Morph-M

h1. Morph-M Python - Neighborhood Operator

Example 1: Erosion. This generic function, create a list with all neighborhord values. These values are send to its operator and rthe return value will be put on center.

<pre><code class="ruby">

def MyErode(imIn, nl, imOut):

	# version lambda:

	morphee.ImNeighborhoodUnaryOperation(imIn, nl, lambda l:min(l), imOut)

	# version that directly use the python function 'min':

	morphee.ImNeighborhoodUnaryOperation(imIn, nl, min, imOut)

if __name__=='__main__':

  im8=morphee.fileRead(os.path.join(images_dir_gray,"foreman.png"))

  imOut=morphee.getSame(im8)

  imOut_2=morphee.getSame(im8)

  nl=morphee.NeighborList.neighborsSquare2D

  # version Python:

  MyErode(im8,nl,imOut)

  # version C++:

  morphee.ImErode(im8,nl,imOut_2)

  # vérification:

  morphee.pngFileWrite(imOut,os.path.join(temp_dir,"ero1.png"))

  morphee.pngFileWrite(imOut_2,os.path.join(temp_dir,"ero2.png"))

  for p1,p2 in zip(imOut.imageData(), imOut_2.imageData()):

	assert(p1==p2)

</code></pre>

*Rank Filter*

<pre><code class="ruby">

class RankOrder:

	def __init__(self, quantile):

		# on stocke la valeur du quantile:

		self.quantile=quantile

	def __call__(self, pyt):

		l=list(pyt)

		# l est la liste des valeurs des voisins

		l.sort()

		# conversion quantile/index:

		index=int(len(l)*self.quantile)

		if index >= len(l):# si on dépasse, on prend le dernier

			index=-1# -1 est le dernier élément de la liste

		return l[index]

def ImRankOrder(imIn, nl, quantile, imOut):

	op=RankOrder(quantile)

	morphee.ImNeighborhoodUnaryOperation(imIn,nl,op,imOut)

# min (erosion)

ImRankOrder(im8,nl,0,imOut)

# check results:

morphee.ImErode(im8,nl,imOut_2)

for p1,p2 in zip(imOut.imageData(), imOut_2.imageData()):

	assert(p1==p2)

# max (dilatation)

ImRankOrder(im8,nl,1,imOut)

# check results:

morphee.ImDilate(im8,nl,imOut_2)

for p1,p2 in zip(imOut.imageData(), imOut_2.imageData()):

	assert(p1==p2)

# quantile à 0.25:

ImRankOrder(im8,nl,0.25,imOut)

# check results:

for pOut,pIn in zip(imOut.imageData(), im8.imageData()):

	try:

		assert(pOut<=pIn)

	except:

		pass

		#print "Opérateur non anti-extensif: ",pOut, pIn

</code></pre>

Filtre de rang, avec [anti]extensivité garantie

<pre><code class="ruby">

class RankOrderWithExtensivity:

	def __init__(self, quantile):

		self.quantile=quantile

		if quantile > 0.5:	

			self.f=max

		elif quantile < 0.5:

			self.f=min

		else:

			self.f=None

	def __call__(self, pyt,center):

		l=list(pyt)

		l.sort()

		index=int(len(l)*self.quantile)

		if index == len(l):

			index=-1

		if self.f:

			# selon que l'on a choisi un quantile

			# dans la moitié supérieure ou inférieure,

			# on prend le max (resp. min) avec le centre,

			# pour garantir imOut>=imIn (resp <=)

			return self.f(center, l[index])

		else:

			return l[index]

def ImRankOrderWithExtensivity(imIn, nl, quantile, imOut):

	op=RankOrderWithExtensivity(quantile)

	morphee.ImNeighborhoodUnaryOperationWithCenter(imIn,nl,op,imOut)

# quantile à 0.25 sauf si on est pas en-dessous

ImRankOrderWithExtensivity(im8,nl,0.25,imOut)

# Check results

for pOut,pIn in zip(imOut.imageData(), im8.imageData()):

	try:

		assert(pOut<=pIn)

	except:

		print "Opérateur complexe non anti-extensif: ",pOut, pIn

</code></pre>

Minkowski Addition (dual dilatation)

<pre><code class="ruby">

def MinkowskiAdditionOperator(pyt,center):

	while pyt.isNotFinished():

		if pyt.getPixel() < center:

			pyt.setPixel(center)

		pyt.next()

def MyMinkowskiAddition(imIn, nl, imOut):

	morphee.ImUnaryOperationOnNeighborhoodWithCenter(imIn,nl,MinkowskiAdditionOperator,imOut)

# Addition de minkowski (dilatation duale)

# version Python:

MyMinkowskiAddition(im8,nl,imOut)

# version C++:

morphee.ImMinkowskiAddition(im8,nl,imOut_2)

morphee.pngFileWrite(imOut,os.path.join(temp_dir,"dil1.png"))

morphee.pngFileWrite(imOut_2,os.path.join(temp_dir,"dil2.png"))

for p1,p2 in zip(imOut.imageData(), imOut_2.imageData()):

	assert(p1==p2)

</code></pre>