Skip to content

rshkarin/quanfima

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

31 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

image


image

Documentation Status

image

Quanfima (quantitative analysis of fibrous materials) is a collection of useful functions for morphological analysis and visualization of 2D/3D data from various areas of material science. The aim is to simplify the analysis process by providing functionality for frequently required tasks in the same place.

More examples of usage you can find in the documentation.

  • Analysis of fibrous structures by tensor-based method in 2D / 3D datasets.
  • Estimation of structure diameters in 2D / 3D by a ray-casting method.
  • Counting of particles in 2D / 3D datasets and providing a detailed report in pandas.DataFrame format.
  • Calculation of porosity measure for each material in 2D / 3D datasets.
  • Visualization in 2D / 3D using matplotlib, visvis packages.

Installation

The easiest way to install the latest version is by using pip:

$ pip install quanfima

You may also use Git to clone the repository and install it manually:

$ git clone https://github.com/rshkarin/quanfima.git
$ cd quanfima
$ python setup.py install

Usage

Open a grayscale image, perform segmentation, estimate porosity, analyze fiber orientation and diameters, and plot the results.

import numpy as np
from skimage import io, filters
from quanfima import morphology as mrph
from quanfima import visualization as vis
from quanfima import utils

img = io.imread('../data/polymer_slice.tif')

th_val = filters.threshold_otsu(img)
img_seg = (img > th_val).astype(np.uint8)

# estimate porosity
pr = mrph.calc_porosity(img_seg)
for k,v in pr.items():
  print 'Porosity ({}): {}'.format(k, v)

# prepare data and analyze fibers
data, skeleton, skeleton_thick = utils.prepare_data(img_seg)
cskel, fskel, omap, dmap, ovals, dvals = \
                    mrph.estimate_fiber_properties(data, skeleton)

# plot results
vis.plot_orientation_map(omap, fskel, min_label=u'0°', max_label=u'180°',
                         figsize=(10,10),
                         name='2d_polymer',
                         output_dir='/path/to/output/dir')
vis.plot_diameter_map(dmap, cskel, figsize=(10,10), cmap='gist_rainbow',
                      name='2d_polymer',
                      output_dir='/path/to/output/dir')
>> Porosity (Material 1): 0.845488888889

image

image

image