slcpy 0.1.7

Python package to decode Amira 3D coordinate spatial graphs into semantic label mask

Semantic Label Creator [slcpy]

Python package to decode Amira 3D coordinate spatial graphs into semantic label mask.

• Documentation: https://semantic-label-creator.readthedocs.io/en/latest/

Features

• Load Amira spatial graph to transform 3D coordinates into semantic label mask

Installation

Stable release

To install Semantic_Label_Creator, run this command in your terminal:

$ pip install slcpy

This is the preferred method to install Semantic_Label_Creator, as it will always install the most recent stable release.

From sources

The sources for Semantic_Label_Creator can be downloaded from the Github repo.

You can either clone the public repository:

$ git clone git://github.com/RRobert92/Semantic_Label_Creator

Once you have a copy of the source, you can install it with:

$ python setup.py install

Usage

To use Semantic_Label_Creator in a project:

from slcpy.main import slcpy
label_mask = slcpy(dir_path, pixel_size=None, circle_size=250)

or with terminal:

   slcpy -dir -o -px -d

string [-dir] directory of the folder that contain data.
   [-default] os.getcwd() + r'\data'
string [-o] output directory to the folder where all of converted filed are stored.
   [-default] os.getcwd() + r'\data' + r'\output'
int [-px] anisotropic images pixel size in Angstrom.
   [-default] None
int [-d] diameter in Angstrom of a circle that would be drawn a semantic mask
   [-default] 250

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.