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.
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
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
