Operations using blobs

Detailed Description

Collaboration diagram for Operations using blobs:

Functions
template<typename T >
RES_T	areaThreshold (const Image< T > &imIn, const int threshold, Image< T > &imOut, const bool gt=true)
	areaThreshold() -
template<typename T , typename labelT >
map< labelT, Vector_double >	blobsInertiaMatrix (const Image< T > &imIn, map< labelT, Blob > &blobs, const bool central=false)
	blobsInertiaMatrix() -
template<typename T >
map< T, Vector_double >	blobsInertiaMatrix (const Image< T > &imLbl, const bool onlyNonZero=true, const bool central=false)
	blobsInertiaMatrix() -

Function Documentation

areaThreshold()

template<typename T >

RES_T areaThreshold	(	const Image< T > &	imIn,
		const int	threshold,
		Image< T > &	imOut,
		const bool	gt = true
	)

areaThreshold() -

Parameters

[in]	imIn	: input binary image
[in]	threshold	: threshold level
[out]	imOut	: output image
[in]	gt	: blobs which area is greater than will be retained if gt is true, and lesser than if gt is false.

Note

• output image is of the same kind of input image : binary or labeled.

Example

import smilPython as sp
import time
 
thresh = 1000
 
im = sp.Image("https://smil.cmm.minesparis.psl.eu/images/balls.png")
iml = sp.Image(im)
img = sp.Image(im)
ims = sp.Image(im)
 
sp.label(im, iml)
 
im.show("balls.png")
iml.showLabel("iml")
 
sp.areaThreshold(iml, thresh, True, img)
img.showLabel("img")
sp.areaThreshold(im, thresh, False, ims)
ims.show("ims")
 
nlold = 0
for threshold in range(1, 6000, 20):
    sp.areaThreshold(im, threshold, True, ims)
    nl = sp.label(ims, iml)
    if nl != nlold:
        print(' Threshold {:6d} : {:3d} blobs'.format(threshold, nl))
        sp.Gui.processEvents()
        time.sleep(1)
    if nl == 0:
        break
    nlold = nl

blobsInertiaMatrix() [1/2]

template<typename T , typename labelT >

map< labelT, Vector_double > blobsInertiaMatrix	(	const Image< T > &	imIn,
		map< labelT, Blob > &	blobs,
		const bool	central = false
	)

blobsInertiaMatrix() -

Parameters

[in]	imIn	: input image
[in]	blobs	: blobs in the image
[in]	central	: blobs centered on their barycenters

Example

import smilPython as sp
import numpy as np
from numpy import linalg as la
 
# get image
imIn = sp.Image("https://smil.cmm.minesparis.psl.eu/images/tools.png")
 
# labelize input image
imThr = sp.Image(imIn)
sp.topHat(imIn, imThr, sp.hSE(20))
sp.threshold(imThr, imThr)
imLbl = sp.Image(imIn, "UINT16")
sp.label(imThr, imLbl)
 
# compute blobs and get their data
blobs   = sp.computeBlobs(imLbl)
central = True
inertia = sp.blobsInertiaMatrix(imIn, blobs, central)
barys   = sp.blobsBarycenter(imIn, blobs)
 
nshape = (2, 2)
if imIn.getDimension() == 3:
  nshape = (3, 3)
 
for k in inertia.keys():
    print("=" * 64)
    s = ""
    for v in barys[k]:
        s += " {:6.1f}".format(v)
    print("Blob label : {:3d} - Barycenter :{:}".format(k, s))
    # Smil returns inertia matrix as a vector. Reshape it.
    xi = np.array(inertia[k])
    xi = xi.reshape(nshape)
    np.set_printoptions(precision=3)
    print("    ====== Inertia Matrix")
    print(xi)
    # let numpy evaluate eingenvalues and eingenvectors
    w, v = la.eig(xi)
    print("    ====== Eingenvalues")
    print(w)
    print("    ====== Eingenvectors")
    print(v)
 

blobsInertiaMatrix() [2/2]

template<typename T >

map< T, Vector_double > blobsInertiaMatrix	(	const Image< T > &	imLbl,
		const bool	onlyNonZero = true,
		const bool	central = false
	)

blobsInertiaMatrix() -

Parameters

[in]	imLbl	: input labeled image
[in]	onlyNonZero	:
[in]	central	: blobs centered on their barycenters