From 8788b58822dcfc9e8ff459368e432fba859c0e0b Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Thu, 18 May 2023 04:59:28 +0000 Subject: automatic import of python-napari-skimage-regionprops --- python-napari-skimage-regionprops.spec | 1101 ++++++++++++++++++++++++++++++++ 1 file changed, 1101 insertions(+) create mode 100644 python-napari-skimage-regionprops.spec (limited to 'python-napari-skimage-regionprops.spec') diff --git a/python-napari-skimage-regionprops.spec b/python-napari-skimage-regionprops.spec new file mode 100644 index 0000000..2cf69ba --- /dev/null +++ b/python-napari-skimage-regionprops.spec @@ -0,0 +1,1101 @@ +%global _empty_manifest_terminate_build 0 +Name: python-napari-skimage-regionprops +Version: 0.10.0 +Release: 1 +Summary: A regionprops table widget plugin for napari +License: BSD-3 +URL: https://github.com/haesleinhuepf/napari-skimage-regionprops +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/1d/a6/cfa054ea2c2a1a5aaa8b112a385279ca1ea3682cebe958819e620dd9b8aa/napari-skimage-regionprops-0.10.0.tar.gz +BuildArch: noarch + +Requires: python3-napari-plugin-engine +Requires: python3-numpy +Requires: python3-scikit-image +Requires: python3-napari +Requires: python3-pandas +Requires: python3-napari-tools-menu +Requires: python3-napari-workflows +Requires: python3-imageio +Requires: python3-Deprecated + +%description +# napari-skimage-regionprops (nsr) + + + +[![License](https://img.shields.io/pypi/l/napari-skimage-regionprops.svg?color=green)](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/LICENSE) + +[![PyPI](https://img.shields.io/pypi/v/napari-skimage-regionprops.svg?color=green)](https://pypi.org/project/napari-skimage-regionprops) + +[![Python Version](https://img.shields.io/pypi/pyversions/napari-skimage-regionprops.svg?color=green)](https://python.org) + +[![tests](https://github.com/haesleinhuepf/napari-skimage-regionprops/workflows/tests/badge.svg)](https://github.com/haesleinhuepf/napari-skimage-regionprops/actions) + +[![codecov](https://codecov.io/gh/haesleinhuepf/napari-skimage-regionprops/branch/master/graph/badge.svg)](https://codecov.io/gh/haesleinhuepf/napari-skimage-regionprops) + +[![Development Status](https://img.shields.io/pypi/status/napari-skimage-regionprops.svg)](https://en.wikipedia.org/wiki/Software_release_life_cycle#Alpha) + +[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-skimage-regionprops)](https://napari-hub.org/plugins/napari-skimage-regionprops) + + + + + +A [napari] plugin for measuring properties of labeled objects based on [scikit-image] + + + +![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/interactive.gif) + + + +## Usage: measure region properties + + + +From the menu `Tools > Measurement > Regionprops (nsr)` you can open a dialog where you can choose an intensity image, a corresponding label image and the features you want to measure: + + + +![img.png](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/dialog.png) + + + +If you want to interface with the labels and see which table row corresponds to which labeled object, use the label picker and + +activate the `show selected` checkbox. + + + +![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/interactive.png) + + + +If you closed a table and want to reopen it, you can use the menu `Tools > Measurements > Show table (nsr)` to reopen it. + +You just need to select the labels layer the properties are associated with. + + + +For visualizing measurements with different grey values, as parametric images, you can double-click table headers. + + + +![img.png](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/label_value_visualization.gif) + + + +## Usage: measure point intensities + + + +Analogously, also the intensity and coordinates of point layers can be measured using the menu `Tools > Measurement > Measure intensity at point coordinates (nsr)`. + +Also these measurements can be visualized by double-clicking table headers: + + + +![img.png](measure_point_intensity.png) + + + +![img_1.png](measure_point_coordinate.png) + + + +## Working with time-lapse and tracking data + + + +Note that tables for time-lapse data should include a column named "frame", which indicates which slice in + +time the given row refers to. If you want to import your own csv files for time-lapse data make sure to include this column. + +If you have tracking data where each column specifies measurements for a track instead of a label at a specific time point, + +this column must not be added. + + + +In case you have 2D time-lapse data you need to convert it into a suitable shape using the function: `Tools > Utilities > Convert 3D stack to 2D time-lapse (time-slicer)`, + +which can be found in the [napari time slicer](https://www.napari-hub.org/plugins/napari-time-slicer). + + + +Last but not least, make sure that in case of time-lapse data the label image has labels that are subsquently labeled per timepoint. + +E.g. a dataset where label 5 is missing at timepoint 4 may be visualized incorrectly. + + + +## Usage: multichannel or multi-label data + + + +If you want to relate objects from one channels to objects from another channel, you can use `Tools > Measurement tables > Object Features/Properties (scikit-image, nsr)`. + +This plugin module allos you to answer questions like: + + - how many objects I have inside other objects? + + - what is the average intensity of the objects inside other objects? + +For that, you need at least two labeled images in napari. You can relate objects along with their features. + +If intensity features are also wanted, then you also need to provide two intensity images. + +Below, there is a small example on how to use it. + +Also, take a look at [this example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/measure_things_inside_things_plugin.ipynb). + + + + ![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/things_inside_things_demo.gif) + + + +## Usage, programmatically + + + +You can also control the tables programmatically. See this + +[example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/tables.ipynb) for details on regionprops and + +[this example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/measure_points.ipynb) for details on measuring intensity at point coordinates. For creating parametric map images, see [this notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/map_measurements.ipynb). + + + + + +## Features + +The user can select categories of features for feature extraction in the user interface. These categories contain measurements from the scikit-image [regionprops list of measurements](https://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.regionprops) library: + +* size: + + * area + + * bbox_area + + * convex_area + + * equivalent_diameter + +* intensity: + + * max_intensity + + * mean_intensity + + * min_intensity + + * standard_deviation_intensity (`extra_properties` implementation using numpy) + +* perimeter: + + * perimeter + + * perimeter_crofton + +* shape + + * major_axis_length + + * minor_axis_length + + * orientation + + * solidity + + * eccentricity + + * extent + + * feret_diameter_max + + * local_centroid + + * roundness as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + + * circularity as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + + * aspect_ratio as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + +* position: + + * centroid + + * bbox + + * weighted_centroid + +* moments: + + * moments + + * moments_central + + * moments_hu + + * moments_normalized + + + + + + + +This [napari] plugin was generated with [Cookiecutter] using with [@napari]'s [cookiecutter-napari-plugin] template. + + + +## See also + + + +There are other napari plugins with similar functionality for extracting features: + +* [morphometrics](https://www.napari-hub.org/plugins/morphometrics) + +* [PartSeg](https://www.napari-hub.org/plugins/PartSeg) + +* [napari-simpleitk-image-processing](https://www.napari-hub.org/plugins/napari-simpleitk-image-processing) + +* [napari-cupy-image-processing](https://www.napari-hub.org/plugins/napari-cupy-image-processing) + +* [napari-pyclesperanto-assistant](https://www.napari-hub.org/plugins/napari-pyclesperanto-assistant) + + + +Furthermore, there are plugins for postprocessing extracted measurements + +* [napari-feature-classifier](https://www.napari-hub.org/plugins/napari-feature-classifier) + +* [napari-clusters-plotter](https://www.napari-hub.org/plugins/napari-clusters-plotter) + +* [napari-accelerated-pixel-and-object-classification](https://www.napari-hub.org/plugins/napari-accelerated-pixel-and-object-classification) + + + +## Installation + + + +You can install `napari-skimage-regionprops` via [pip]: + + + + pip install napari-skimage-regionprops + + + +Or if you plan to develop it: + + + + git clone https://github.com/haesleinhuepf/napari-skimage-regionprops + + cd napari-skimage-regionprops + + pip install -e . + + + +If there is an error message suggesting that git is not installed, run `conda install git`. + + + +## Contributing + + + +Contributions are very welcome. Tests can be run with [tox], please ensure + +the coverage at least stays the same before you submit a pull request. + + + +## License + + + +Distributed under the terms of the [BSD-3] license, + +"napari-skimage-regionprops" is free and open source software + + + +## Issues + + + +If you encounter any problems, please create a thread on [image.sc] along with a detailed description and tag [@haesleinhuepf]. + + + +[napari]: https://github.com/napari/napari + +[Cookiecutter]: https://github.com/audreyr/cookiecutter + +[@napari]: https://github.com/napari + +[BSD-3]: http://opensource.org/licenses/BSD-3-Clause + +[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin + +[image.sc]: https://image.sc + +[napari]: https://github.com/napari/napari + +[tox]: https://tox.readthedocs.io/en/latest/ + +[pip]: https://pypi.org/project/pip/ + +[PyPI]: https://pypi.org/ + +[scikit-image]: https://scikit-image.org/ + +[@haesleinhuepf]: https://twitter.com/haesleinhuepf + + + +%package -n python3-napari-skimage-regionprops +Summary: A regionprops table widget plugin for napari +Provides: python-napari-skimage-regionprops +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-napari-skimage-regionprops +# napari-skimage-regionprops (nsr) + + + +[![License](https://img.shields.io/pypi/l/napari-skimage-regionprops.svg?color=green)](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/LICENSE) + +[![PyPI](https://img.shields.io/pypi/v/napari-skimage-regionprops.svg?color=green)](https://pypi.org/project/napari-skimage-regionprops) + +[![Python Version](https://img.shields.io/pypi/pyversions/napari-skimage-regionprops.svg?color=green)](https://python.org) + +[![tests](https://github.com/haesleinhuepf/napari-skimage-regionprops/workflows/tests/badge.svg)](https://github.com/haesleinhuepf/napari-skimage-regionprops/actions) + +[![codecov](https://codecov.io/gh/haesleinhuepf/napari-skimage-regionprops/branch/master/graph/badge.svg)](https://codecov.io/gh/haesleinhuepf/napari-skimage-regionprops) + +[![Development Status](https://img.shields.io/pypi/status/napari-skimage-regionprops.svg)](https://en.wikipedia.org/wiki/Software_release_life_cycle#Alpha) + +[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-skimage-regionprops)](https://napari-hub.org/plugins/napari-skimage-regionprops) + + + + + +A [napari] plugin for measuring properties of labeled objects based on [scikit-image] + + + +![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/interactive.gif) + + + +## Usage: measure region properties + + + +From the menu `Tools > Measurement > Regionprops (nsr)` you can open a dialog where you can choose an intensity image, a corresponding label image and the features you want to measure: + + + +![img.png](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/dialog.png) + + + +If you want to interface with the labels and see which table row corresponds to which labeled object, use the label picker and + +activate the `show selected` checkbox. + + + +![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/interactive.png) + + + +If you closed a table and want to reopen it, you can use the menu `Tools > Measurements > Show table (nsr)` to reopen it. + +You just need to select the labels layer the properties are associated with. + + + +For visualizing measurements with different grey values, as parametric images, you can double-click table headers. + + + +![img.png](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/label_value_visualization.gif) + + + +## Usage: measure point intensities + + + +Analogously, also the intensity and coordinates of point layers can be measured using the menu `Tools > Measurement > Measure intensity at point coordinates (nsr)`. + +Also these measurements can be visualized by double-clicking table headers: + + + +![img.png](measure_point_intensity.png) + + + +![img_1.png](measure_point_coordinate.png) + + + +## Working with time-lapse and tracking data + + + +Note that tables for time-lapse data should include a column named "frame", which indicates which slice in + +time the given row refers to. If you want to import your own csv files for time-lapse data make sure to include this column. + +If you have tracking data where each column specifies measurements for a track instead of a label at a specific time point, + +this column must not be added. + + + +In case you have 2D time-lapse data you need to convert it into a suitable shape using the function: `Tools > Utilities > Convert 3D stack to 2D time-lapse (time-slicer)`, + +which can be found in the [napari time slicer](https://www.napari-hub.org/plugins/napari-time-slicer). + + + +Last but not least, make sure that in case of time-lapse data the label image has labels that are subsquently labeled per timepoint. + +E.g. a dataset where label 5 is missing at timepoint 4 may be visualized incorrectly. + + + +## Usage: multichannel or multi-label data + + + +If you want to relate objects from one channels to objects from another channel, you can use `Tools > Measurement tables > Object Features/Properties (scikit-image, nsr)`. + +This plugin module allos you to answer questions like: + + - how many objects I have inside other objects? + + - what is the average intensity of the objects inside other objects? + +For that, you need at least two labeled images in napari. You can relate objects along with their features. + +If intensity features are also wanted, then you also need to provide two intensity images. + +Below, there is a small example on how to use it. + +Also, take a look at [this example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/measure_things_inside_things_plugin.ipynb). + + + + ![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/things_inside_things_demo.gif) + + + +## Usage, programmatically + + + +You can also control the tables programmatically. See this + +[example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/tables.ipynb) for details on regionprops and + +[this example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/measure_points.ipynb) for details on measuring intensity at point coordinates. For creating parametric map images, see [this notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/map_measurements.ipynb). + + + + + +## Features + +The user can select categories of features for feature extraction in the user interface. These categories contain measurements from the scikit-image [regionprops list of measurements](https://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.regionprops) library: + +* size: + + * area + + * bbox_area + + * convex_area + + * equivalent_diameter + +* intensity: + + * max_intensity + + * mean_intensity + + * min_intensity + + * standard_deviation_intensity (`extra_properties` implementation using numpy) + +* perimeter: + + * perimeter + + * perimeter_crofton + +* shape + + * major_axis_length + + * minor_axis_length + + * orientation + + * solidity + + * eccentricity + + * extent + + * feret_diameter_max + + * local_centroid + + * roundness as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + + * circularity as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + + * aspect_ratio as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + +* position: + + * centroid + + * bbox + + * weighted_centroid + +* moments: + + * moments + + * moments_central + + * moments_hu + + * moments_normalized + + + + + + + +This [napari] plugin was generated with [Cookiecutter] using with [@napari]'s [cookiecutter-napari-plugin] template. + + + +## See also + + + +There are other napari plugins with similar functionality for extracting features: + +* [morphometrics](https://www.napari-hub.org/plugins/morphometrics) + +* [PartSeg](https://www.napari-hub.org/plugins/PartSeg) + +* [napari-simpleitk-image-processing](https://www.napari-hub.org/plugins/napari-simpleitk-image-processing) + +* [napari-cupy-image-processing](https://www.napari-hub.org/plugins/napari-cupy-image-processing) + +* [napari-pyclesperanto-assistant](https://www.napari-hub.org/plugins/napari-pyclesperanto-assistant) + + + +Furthermore, there are plugins for postprocessing extracted measurements + +* [napari-feature-classifier](https://www.napari-hub.org/plugins/napari-feature-classifier) + +* [napari-clusters-plotter](https://www.napari-hub.org/plugins/napari-clusters-plotter) + +* [napari-accelerated-pixel-and-object-classification](https://www.napari-hub.org/plugins/napari-accelerated-pixel-and-object-classification) + + + +## Installation + + + +You can install `napari-skimage-regionprops` via [pip]: + + + + pip install napari-skimage-regionprops + + + +Or if you plan to develop it: + + + + git clone https://github.com/haesleinhuepf/napari-skimage-regionprops + + cd napari-skimage-regionprops + + pip install -e . + + + +If there is an error message suggesting that git is not installed, run `conda install git`. + + + +## Contributing + + + +Contributions are very welcome. Tests can be run with [tox], please ensure + +the coverage at least stays the same before you submit a pull request. + + + +## License + + + +Distributed under the terms of the [BSD-3] license, + +"napari-skimage-regionprops" is free and open source software + + + +## Issues + + + +If you encounter any problems, please create a thread on [image.sc] along with a detailed description and tag [@haesleinhuepf]. + + + +[napari]: https://github.com/napari/napari + +[Cookiecutter]: https://github.com/audreyr/cookiecutter + +[@napari]: https://github.com/napari + +[BSD-3]: http://opensource.org/licenses/BSD-3-Clause + +[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin + +[image.sc]: https://image.sc + +[napari]: https://github.com/napari/napari + +[tox]: https://tox.readthedocs.io/en/latest/ + +[pip]: https://pypi.org/project/pip/ + +[PyPI]: https://pypi.org/ + +[scikit-image]: https://scikit-image.org/ + +[@haesleinhuepf]: https://twitter.com/haesleinhuepf + + + +%package help +Summary: Development documents and examples for napari-skimage-regionprops +Provides: python3-napari-skimage-regionprops-doc +%description help +# napari-skimage-regionprops (nsr) + + + +[![License](https://img.shields.io/pypi/l/napari-skimage-regionprops.svg?color=green)](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/LICENSE) + +[![PyPI](https://img.shields.io/pypi/v/napari-skimage-regionprops.svg?color=green)](https://pypi.org/project/napari-skimage-regionprops) + +[![Python Version](https://img.shields.io/pypi/pyversions/napari-skimage-regionprops.svg?color=green)](https://python.org) + +[![tests](https://github.com/haesleinhuepf/napari-skimage-regionprops/workflows/tests/badge.svg)](https://github.com/haesleinhuepf/napari-skimage-regionprops/actions) + +[![codecov](https://codecov.io/gh/haesleinhuepf/napari-skimage-regionprops/branch/master/graph/badge.svg)](https://codecov.io/gh/haesleinhuepf/napari-skimage-regionprops) + +[![Development Status](https://img.shields.io/pypi/status/napari-skimage-regionprops.svg)](https://en.wikipedia.org/wiki/Software_release_life_cycle#Alpha) + +[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-skimage-regionprops)](https://napari-hub.org/plugins/napari-skimage-regionprops) + + + + + +A [napari] plugin for measuring properties of labeled objects based on [scikit-image] + + + +![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/interactive.gif) + + + +## Usage: measure region properties + + + +From the menu `Tools > Measurement > Regionprops (nsr)` you can open a dialog where you can choose an intensity image, a corresponding label image and the features you want to measure: + + + +![img.png](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/dialog.png) + + + +If you want to interface with the labels and see which table row corresponds to which labeled object, use the label picker and + +activate the `show selected` checkbox. + + + +![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/interactive.png) + + + +If you closed a table and want to reopen it, you can use the menu `Tools > Measurements > Show table (nsr)` to reopen it. + +You just need to select the labels layer the properties are associated with. + + + +For visualizing measurements with different grey values, as parametric images, you can double-click table headers. + + + +![img.png](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/label_value_visualization.gif) + + + +## Usage: measure point intensities + + + +Analogously, also the intensity and coordinates of point layers can be measured using the menu `Tools > Measurement > Measure intensity at point coordinates (nsr)`. + +Also these measurements can be visualized by double-clicking table headers: + + + +![img.png](measure_point_intensity.png) + + + +![img_1.png](measure_point_coordinate.png) + + + +## Working with time-lapse and tracking data + + + +Note that tables for time-lapse data should include a column named "frame", which indicates which slice in + +time the given row refers to. If you want to import your own csv files for time-lapse data make sure to include this column. + +If you have tracking data where each column specifies measurements for a track instead of a label at a specific time point, + +this column must not be added. + + + +In case you have 2D time-lapse data you need to convert it into a suitable shape using the function: `Tools > Utilities > Convert 3D stack to 2D time-lapse (time-slicer)`, + +which can be found in the [napari time slicer](https://www.napari-hub.org/plugins/napari-time-slicer). + + + +Last but not least, make sure that in case of time-lapse data the label image has labels that are subsquently labeled per timepoint. + +E.g. a dataset where label 5 is missing at timepoint 4 may be visualized incorrectly. + + + +## Usage: multichannel or multi-label data + + + +If you want to relate objects from one channels to objects from another channel, you can use `Tools > Measurement tables > Object Features/Properties (scikit-image, nsr)`. + +This plugin module allos you to answer questions like: + + - how many objects I have inside other objects? + + - what is the average intensity of the objects inside other objects? + +For that, you need at least two labeled images in napari. You can relate objects along with their features. + +If intensity features are also wanted, then you also need to provide two intensity images. + +Below, there is a small example on how to use it. + +Also, take a look at [this example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/measure_things_inside_things_plugin.ipynb). + + + + ![](https://github.com/haesleinhuepf/napari-skimage-regionprops/raw/master/images/things_inside_things_demo.gif) + + + +## Usage, programmatically + + + +You can also control the tables programmatically. See this + +[example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/tables.ipynb) for details on regionprops and + +[this example notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/measure_points.ipynb) for details on measuring intensity at point coordinates. For creating parametric map images, see [this notebook](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/demo/map_measurements.ipynb). + + + + + +## Features + +The user can select categories of features for feature extraction in the user interface. These categories contain measurements from the scikit-image [regionprops list of measurements](https://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.regionprops) library: + +* size: + + * area + + * bbox_area + + * convex_area + + * equivalent_diameter + +* intensity: + + * max_intensity + + * mean_intensity + + * min_intensity + + * standard_deviation_intensity (`extra_properties` implementation using numpy) + +* perimeter: + + * perimeter + + * perimeter_crofton + +* shape + + * major_axis_length + + * minor_axis_length + + * orientation + + * solidity + + * eccentricity + + * extent + + * feret_diameter_max + + * local_centroid + + * roundness as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + + * circularity as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + + * aspect_ratio as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html#set) + +* position: + + * centroid + + * bbox + + * weighted_centroid + +* moments: + + * moments + + * moments_central + + * moments_hu + + * moments_normalized + + + + + + + +This [napari] plugin was generated with [Cookiecutter] using with [@napari]'s [cookiecutter-napari-plugin] template. + + + +## See also + + + +There are other napari plugins with similar functionality for extracting features: + +* [morphometrics](https://www.napari-hub.org/plugins/morphometrics) + +* [PartSeg](https://www.napari-hub.org/plugins/PartSeg) + +* [napari-simpleitk-image-processing](https://www.napari-hub.org/plugins/napari-simpleitk-image-processing) + +* [napari-cupy-image-processing](https://www.napari-hub.org/plugins/napari-cupy-image-processing) + +* [napari-pyclesperanto-assistant](https://www.napari-hub.org/plugins/napari-pyclesperanto-assistant) + + + +Furthermore, there are plugins for postprocessing extracted measurements + +* [napari-feature-classifier](https://www.napari-hub.org/plugins/napari-feature-classifier) + +* [napari-clusters-plotter](https://www.napari-hub.org/plugins/napari-clusters-plotter) + +* [napari-accelerated-pixel-and-object-classification](https://www.napari-hub.org/plugins/napari-accelerated-pixel-and-object-classification) + + + +## Installation + + + +You can install `napari-skimage-regionprops` via [pip]: + + + + pip install napari-skimage-regionprops + + + +Or if you plan to develop it: + + + + git clone https://github.com/haesleinhuepf/napari-skimage-regionprops + + cd napari-skimage-regionprops + + pip install -e . + + + +If there is an error message suggesting that git is not installed, run `conda install git`. + + + +## Contributing + + + +Contributions are very welcome. Tests can be run with [tox], please ensure + +the coverage at least stays the same before you submit a pull request. + + + +## License + + + +Distributed under the terms of the [BSD-3] license, + +"napari-skimage-regionprops" is free and open source software + + + +## Issues + + + +If you encounter any problems, please create a thread on [image.sc] along with a detailed description and tag [@haesleinhuepf]. + + + +[napari]: https://github.com/napari/napari + +[Cookiecutter]: https://github.com/audreyr/cookiecutter + +[@napari]: https://github.com/napari + +[BSD-3]: http://opensource.org/licenses/BSD-3-Clause + +[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin + +[image.sc]: https://image.sc + +[napari]: https://github.com/napari/napari + +[tox]: https://tox.readthedocs.io/en/latest/ + +[pip]: https://pypi.org/project/pip/ + +[PyPI]: https://pypi.org/ + +[scikit-image]: https://scikit-image.org/ + +[@haesleinhuepf]: https://twitter.com/haesleinhuepf + + + +%prep +%autosetup -n napari-skimage-regionprops-0.10.0 + +%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-napari-skimage-regionprops -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Thu May 18 2023 Python_Bot - 0.10.0-1 +- Package Spec generated -- cgit v1.2.3