Metadata-Version: 1.1
Name: FastDRaW
Version: 1.2.1
Summary: Image segmentation algorithm using Fast Delineation by RAndom Walker
Home-page: https://github.com/hgueziri/FastDRaW-Segmentation
Author: Houssem-Eddine Gueziri
Author-email: houssem-eddine.gueziri.1@etsmtl.net
License: MIT
Download-URL: https://github.com/hgueziri/FastDRaW-Segmentation/archive/1.2.tar.gz
Description: # FastDRaW
        FastDRaW – Fast Delineation by Random
        
        This software is under the MIT License. If you use this code in your research please cite the following paper:
        
        H.-E. Gueziri, L. Lakhdar, M. J. McGuffin and C. Laporte "FastDRaW – Fast Delineation by Random Walker: application to large images", MICCAI workshop on Interactive Medical Image Computing (IMIC), Athens, Greece, (2016).
        
        @author Houssem-Eddine Gueziri
        
        ## Requirements:
        
        FastDRaW requires the following packages
        
        - [Scipy and Numpy](https://www.scipy.org/install.html)
        - [PyAMG](http://pyamg.org/) (for linear system solver)
        
        Or run
        
        ```shell
        sudo apt-get install build-essential python2.7-dev
        sudo pip install -r requirements.txt
        ```
        
        ## Install:
        
        From PyPI:
        
        ```shell
        sudo pip install FastDRaW
        ```
        From git repository:
        
        ```shell
        git clone https://github.com/hgueziri/FastDRaW-Segmentation.git
        cd FastDRaW-Segmentation
        sudo python setup.py install
        ```
        
        ## Usage example:
        
        ```python
        >>> from FastDRaW import Segmenter
        >>> from skimage.data import coins
        >>> import matplotlib.pyplot as plt
        >>> image = coins()
        >>> labels = np.zeros_like(image)
        >>> labels[[129, 199], [155, 155]] = 1 # label some pixels as foreground
        >>> labels[[162, 224], [131, 184]] = 2 # label some pixels as background
        >>> fastdraw = Segmenter(image, beta=100, downsampled_size=[100,100])
        >>> segm = fastdraw.update(labels)
        >>> plt.imshow(image,'gray')
        >>> plt.imshow(segm, alpha=0.7)
        ```
        
        
        
Keywords: segmentation,fastdraw,medical
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
