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authorCoprDistGit <infra@openeuler.org>2023-05-29 10:54:31 +0000
committerCoprDistGit <infra@openeuler.org>2023-05-29 10:54:31 +0000
commit35c013eeea0e102d63be4b04464c46940ab6f1e8 (patch)
treed1e18400bb36e785f1858e92e893ad5a6d466256 /python-dnnlab.spec
parent5ad98b47cf89d2ecf530f69cf14afc940da4ea89 (diff)
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+%global _empty_manifest_terminate_build 0
+Name: python-dnnlab
+Version: 2.2.5
+Release: 1
+Summary: DnnLab
+License: Apache Software License
+URL: https://pypi.org/project/dnnlab/
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/4e/05/13de5b2635ea6158bcc084e433ac34cb5ea1e7a6c523e13b5747217137d7/dnnlab-2.2.5.tar.gz
+BuildArch: noarch
+
+Requires: python3-Cython
+Requires: python3-numpy
+Requires: python3-pycocotools
+Requires: python3-Click
+Requires: python3-opencv-python
+Requires: python3-imgaug
+Requires: python3-matplotlib
+
+%description
+# DnnLab
+Dnnlab is a small framework for deep learning models based on TensorFlow.
+
+
+
+It provides custom training loops for:
+* Generative Models (GAN, cGan, cycleGAN)
+* Image Detection (custom YOLO)
+
+
+Additonaly custom Keras Layer:
+* Non-Local-Blocks (Self-Attention)
+* Squeeze and Excitation Blocks (SEBlocks)
+* YOLO-Decoding Layer
+
+Input pipeline functionality:
+* YOLO (Tfrecords to Datasets)
+* YOLO data augmentation
+* Generative Models (Tfrecords to Datasets)
+
+TensorBoard output:
+* YOLO coco metrics (Precision (mAP) & Recall)
+* YOLO loss (loss_class, loss_conf, loss_xywh, total_loss)
+* YOLO bounding boxes
+* Generative Models (Loss & Images)
+
+
+## Requirements
+TensorFlow 2.3.0
+
+## Installation
+Run the following to install:
+```python
+pip install dnnlab
+```
+
+
+
+
+
+
+
+
+
+
+
+%package -n python3-dnnlab
+Summary: DnnLab
+Provides: python-dnnlab
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-pip
+%description -n python3-dnnlab
+# DnnLab
+Dnnlab is a small framework for deep learning models based on TensorFlow.
+
+
+
+It provides custom training loops for:
+* Generative Models (GAN, cGan, cycleGAN)
+* Image Detection (custom YOLO)
+
+
+Additonaly custom Keras Layer:
+* Non-Local-Blocks (Self-Attention)
+* Squeeze and Excitation Blocks (SEBlocks)
+* YOLO-Decoding Layer
+
+Input pipeline functionality:
+* YOLO (Tfrecords to Datasets)
+* YOLO data augmentation
+* Generative Models (Tfrecords to Datasets)
+
+TensorBoard output:
+* YOLO coco metrics (Precision (mAP) & Recall)
+* YOLO loss (loss_class, loss_conf, loss_xywh, total_loss)
+* YOLO bounding boxes
+* Generative Models (Loss & Images)
+
+
+## Requirements
+TensorFlow 2.3.0
+
+## Installation
+Run the following to install:
+```python
+pip install dnnlab
+```
+
+
+
+
+
+
+
+
+
+
+
+%package help
+Summary: Development documents and examples for dnnlab
+Provides: python3-dnnlab-doc
+%description help
+# DnnLab
+Dnnlab is a small framework for deep learning models based on TensorFlow.
+
+
+
+It provides custom training loops for:
+* Generative Models (GAN, cGan, cycleGAN)
+* Image Detection (custom YOLO)
+
+
+Additonaly custom Keras Layer:
+* Non-Local-Blocks (Self-Attention)
+* Squeeze and Excitation Blocks (SEBlocks)
+* YOLO-Decoding Layer
+
+Input pipeline functionality:
+* YOLO (Tfrecords to Datasets)
+* YOLO data augmentation
+* Generative Models (Tfrecords to Datasets)
+
+TensorBoard output:
+* YOLO coco metrics (Precision (mAP) & Recall)
+* YOLO loss (loss_class, loss_conf, loss_xywh, total_loss)
+* YOLO bounding boxes
+* Generative Models (Loss & Images)
+
+
+## Requirements
+TensorFlow 2.3.0
+
+## Installation
+Run the following to install:
+```python
+pip install dnnlab
+```
+
+
+
+
+
+
+
+
+
+
+
+%prep
+%autosetup -n dnnlab-2.2.5
+
+%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-dnnlab -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.5-1
+- Package Spec generated