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diff --git a/python-split-folders.spec b/python-split-folders.spec new file mode 100644 index 0000000..3f9c931 --- /dev/null +++ b/python-split-folders.spec @@ -0,0 +1,484 @@ +%global _empty_manifest_terminate_build 0 +Name: python-split-folders +Version: 0.5.1 +Release: 1 +Summary: Split folders with files (e.g. images) into training, validation and test (dataset) folders. +License: MIT +URL: https://github.com/jfilter/split-folders +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a7/4c/32d2d49b82ea5baf0ff1a55de88c7fb8a0bf2aab02763c8501b2a51bf55f/split_folders-0.5.1.tar.gz +BuildArch: noarch + +Requires: python3-tqdm + +%description +# `split-folders` [](https://github.com/jfilter/split-folders/actions/workflows/test.yml) [](https://pypi.org/project/split-folders/) [](https://pypi.org/project/split-folders/) [](https://pypistats.org/packages/split-folders) + +Split folders with files (e.g. images) into **train**, **validation** and **test** (dataset) folders. + +The input folder should have the following format: + +``` +input/ + class1/ + img1.jpg + img2.jpg + ... + class2/ + imgWhatever.jpg + ... + ... +``` + +In order to give you this: + +``` +output/ + train/ + class1/ + img1.jpg + ... + class2/ + imga.jpg + ... + val/ + class1/ + img2.jpg + ... + class2/ + imgb.jpg + ... + test/ + class1/ + img3.jpg + ... + class2/ + imgc.jpg + ... +``` + +This should get you started to do some serious deep learning on your data. [Read here](https://stats.stackexchange.com/questions/19048/what-is-the-difference-between-test-set-and-validation-set) why it's a good idea to split your data intro three different sets. + +- Split files into a training set and a validation set (and optionally a test set). +- Works on any file types. +- The files get shuffled. +- A [seed](https://docs.python.org/3/library/random.html#random.seed) makes splits reproducible. +- Allows randomized [oversampling](https://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis) for imbalanced datasets. +- Optionally group files by prefix. +- (Should) work on all operating systems. + +## Install + +This package is Python only and there are no external dependencies. + +```bash +pip install split-folders +``` + +Optionally, you may install [tqdm](https://github.com/tqdm/tqdm) to get get a progress bar when moving files. + +```bash +pip install split-folders[full] +``` + +## Usage + +You can use `split-folders` as Python module or as a Command Line Interface (CLI). + +If your datasets is balanced (each class has the same number of samples), choose `ratio` otherwise `fixed`. +NB: oversampling is turned off by default. +Oversampling is only applied to the _train_ folder since having duplicates in _val_ or _test_ would be considered cheating. + +### Module + +```python +import splitfolders + +# Split with a ratio. +# To only split into training and validation set, set a tuple to `ratio`, i.e, `(.8, .2)`. +splitfolders.ratio("input_folder", output="output", + seed=1337, ratio=(.8, .1, .1), group_prefix=None, move=False) # default values + +# Split val/test with a fixed number of items, e.g. `(100, 100)`, for each set. +# To only split into training and validation set, use a single number to `fixed`, i.e., `10`. +# Set 3 values, e.g. `(300, 100, 100)`, to limit the number of training values. +splitfolders.fixed("input_folder", output="output", + seed=1337, fixed=(100, 100), oversample=False, group_prefix=None, move=False) # default values +``` + +Occasionally, you may have things that comprise more than a single file (e.g. picture (.png) + annotation (.txt)). +`splitfolders` lets you split files into equally-sized groups based on their prefix. +Set `group_prefix` to the length of the group (e.g. `2`). +But now _all_ files should be part of groups. + +Set `move=True` if you want to move the files instead of copying. + +### CLI + +``` +Usage: + splitfolders [--output] [--ratio] [--fixed] [--seed] [--oversample] [--group_prefix] [--move] folder_with_images +Options: + --output path to the output folder. defaults to `output`. Get created if non-existent. + --ratio the ratio to split. e.g. for train/val/test `.8 .1 .1 --` or for train/val `.8 .2 --`. + --fixed set the absolute number of items per validation/test set. The remaining items constitute + the training set. e.g. for train/val/test `100 100` or for train/val `100`. + Set 3 values, e.g. `300 100 100`, to limit the number of training values. + --seed set seed value for shuffling the items. defaults to 1337. + --oversample enable oversampling of imbalanced datasets, works only with --fixed. + --group_prefix split files into equally-sized groups based on their prefix + --move move the files instead of copying +Example: + splitfolders --ratio .8 .1 .1 -- folder_with_images +``` + +Because of some [Python quirks](https://github.com/jfilter/split-folders/issues/19) you have to prepend ` --` afer using `--ratio`. + +Instead of the command `splitfolders` you can also use `split_folders` or `split-folders`. + +## Development + +Install and use [poetry](https://python-poetry.org/). + +## Contributing + +If you have a **question**, found a **bug** or want to propose a new **feature**, have a look at the [issues page](https://github.com/jfilter/split-folders/issues). + +**Pull requests** are especially welcomed when they fix bugs or improve the code quality. + +## License + +MIT + + +%package -n python3-split-folders +Summary: Split folders with files (e.g. images) into training, validation and test (dataset) folders. +Provides: python-split-folders +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-split-folders +# `split-folders` [](https://github.com/jfilter/split-folders/actions/workflows/test.yml) [](https://pypi.org/project/split-folders/) [](https://pypi.org/project/split-folders/) [](https://pypistats.org/packages/split-folders) + +Split folders with files (e.g. images) into **train**, **validation** and **test** (dataset) folders. + +The input folder should have the following format: + +``` +input/ + class1/ + img1.jpg + img2.jpg + ... + class2/ + imgWhatever.jpg + ... + ... +``` + +In order to give you this: + +``` +output/ + train/ + class1/ + img1.jpg + ... + class2/ + imga.jpg + ... + val/ + class1/ + img2.jpg + ... + class2/ + imgb.jpg + ... + test/ + class1/ + img3.jpg + ... + class2/ + imgc.jpg + ... +``` + +This should get you started to do some serious deep learning on your data. [Read here](https://stats.stackexchange.com/questions/19048/what-is-the-difference-between-test-set-and-validation-set) why it's a good idea to split your data intro three different sets. + +- Split files into a training set and a validation set (and optionally a test set). +- Works on any file types. +- The files get shuffled. +- A [seed](https://docs.python.org/3/library/random.html#random.seed) makes splits reproducible. +- Allows randomized [oversampling](https://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis) for imbalanced datasets. +- Optionally group files by prefix. +- (Should) work on all operating systems. + +## Install + +This package is Python only and there are no external dependencies. + +```bash +pip install split-folders +``` + +Optionally, you may install [tqdm](https://github.com/tqdm/tqdm) to get get a progress bar when moving files. + +```bash +pip install split-folders[full] +``` + +## Usage + +You can use `split-folders` as Python module or as a Command Line Interface (CLI). + +If your datasets is balanced (each class has the same number of samples), choose `ratio` otherwise `fixed`. +NB: oversampling is turned off by default. +Oversampling is only applied to the _train_ folder since having duplicates in _val_ or _test_ would be considered cheating. + +### Module + +```python +import splitfolders + +# Split with a ratio. +# To only split into training and validation set, set a tuple to `ratio`, i.e, `(.8, .2)`. +splitfolders.ratio("input_folder", output="output", + seed=1337, ratio=(.8, .1, .1), group_prefix=None, move=False) # default values + +# Split val/test with a fixed number of items, e.g. `(100, 100)`, for each set. +# To only split into training and validation set, use a single number to `fixed`, i.e., `10`. +# Set 3 values, e.g. `(300, 100, 100)`, to limit the number of training values. +splitfolders.fixed("input_folder", output="output", + seed=1337, fixed=(100, 100), oversample=False, group_prefix=None, move=False) # default values +``` + +Occasionally, you may have things that comprise more than a single file (e.g. picture (.png) + annotation (.txt)). +`splitfolders` lets you split files into equally-sized groups based on their prefix. +Set `group_prefix` to the length of the group (e.g. `2`). +But now _all_ files should be part of groups. + +Set `move=True` if you want to move the files instead of copying. + +### CLI + +``` +Usage: + splitfolders [--output] [--ratio] [--fixed] [--seed] [--oversample] [--group_prefix] [--move] folder_with_images +Options: + --output path to the output folder. defaults to `output`. Get created if non-existent. + --ratio the ratio to split. e.g. for train/val/test `.8 .1 .1 --` or for train/val `.8 .2 --`. + --fixed set the absolute number of items per validation/test set. The remaining items constitute + the training set. e.g. for train/val/test `100 100` or for train/val `100`. + Set 3 values, e.g. `300 100 100`, to limit the number of training values. + --seed set seed value for shuffling the items. defaults to 1337. + --oversample enable oversampling of imbalanced datasets, works only with --fixed. + --group_prefix split files into equally-sized groups based on their prefix + --move move the files instead of copying +Example: + splitfolders --ratio .8 .1 .1 -- folder_with_images +``` + +Because of some [Python quirks](https://github.com/jfilter/split-folders/issues/19) you have to prepend ` --` afer using `--ratio`. + +Instead of the command `splitfolders` you can also use `split_folders` or `split-folders`. + +## Development + +Install and use [poetry](https://python-poetry.org/). + +## Contributing + +If you have a **question**, found a **bug** or want to propose a new **feature**, have a look at the [issues page](https://github.com/jfilter/split-folders/issues). + +**Pull requests** are especially welcomed when they fix bugs or improve the code quality. + +## License + +MIT + + +%package help +Summary: Development documents and examples for split-folders +Provides: python3-split-folders-doc +%description help +# `split-folders` [](https://github.com/jfilter/split-folders/actions/workflows/test.yml) [](https://pypi.org/project/split-folders/) [](https://pypi.org/project/split-folders/) [](https://pypistats.org/packages/split-folders) + +Split folders with files (e.g. images) into **train**, **validation** and **test** (dataset) folders. + +The input folder should have the following format: + +``` +input/ + class1/ + img1.jpg + img2.jpg + ... + class2/ + imgWhatever.jpg + ... + ... +``` + +In order to give you this: + +``` +output/ + train/ + class1/ + img1.jpg + ... + class2/ + imga.jpg + ... + val/ + class1/ + img2.jpg + ... + class2/ + imgb.jpg + ... + test/ + class1/ + img3.jpg + ... + class2/ + imgc.jpg + ... +``` + +This should get you started to do some serious deep learning on your data. [Read here](https://stats.stackexchange.com/questions/19048/what-is-the-difference-between-test-set-and-validation-set) why it's a good idea to split your data intro three different sets. + +- Split files into a training set and a validation set (and optionally a test set). +- Works on any file types. +- The files get shuffled. +- A [seed](https://docs.python.org/3/library/random.html#random.seed) makes splits reproducible. +- Allows randomized [oversampling](https://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis) for imbalanced datasets. +- Optionally group files by prefix. +- (Should) work on all operating systems. + +## Install + +This package is Python only and there are no external dependencies. + +```bash +pip install split-folders +``` + +Optionally, you may install [tqdm](https://github.com/tqdm/tqdm) to get get a progress bar when moving files. + +```bash +pip install split-folders[full] +``` + +## Usage + +You can use `split-folders` as Python module or as a Command Line Interface (CLI). + +If your datasets is balanced (each class has the same number of samples), choose `ratio` otherwise `fixed`. +NB: oversampling is turned off by default. +Oversampling is only applied to the _train_ folder since having duplicates in _val_ or _test_ would be considered cheating. + +### Module + +```python +import splitfolders + +# Split with a ratio. +# To only split into training and validation set, set a tuple to `ratio`, i.e, `(.8, .2)`. +splitfolders.ratio("input_folder", output="output", + seed=1337, ratio=(.8, .1, .1), group_prefix=None, move=False) # default values + +# Split val/test with a fixed number of items, e.g. `(100, 100)`, for each set. +# To only split into training and validation set, use a single number to `fixed`, i.e., `10`. +# Set 3 values, e.g. `(300, 100, 100)`, to limit the number of training values. +splitfolders.fixed("input_folder", output="output", + seed=1337, fixed=(100, 100), oversample=False, group_prefix=None, move=False) # default values +``` + +Occasionally, you may have things that comprise more than a single file (e.g. picture (.png) + annotation (.txt)). +`splitfolders` lets you split files into equally-sized groups based on their prefix. +Set `group_prefix` to the length of the group (e.g. `2`). +But now _all_ files should be part of groups. + +Set `move=True` if you want to move the files instead of copying. + +### CLI + +``` +Usage: + splitfolders [--output] [--ratio] [--fixed] [--seed] [--oversample] [--group_prefix] [--move] folder_with_images +Options: + --output path to the output folder. defaults to `output`. Get created if non-existent. + --ratio the ratio to split. e.g. for train/val/test `.8 .1 .1 --` or for train/val `.8 .2 --`. + --fixed set the absolute number of items per validation/test set. The remaining items constitute + the training set. e.g. for train/val/test `100 100` or for train/val `100`. + Set 3 values, e.g. `300 100 100`, to limit the number of training values. + --seed set seed value for shuffling the items. defaults to 1337. + --oversample enable oversampling of imbalanced datasets, works only with --fixed. + --group_prefix split files into equally-sized groups based on their prefix + --move move the files instead of copying +Example: + splitfolders --ratio .8 .1 .1 -- folder_with_images +``` + +Because of some [Python quirks](https://github.com/jfilter/split-folders/issues/19) you have to prepend ` --` afer using `--ratio`. + +Instead of the command `splitfolders` you can also use `split_folders` or `split-folders`. + +## Development + +Install and use [poetry](https://python-poetry.org/). + +## Contributing + +If you have a **question**, found a **bug** or want to propose a new **feature**, have a look at the [issues page](https://github.com/jfilter/split-folders/issues). + +**Pull requests** are especially welcomed when they fix bugs or improve the code quality. + +## License + +MIT + + +%prep +%autosetup -n split-folders-0.5.1 + +%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-split-folders -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.5.1-1 +- Package Spec generated |