models.ipynb) for other options and use cases.
+| `keras_unet_collection.models` | Name | Reference |
+|:---------------|:----------------|:----------------|
+| `unet_2d` | U-net | [Ronneberger et al. (2015)](https://link.springer.com/chapter/10.1007/978-3-319-24574-4_28) |
+| `vnet_2d` | V-net (modified for 2-d inputs) | [Milletari et al. (2016)](https://arxiv.org/abs/1606.04797) |
+| `unet_plus_2d` | U-net++ | [Zhou et al. (2018)](https://link.springer.com/chapter/10.1007/978-3-030-00889-5_1) |
+| `r2_unet_2d` | R2U-Net | [Alom et al. (2018)](https://arxiv.org/abs/1802.06955) |
+| `att_unet_2d` | Attention U-net | [Oktay et al. (2018)](https://arxiv.org/abs/1804.03999) |
+| `resunet_a_2d` | ResUnet-a | [Diakogiannis et al. (2020)](https://doi.org/10.1016/j.isprsjprs.2020.01.013) |
+| `u2net_2d` | U^2-Net | [Qin et al. (2020)](https://arxiv.org/abs/2005.09007) |
+| `unet_3plus_2d` | UNET 3+ | [Huang et al. (2020)](https://arxiv.org/abs/2004.08790) |
+| `transunet_2d` | TransUNET | [Chen et al. (2021)](https://arxiv.org/abs/2102.04306) |
+| `swin_unet_2d` | Swin-UNET | [Hu et al. (2021)](https://arxiv.org/abs/2105.05537) |
+
+%package -n python3-keras-unet-collection
+Summary: The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.
+Provides: python-keras-unet-collection
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-pip
+%description -n python3-keras-unet-collection
+`keras_unet_collection.models` contains functions that configure keras models with hyper-parameter options.
+* Pre-trained ImageNet backbones are supported for U-net, U-net++, UNET 3+, Attention U-net, and TransUNET.
+* Deep supervision is supported for U-net++, UNET 3+, and U^2-Net.
+* See the [User guide](https://github.com/yingkaisha/keras-unet-collection/blob/main/examples/user_guide_models.ipynb) for other options and use cases.
+| `keras_unet_collection.models` | Name | Reference |
+|:---------------|:----------------|:----------------|
+| `unet_2d` | U-net | [Ronneberger et al. (2015)](https://link.springer.com/chapter/10.1007/978-3-319-24574-4_28) |
+| `vnet_2d` | V-net (modified for 2-d inputs) | [Milletari et al. (2016)](https://arxiv.org/abs/1606.04797) |
+| `unet_plus_2d` | U-net++ | [Zhou et al. (2018)](https://link.springer.com/chapter/10.1007/978-3-030-00889-5_1) |
+| `r2_unet_2d` | R2U-Net | [Alom et al. (2018)](https://arxiv.org/abs/1802.06955) |
+| `att_unet_2d` | Attention U-net | [Oktay et al. (2018)](https://arxiv.org/abs/1804.03999) |
+| `resunet_a_2d` | ResUnet-a | [Diakogiannis et al. (2020)](https://doi.org/10.1016/j.isprsjprs.2020.01.013) |
+| `u2net_2d` | U^2-Net | [Qin et al. (2020)](https://arxiv.org/abs/2005.09007) |
+| `unet_3plus_2d` | UNET 3+ | [Huang et al. (2020)](https://arxiv.org/abs/2004.08790) |
+| `transunet_2d` | TransUNET | [Chen et al. (2021)](https://arxiv.org/abs/2102.04306) |
+| `swin_unet_2d` | Swin-UNET | [Hu et al. (2021)](https://arxiv.org/abs/2105.05537) |
+
+%package help
+Summary: Development documents and examples for keras-unet-collection
+Provides: python3-keras-unet-collection-doc
+%description help
+`keras_unet_collection.models` contains functions that configure keras models with hyper-parameter options.
+* Pre-trained ImageNet backbones are supported for U-net, U-net++, UNET 3+, Attention U-net, and TransUNET.
+* Deep supervision is supported for U-net++, UNET 3+, and U^2-Net.
+* See the [User guide](https://github.com/yingkaisha/keras-unet-collection/blob/main/examples/user_guide_models.ipynb) for other options and use cases.
+| `keras_unet_collection.models` | Name | Reference |
+|:---------------|:----------------|:----------------|
+| `unet_2d` | U-net | [Ronneberger et al. (2015)](https://link.springer.com/chapter/10.1007/978-3-319-24574-4_28) |
+| `vnet_2d` | V-net (modified for 2-d inputs) | [Milletari et al. (2016)](https://arxiv.org/abs/1606.04797) |
+| `unet_plus_2d` | U-net++ | [Zhou et al. (2018)](https://link.springer.com/chapter/10.1007/978-3-030-00889-5_1) |
+| `r2_unet_2d` | R2U-Net | [Alom et al. (2018)](https://arxiv.org/abs/1802.06955) |
+| `att_unet_2d` | Attention U-net | [Oktay et al. (2018)](https://arxiv.org/abs/1804.03999) |
+| `resunet_a_2d` | ResUnet-a | [Diakogiannis et al. (2020)](https://doi.org/10.1016/j.isprsjprs.2020.01.013) |
+| `u2net_2d` | U^2-Net | [Qin et al. (2020)](https://arxiv.org/abs/2005.09007) |
+| `unet_3plus_2d` | UNET 3+ | [Huang et al. (2020)](https://arxiv.org/abs/2004.08790) |
+| `transunet_2d` | TransUNET | [Chen et al. (2021)](https://arxiv.org/abs/2102.04306) |
+| `swin_unet_2d` | Swin-UNET | [Hu et al. (2021)](https://arxiv.org/abs/2105.05537) |
+
+%prep
+%autosetup -n keras-unet-collection-0.1.13
+
+%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-keras-unet-collection -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.13-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..2fa7af2
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+1f7224d7943ba902d2c5bcc4545821ac keras-unet-collection-0.1.13.tar.gz