Metadata-Version: 1.1
Name: Sid
Version: 0.2.0
Summary:  Image processing for seed images
Home-page: https://github.com/yoavram/Sid
Author: Yoav Ram
Author-email: yoav@yoavram.com
License: MIT
Description: # Sid
        ## Image processing for seed images
        
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        Python script for image processing of plant seed images, specifically _Lamium amplexicaule_.
        
        [![PyPI](https://img.shields.io/pypi/v/Sid.svg)](https://pypi.python.org/pypi/Sid/)
        [![Supported Python versions](https://img.shields.io/pypi/pyversions/Sid.svg)](https://pypi.python.org/pypi/Sid/)
        [![License](https://img.shields.io/pypi/l/Sid.svg)](https://github.com/yoavram/Sid/blob/master/LICENCE.txt)
        [![Build Status](https://travis-ci.org/yoavram/Sid.svg)](https://travis-ci.org/yoavram/Sid)
        [![codecov.io](http://codecov.io/github/yoavram/Sid/coverage.svg?branch=master)](http://codecov.io/github/yoavram/Sid)
        
        ## Requirements
        
        - Python 2.7
        - PIL/Pillow
        - numpy
        - scipy.ndimage
        - scikit-image
        - matplotlib
        - watchdog
        - click
        
        For testing and documentation:
        
        - nose
        - coverage
        - sphinx
        
        ## Install
        
        1. Install the [Anaconda Python 2.7 distribution](https://www.continuum.io/downloads).
        1. Install Sid using pip:
        ```
        pip install Sid
        ```
        1. Check that Sid was installed properly:
        ```
        take_cover --version
        ```
        
        ### Developers
        
        Sid can also be used by cloning the repository, usually for developing purposes:
        ```
        git clone https://github.com/yoavram/Sid.git
        ```
        or by downloading the repository as a [zip file](https://github.com/yoavram/Sid/archive/master.zip).
        
        ## Usage
        
        ### take_cover
        
        Use by running:
        ```
        take_cover
        ```
        The script will first ask for a folder name - this will be the working directory from which the script will read _jpg_ files and to which it will write _png_ and _csv_ files.
        
        The script will then ask if the folder should be prcoessed Continuously or once.
        
        For more options, see the help message:
        ```
        take_cover --help
        ```
        
        ## Continuous processing
        
        In this case the script will wait for new _jpg_ files in the folder. When a new _jpg_ file is created, the script will process it, creating _png_ files with the color spaces and the segmentation checkpoints, open the segmentation image, and will print the final stats to the screen.
        
        ## Single processing
        
        In this case the script will go over all _jpg_ files in the folder and process them. It will produce _png_ files with the color spaces and the segmentation checkpoints and two _csv_ files: one with the final stats for each _jpg_ file and one with the histograms that were used to find the features on the seed (background, eliosom, cover). 
        
        ### take_cover.json
        
        This is the configuration file which includes values of different parameters of the algorithm, including segmentation thresholds. 
        
        ## Support
        Don't hesitate to contact [Yoav Ram](http://www.yoavram.com) for questions and help.
        
        Bugs and feature requests can be opened on [GitHub](https://github.com/yoavram/Sid/issues) 
        
        [![GitHub issues](https://img.shields.io/github/issues/yoavram/Sid.svg)](https://github.com/yoavram/Sid)
        
        
        ## License
        
        Sid source code and examples are licensed under the terms of the [MIT license](http://opensource.org/licenses/MIT).
        
        Sid documentation, examples, and other materials are licensed under the terms of the [Creative Commons Attribution 4.0 International (CC BY 4.0) license](https://creativecommons.org/licenses/by/4.0/).
        
        
Keywords: biology image-processing plant-science
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2.7
Classifier: Operating System :: OS Independent
