%global _empty_manifest_terminate_build 0 Name: python-panimg Version: 0.12.0 Release: 1 Summary: Conversion of medical images to MHA and TIFF. License: Apache-2.0 URL: https://github.com/DIAGNijmegen/rse-panimg Source0: https://mirrors.aliyun.com/pypi/web/packages/1f/e3/9401ec58f8700a0d9bcbefa9be87ccfe226a6c65390834d7eacb0c1fb7b6/panimg-0.12.0.tar.gz BuildArch: noarch Requires: python3-pydantic Requires: python3-numpy Requires: python3-SimpleITK Requires: python3-pydicom Requires: python3-Pillow Requires: python3-openslide-python Requires: python3-pyvips Requires: python3-tifffile Requires: python3-construct Requires: python3-click Requires: python3-pylibjpeg Requires: python3-pylibjpeg-libjpeg Requires: python3-pylibjpeg-openjpeg Requires: python3-wsidicom Requires: python3-imagecodecs %description # panimg [![CI](https://github.com/DIAGNijmegen/rse-panimg/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/DIAGNijmegen/rse-panimg/actions/workflows/ci.yml?query=branch%3Amain) [![PyPI](https://img.shields.io/pypi/v/panimg)](https://pypi.org/project/panimg/) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/panimg)](https://pypi.org/project/panimg/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![DOI](https://zenodo.org/badge/344730308.svg)](https://zenodo.org/badge/latestdoi/344730308) **NOT FOR CLINICAL USE** Conversion of medical images to MHA and TIFF. Requires Python 3.8, 3.9, 3.10 or 3.11. `libvips-dev` and `libopenslide-dev` must be installed on your system. Under the hood we use: * `SimpleITK` * `pydicom` * `pylibjpeg` * `Pillow` * `openslide-python` * `pyvips` * `oct-converter` * `wsidicom` ## Usage `panimg` takes a directory and tries to convert the containing files to MHA or TIFF. By default, it will try to convert files from subdirectories as well. To only convert files in the top level directory, set `recurse_subdirectories` to `False`. It will try several strategies for loading the contained files, and if an image is found it will output it to the output directory. It will return a structure containing information about what images were produced, what images were used to form the new images, image metadata, and any errors from any of the strategies. **NOTE: Alpha software, do not run this on directories you do not have a backup of.** ```python from pathlib import Path from panimg import convert result = convert( input_directory=Path("/path/to/files/"), output_directory=Path("/where/files/will/go/"), ) ``` ### Command Line Interface `panimg` is also accessible from the command line. Install the package from pip as before, then you can use: **NOTE: Alpha software, do not run this on directories you do not have a backup of.** ```shell panimg convert /path/to/files/ /where/files/will/go/ ``` To access the help test you can use `panimg -h`. ### Supported Formats | Input | Output | Strategy | Notes | |-------------------------------------| --------| ---------- | -------------------------- | | `.mha` | `.mha` | `metaio` | | | `.mhd` with `.raw` or `.zraw` | `.mha` | `metaio` | | | `.dcm` | `.mha` | `dicom` | | | `.nii` | `.mha` | `nifti` | | | `.nii.gz` | `.mha` | `nifti` | | | `.nrrd` | `.mha` | `nrrd` | [1](#footnote1) | | `.e2e` | `.mha` | `oct` | [2](#footnote2) | | `.fds` | `.mha` | `oct` | [2](#footnote2) | | `.fda` | `.mha` | `oct` | [2](#footnote2) | | `.png` | `.mha` | `fallback` | [3](#footnote3) | | `.jpeg` | `.mha` | `fallback` | [3](#footnote3) | | `.tiff` | `.tiff` | `tiff` | | | `.svs` (Aperio) | `.tiff` | `tiff` | | | `.vms`, `.vmu`, `.ndpi` (Hamamatsu) | `.tiff` | `tiff` | | | `.scn` (Leica) | `.tiff` | `tiff` | | | `.mrxs` (MIRAX) | `.tiff` | `tiff` | | | `.biff` (Ventana) | `.tiff` | `tiff` | | | `.dcm` (DICOM-WSI) | `.tiff` | `tiff` | | 1: Detached headers are not supported. 2: Only OCT volume(s), no fundus image(s) will be extracted. 3: 2D only, unitary dimensions #### Post Processors You can also define a set of post processors that will operate on each output file. Post processors will not produce any new image entities, but rather add additional representations of an image, such as DZI or thumbnails. We provide a `dzi_to_tiff` post processor that is enabled by default, which will produce a DZI file if it is able to. To customise the post processors that run you can do this with ```python result = convert(..., post_processors=[...]) ``` You are able to run the post processors directly with ```python from panimg import post_process from panimg.models import PanImgFile result = post_process(image_files={PanImgFile(...), ...}, post_processors=[...]) ``` #### Using Strategies Directly If you want to run a particular strategy directly which returns a generator of images for a set of files you can do this with ```python files = {f for f in Path("/foo/").glob("*.dcm") if f.is_file()} try: for result in image_builder_dicom(files=files): sitk_image = result.image process(sitk_image) # etc. you can also look at result.name for the name of the file, # and result.consumed_files to see what files were used for this image except UnconsumedFilesException as e: # e.errors is keyed with a Path to a file that could not be consumed, # with a list of all the errors found with loading it, # the user can then choose what to do with that information ... ``` %package -n python3-panimg Summary: Conversion of medical images to MHA and TIFF. Provides: python-panimg BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-panimg # panimg [![CI](https://github.com/DIAGNijmegen/rse-panimg/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/DIAGNijmegen/rse-panimg/actions/workflows/ci.yml?query=branch%3Amain) [![PyPI](https://img.shields.io/pypi/v/panimg)](https://pypi.org/project/panimg/) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/panimg)](https://pypi.org/project/panimg/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![DOI](https://zenodo.org/badge/344730308.svg)](https://zenodo.org/badge/latestdoi/344730308) **NOT FOR CLINICAL USE** Conversion of medical images to MHA and TIFF. Requires Python 3.8, 3.9, 3.10 or 3.11. `libvips-dev` and `libopenslide-dev` must be installed on your system. Under the hood we use: * `SimpleITK` * `pydicom` * `pylibjpeg` * `Pillow` * `openslide-python` * `pyvips` * `oct-converter` * `wsidicom` ## Usage `panimg` takes a directory and tries to convert the containing files to MHA or TIFF. By default, it will try to convert files from subdirectories as well. To only convert files in the top level directory, set `recurse_subdirectories` to `False`. It will try several strategies for loading the contained files, and if an image is found it will output it to the output directory. It will return a structure containing information about what images were produced, what images were used to form the new images, image metadata, and any errors from any of the strategies. **NOTE: Alpha software, do not run this on directories you do not have a backup of.** ```python from pathlib import Path from panimg import convert result = convert( input_directory=Path("/path/to/files/"), output_directory=Path("/where/files/will/go/"), ) ``` ### Command Line Interface `panimg` is also accessible from the command line. Install the package from pip as before, then you can use: **NOTE: Alpha software, do not run this on directories you do not have a backup of.** ```shell panimg convert /path/to/files/ /where/files/will/go/ ``` To access the help test you can use `panimg -h`. ### Supported Formats | Input | Output | Strategy | Notes | |-------------------------------------| --------| ---------- | -------------------------- | | `.mha` | `.mha` | `metaio` | | | `.mhd` with `.raw` or `.zraw` | `.mha` | `metaio` | | | `.dcm` | `.mha` | `dicom` | | | `.nii` | `.mha` | `nifti` | | | `.nii.gz` | `.mha` | `nifti` | | | `.nrrd` | `.mha` | `nrrd` | [1](#footnote1) | | `.e2e` | `.mha` | `oct` | [2](#footnote2) | | `.fds` | `.mha` | `oct` | [2](#footnote2) | | `.fda` | `.mha` | `oct` | [2](#footnote2) | | `.png` | `.mha` | `fallback` | [3](#footnote3) | | `.jpeg` | `.mha` | `fallback` | [3](#footnote3) | | `.tiff` | `.tiff` | `tiff` | | | `.svs` (Aperio) | `.tiff` | `tiff` | | | `.vms`, `.vmu`, `.ndpi` (Hamamatsu) | `.tiff` | `tiff` | | | `.scn` (Leica) | `.tiff` | `tiff` | | | `.mrxs` (MIRAX) | `.tiff` | `tiff` | | | `.biff` (Ventana) | `.tiff` | `tiff` | | | `.dcm` (DICOM-WSI) | `.tiff` | `tiff` | | 1: Detached headers are not supported. 2: Only OCT volume(s), no fundus image(s) will be extracted. 3: 2D only, unitary dimensions #### Post Processors You can also define a set of post processors that will operate on each output file. Post processors will not produce any new image entities, but rather add additional representations of an image, such as DZI or thumbnails. We provide a `dzi_to_tiff` post processor that is enabled by default, which will produce a DZI file if it is able to. To customise the post processors that run you can do this with ```python result = convert(..., post_processors=[...]) ``` You are able to run the post processors directly with ```python from panimg import post_process from panimg.models import PanImgFile result = post_process(image_files={PanImgFile(...), ...}, post_processors=[...]) ``` #### Using Strategies Directly If you want to run a particular strategy directly which returns a generator of images for a set of files you can do this with ```python files = {f for f in Path("/foo/").glob("*.dcm") if f.is_file()} try: for result in image_builder_dicom(files=files): sitk_image = result.image process(sitk_image) # etc. you can also look at result.name for the name of the file, # and result.consumed_files to see what files were used for this image except UnconsumedFilesException as e: # e.errors is keyed with a Path to a file that could not be consumed, # with a list of all the errors found with loading it, # the user can then choose what to do with that information ... ``` %package help Summary: Development documents and examples for panimg Provides: python3-panimg-doc %description help # panimg [![CI](https://github.com/DIAGNijmegen/rse-panimg/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/DIAGNijmegen/rse-panimg/actions/workflows/ci.yml?query=branch%3Amain) [![PyPI](https://img.shields.io/pypi/v/panimg)](https://pypi.org/project/panimg/) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/panimg)](https://pypi.org/project/panimg/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![DOI](https://zenodo.org/badge/344730308.svg)](https://zenodo.org/badge/latestdoi/344730308) **NOT FOR CLINICAL USE** Conversion of medical images to MHA and TIFF. Requires Python 3.8, 3.9, 3.10 or 3.11. `libvips-dev` and `libopenslide-dev` must be installed on your system. Under the hood we use: * `SimpleITK` * `pydicom` * `pylibjpeg` * `Pillow` * `openslide-python` * `pyvips` * `oct-converter` * `wsidicom` ## Usage `panimg` takes a directory and tries to convert the containing files to MHA or TIFF. By default, it will try to convert files from subdirectories as well. To only convert files in the top level directory, set `recurse_subdirectories` to `False`. It will try several strategies for loading the contained files, and if an image is found it will output it to the output directory. It will return a structure containing information about what images were produced, what images were used to form the new images, image metadata, and any errors from any of the strategies. **NOTE: Alpha software, do not run this on directories you do not have a backup of.** ```python from pathlib import Path from panimg import convert result = convert( input_directory=Path("/path/to/files/"), output_directory=Path("/where/files/will/go/"), ) ``` ### Command Line Interface `panimg` is also accessible from the command line. Install the package from pip as before, then you can use: **NOTE: Alpha software, do not run this on directories you do not have a backup of.** ```shell panimg convert /path/to/files/ /where/files/will/go/ ``` To access the help test you can use `panimg -h`. ### Supported Formats | Input | Output | Strategy | Notes | |-------------------------------------| --------| ---------- | -------------------------- | | `.mha` | `.mha` | `metaio` | | | `.mhd` with `.raw` or `.zraw` | `.mha` | `metaio` | | | `.dcm` | `.mha` | `dicom` | | | `.nii` | `.mha` | `nifti` | | | `.nii.gz` | `.mha` | `nifti` | | | `.nrrd` | `.mha` | `nrrd` | [1](#footnote1) | | `.e2e` | `.mha` | `oct` | [2](#footnote2) | | `.fds` | `.mha` | `oct` | [2](#footnote2) | | `.fda` | `.mha` | `oct` | [2](#footnote2) | | `.png` | `.mha` | `fallback` | [3](#footnote3) | | `.jpeg` | `.mha` | `fallback` | [3](#footnote3) | | `.tiff` | `.tiff` | `tiff` | | | `.svs` (Aperio) | `.tiff` | `tiff` | | | `.vms`, `.vmu`, `.ndpi` (Hamamatsu) | `.tiff` | `tiff` | | | `.scn` (Leica) | `.tiff` | `tiff` | | | `.mrxs` (MIRAX) | `.tiff` | `tiff` | | | `.biff` (Ventana) | `.tiff` | `tiff` | | | `.dcm` (DICOM-WSI) | `.tiff` | `tiff` | | 1: Detached headers are not supported. 2: Only OCT volume(s), no fundus image(s) will be extracted. 3: 2D only, unitary dimensions #### Post Processors You can also define a set of post processors that will operate on each output file. Post processors will not produce any new image entities, but rather add additional representations of an image, such as DZI or thumbnails. We provide a `dzi_to_tiff` post processor that is enabled by default, which will produce a DZI file if it is able to. To customise the post processors that run you can do this with ```python result = convert(..., post_processors=[...]) ``` You are able to run the post processors directly with ```python from panimg import post_process from panimg.models import PanImgFile result = post_process(image_files={PanImgFile(...), ...}, post_processors=[...]) ``` #### Using Strategies Directly If you want to run a particular strategy directly which returns a generator of images for a set of files you can do this with ```python files = {f for f in Path("/foo/").glob("*.dcm") if f.is_file()} try: for result in image_builder_dicom(files=files): sitk_image = result.image process(sitk_image) # etc. you can also look at result.name for the name of the file, # and result.consumed_files to see what files were used for this image except UnconsumedFilesException as e: # e.errors is keyed with a Path to a file that could not be consumed, # with a list of all the errors found with loading it, # the user can then choose what to do with that information ... ``` %prep %autosetup -n panimg-0.12.0 %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-panimg -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Jun 20 2023 Python_Bot - 0.12.0-1 - Package Spec generated