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+%global _empty_manifest_terminate_build 0
+Name:		python-omnidata-tools
+Version:	0.0.23
+Release:	1
+Summary:	Tooling for Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans
+License:	omnidata # Add licenses and see current list in `setup.py`
+URL:		https://github.com/alexsax/omnidata_tools/tree/main/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/f5/31/2748e589f1ff82f8fa42e340dd9033e04a80190562a2915f4d6b2bdc8315/omnidata_tools-0.0.23.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-tqdm
+Requires:	python3-fastcore
+Requires:	python3-multiprocess
+Requires:	python3-aria2p[tui]
+
+%description
+# Omnidata Docs
+> <strong>Quick links to docs</strong>: [ <a href='/omnidata-tools/pretrained.html'>Pretrained Models</a> ]  [ <a href='/omnidata-tools/starter_dataset.html'>Starter Dataset ]  [ <a href='//omnidata-tools/annotator_usage.html'>Annotator Demo</a> ] 
+
+
+
+**This site is intended to be a wiki/documentation site for everything that we open-sourced from the paper.** There are three main folders: the annotator, utilities (dataloaders, download tools, pretrained models, etc), and a code dump of stuff from the paper that is just for reference. 
+
+(Check out the main site for an overview of 'steerable datastes' and the 3D → 2D rendering pipeline).
+
+
+
+<br>
+
+#### Download the code
+If you want to see and edit the code, then you can clone the github and install with: 
+
+```bash
+git clone https://github.com/EPFL-VILAB/omnidata-tools
+cd omnidata-tools
+pip install -e .    # this will install the python requirements (and also install the CLI)
+```
+This is probably the best option for you if you want to use the pretrained models, dataloaders, etc in other work.
+
+<br>
+
+
+#### Install just CLI tools (`omnitools`)
+If you are only interested in using the [CLI tools](/omnidata-tools/omnitools.html), you can install them with: `pip install omnidata-tools`. This might be preferable if you only want to quickly download the starter data, or if you just want a simple way to manipulate the vision datasets output by the annotator.
+
+_Note:_ The annotator can also be used with a [docker-based](/omnidata-tools/annotator_usage.html) CLI, but you don't need to use the annotator to use the starter dataset, pretrained models, or training code.
+
+
+<br>
+
+
+> ...were you looking for the [research paper](//omnidata.vision/#paper) or [project website](//omnidata.vision)? 
+
+<!-- <img src="https://raw.githubusercontent.com/alexsax/omnidata-tools/main/docs/images/omnidata_front_page.jpg?token=ABHLE3LC3U64F2QRVSOBSS3BPED24" alt="Website main page" style='max-width: 100%;'/> -->
+
+
+
+
+%package -n python3-omnidata-tools
+Summary:	Tooling for Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans
+Provides:	python-omnidata-tools
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-omnidata-tools
+# Omnidata Docs
+> <strong>Quick links to docs</strong>: [ <a href='/omnidata-tools/pretrained.html'>Pretrained Models</a> ]  [ <a href='/omnidata-tools/starter_dataset.html'>Starter Dataset ]  [ <a href='//omnidata-tools/annotator_usage.html'>Annotator Demo</a> ] 
+
+
+
+**This site is intended to be a wiki/documentation site for everything that we open-sourced from the paper.** There are three main folders: the annotator, utilities (dataloaders, download tools, pretrained models, etc), and a code dump of stuff from the paper that is just for reference. 
+
+(Check out the main site for an overview of 'steerable datastes' and the 3D → 2D rendering pipeline).
+
+
+
+<br>
+
+#### Download the code
+If you want to see and edit the code, then you can clone the github and install with: 
+
+```bash
+git clone https://github.com/EPFL-VILAB/omnidata-tools
+cd omnidata-tools
+pip install -e .    # this will install the python requirements (and also install the CLI)
+```
+This is probably the best option for you if you want to use the pretrained models, dataloaders, etc in other work.
+
+<br>
+
+
+#### Install just CLI tools (`omnitools`)
+If you are only interested in using the [CLI tools](/omnidata-tools/omnitools.html), you can install them with: `pip install omnidata-tools`. This might be preferable if you only want to quickly download the starter data, or if you just want a simple way to manipulate the vision datasets output by the annotator.
+
+_Note:_ The annotator can also be used with a [docker-based](/omnidata-tools/annotator_usage.html) CLI, but you don't need to use the annotator to use the starter dataset, pretrained models, or training code.
+
+
+<br>
+
+
+> ...were you looking for the [research paper](//omnidata.vision/#paper) or [project website](//omnidata.vision)? 
+
+<!-- <img src="https://raw.githubusercontent.com/alexsax/omnidata-tools/main/docs/images/omnidata_front_page.jpg?token=ABHLE3LC3U64F2QRVSOBSS3BPED24" alt="Website main page" style='max-width: 100%;'/> -->
+
+
+
+
+%package help
+Summary:	Development documents and examples for omnidata-tools
+Provides:	python3-omnidata-tools-doc
+%description help
+# Omnidata Docs
+> <strong>Quick links to docs</strong>: [ <a href='/omnidata-tools/pretrained.html'>Pretrained Models</a> ]  [ <a href='/omnidata-tools/starter_dataset.html'>Starter Dataset ]  [ <a href='//omnidata-tools/annotator_usage.html'>Annotator Demo</a> ] 
+
+
+
+**This site is intended to be a wiki/documentation site for everything that we open-sourced from the paper.** There are three main folders: the annotator, utilities (dataloaders, download tools, pretrained models, etc), and a code dump of stuff from the paper that is just for reference. 
+
+(Check out the main site for an overview of 'steerable datastes' and the 3D → 2D rendering pipeline).
+
+
+
+<br>
+
+#### Download the code
+If you want to see and edit the code, then you can clone the github and install with: 
+
+```bash
+git clone https://github.com/EPFL-VILAB/omnidata-tools
+cd omnidata-tools
+pip install -e .    # this will install the python requirements (and also install the CLI)
+```
+This is probably the best option for you if you want to use the pretrained models, dataloaders, etc in other work.
+
+<br>
+
+
+#### Install just CLI tools (`omnitools`)
+If you are only interested in using the [CLI tools](/omnidata-tools/omnitools.html), you can install them with: `pip install omnidata-tools`. This might be preferable if you only want to quickly download the starter data, or if you just want a simple way to manipulate the vision datasets output by the annotator.
+
+_Note:_ The annotator can also be used with a [docker-based](/omnidata-tools/annotator_usage.html) CLI, but you don't need to use the annotator to use the starter dataset, pretrained models, or training code.
+
+
+<br>
+
+
+> ...were you looking for the [research paper](//omnidata.vision/#paper) or [project website](//omnidata.vision)? 
+
+<!-- <img src="https://raw.githubusercontent.com/alexsax/omnidata-tools/main/docs/images/omnidata_front_page.jpg?token=ABHLE3LC3U64F2QRVSOBSS3BPED24" alt="Website main page" style='max-width: 100%;'/> -->
+
+
+
+
+%prep
+%autosetup -n omnidata-tools-0.0.23
+
+%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-omnidata-tools -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.23-1
+- Package Spec generated