def __call__(self, image):
if config.dimension() == 2:
dbls = oofimage.grayify(image)
bools = oofimage.threshold(dbls,self.T)
oofimage.setFromBool(image,bools)
elif config.dimension() == 3:
image.threshold(self.T)
def __call__(self, image):
if config.dimension() == 2:
dbls = oofimage.grayify(image)
bools = oofimage.threshold(dbls, self.T)
oofimage.setFromBool(image, bools)
elif config.dimension() == 3:
image.threshold(self.T)
def __call__(self, image):
dbls = oofimage.grayify(image)
temp = imageops.gaussSmooth(dbls,self.stdDev)
scaled = imageops.scaleArray2(temp, 0.0, 1.0)
imageops.setFromArray(image,scaled)
def __call__(self, image):
dbls = oofimage.grayify(image)
temp = imageops.gaussSmooth(dbls, self.stdDev)
scaled = imageops.scaleArray2(temp, 0.0, 1.0)
imageops.setFromArray(image, scaled)
def __call__(self, image):
dbls = oofimage.grayify(image)
temp1=imageops.sobel(dbls,0)
temp2=imageops.sobel(dbls,2)
combined=imageops.combineVals(temp1,temp2)
scaled = imageops.scaleArray2(combined, 0.0, 1.0)
imageops.setFromArray(image,scaled)
def __call__(self, image):
dbls = oofimage.grayify(image)
temp1 = imageops.sobel(dbls, 0)
temp2 = imageops.sobel(dbls, 2)
combined = imageops.combineVals(temp1, temp2)
scaled = imageops.scaleArray2(combined, 0.0, 1.0)
imageops.setFromArray(image, scaled)
def __call__(self, image):
dbls = oofimage.grayify(image)
for i in range(self.numAngles):
phi = i * 180. / self.numAngles
current = imageops.modGabor(dbls, self.a, self.b, phi)
if i != 0:
old = imageops.findLargerVals(current, old)
else:
old = current
scaled = imageops.scaleArray2(old, 0.0, 1.0)
imageops.setFromArray(image, scaled)
def __call__(self, image):
dbls = oofimage.grayify(image)
for i in range(self.numAngles):
phi = i*180./self.numAngles
current = imageops.modGabor(dbls,self.a,self.b,phi)
if i!=0:
old=imageops.findLargerVals(current,old)
else:
old=current
scaled = imageops.scaleArray2(old, 0.0, 1.0)
imageops.setFromArray(image,scaled)
def __call__(self, image):
dbls = oofimage.grayify(image)
for i in range(self.numAngles):
phi = i * 180. / self.numAngles
current = imageops.realGabor(dbls, self.a, self.b, phi)
if i != 0:
old = imageops.findLargerVals(current, old)
else:
old = current
scaled = imageops.scaleArray(old, 0.0, 1.0, self.Line_color)
bools = imageops.connect(scaled, self.Threshold, self.t, self.d,
self.n, self.B, self.trimYN)
oofimage.setFromBool(image, bools)
def __call__(self, image):
dbls=oofimage.grayify(image)
for i in range(self.numAngles):
phi = i*180./self.numAngles
current = imageops.realGabor(dbls,self.a,self.b,phi)
if i!=0:
old=imageops.findLargerVals(current,old)
else:
old=current
scaled = imageops.scaleArray(old, 0.0, 1.0,self.Line_color)
bools=imageops.connect(scaled,self.Threshold,self.t,self.d,self.n,
self.B,self.trimYN)
oofimage.setFromBool(image,bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
largest = imageops.canny(dbls, self.stdDev)
## smoothed = imageops.gaussSmooth(dbls,self.stdDev)
## for i in range(4):
## temp=imageops.sobel(smoothed,i)
## if i!=0:
## largest=imageops.findLargerVals(largest,temp)
## else:
## largest=temp
scaled = imageops.scaleArray2(largest, 0.0, 1.0)
imageops.setFromArray(image, scaled)
def __call__(self, image):
dbls = oofimage.grayify(image)
largest=imageops.canny(dbls,self.stdDev)
## smoothed = imageops.gaussSmooth(dbls,self.stdDev)
## for i in range(4):
## temp=imageops.sobel(smoothed,i)
## if i!=0:
## largest=imageops.findLargerVals(largest,temp)
## else:
## largest=temp
scaled = imageops.scaleArray2(largest, 0.0, 1.0)
imageops.setFromArray(image,scaled)
def __call__(self, image):
## dbls=imageops.grayify(image)
## final = imageops.newGabor(dbls,self.a,self.b,0)
## gradDirs=intarray.makeIntArray(image.sizeInPixels(),0)
## for i in range(self.numAngles-1):
## phi = (i+1)*180./self.numAngles
## temp = imageops.newGabor(dbls,self.a,self.b,phi)
## final = imageops.findLargerVals2(final,temp,gradDirs,i+1)
## scaled = imageops.scaleArray(final,0.0,1.0,self.Line_color)
## scaled = imageops.nonmaxSuppress(scaled,gradDirs);
## imageops.setFromArray(image,scaled)
dbls = oofimage.grayify(image)
for i in range(self.numAngles):
phi = i*180./self.numAngles
current = imageops.newGabor(dbls,self.a,self.b,phi)
if i!=0:
old=imageops.findLargerVals(current,old)
else:
old=current
scaled = imageops.scaleArray(old, 0.0, 1.0,self.Line_color)
imageops.setFromArray(image,scaled)
def __call__(self, image):
## dbls=imageops.grayify(image)
## final = imageops.newGabor(dbls,self.a,self.b,0)
## gradDirs=intarray.makeIntArray(image.sizeInPixels(),0)
## for i in range(self.numAngles-1):
## phi = (i+1)*180./self.numAngles
## temp = imageops.newGabor(dbls,self.a,self.b,phi)
## final = imageops.findLargerVals2(final,temp,gradDirs,i+1)
## scaled = imageops.scaleArray(final,0.0,1.0,self.Line_color)
## scaled = imageops.nonmaxSuppress(scaled,gradDirs);
## imageops.setFromArray(image,scaled)
dbls = oofimage.grayify(image)
for i in range(self.numAngles):
phi = i * 180. / self.numAngles
current = imageops.newGabor(dbls, self.a, self.b, phi)
if i != 0:
old = imageops.findLargerVals(current, old)
else:
old = current
scaled = imageops.scaleArray(old, 0.0, 1.0, self.Line_color)
imageops.setFromArray(image, scaled)
def __call__(self,image):
dbls=oofimage.grayify(image)
bool1=oofimage.threshold(dbls,.5)
imageops.compare(bool1,self.val)
def __call__(self, image):
dbls = oofimage.grayify(image)
dbls = imageops.spread2(dbls, self.T)
imageops.setFromArray(image, dbls)
def __call__(self, image):
dbls = oofimage.grayify(image)
dbls = imageops.addNoise(dbls, self.Standard_deviation)
imageops.setFromArray(image, dbls)
def __call__(self, image):
dbls = oofimage.grayify(image)
# bools=oofimage.threshold(dbls,.5)
bools = imageops.connecter(dbls, self.Threshold, self.t, self.d,
self.n, self.B, self.trimYN)
oofimage.setFromBool(image, bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
bools = imageops.hysteresisThresh(dbls,self.T1,self.T2)
oofimage.setFromBool(image,bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
bools = oofimage.threshold(dbls, .5)
hough = imageops.houghTrans(bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
bools = oofimage.threshold(dbls, self.T)
oofimage.setFromBool(image, bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
temp = imageops.laplacian(dbls)
scaled = imageops.scaleArray2(temp, 0.0, 1.0)
imageops.setFromArray(image,scaled)
def __call__(self,image):
dbls=oofimage.grayify(image)
# bools=oofimage.threshold(dbls,.5)
bools=imageops.connecter(dbls,self.Threshold,self.t,self.d,self.n,
self.B,self.trimYN)
oofimage.setFromBool(image,bools)
def __call__(self,image):
dbls=oofimage.grayify(image)
dbls=imageops.addNoise(dbls,self.Standard_deviation)
imageops.setFromArray(image,dbls)
def __call__(self, image):
dbls = oofimage.grayify(image)
bools = oofimage.threshold(dbls,self.T)
oofimage.setFromBool(image,bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
imageops.printHistogram(dbls, self.val)
def __call__(self, image):
dbls = oofimage.grayify(image)
bool1 = oofimage.threshold(dbls, .5)
imageops.compare(bool1, self.val)
def __call__(self,image):
dbls=oofimage.grayify(image)
imageops.printHistogram(dbls,self.val)
def __call__(self, image):
dbls = oofimage.grayify(image)
bools = imageops.hysteresisThresh(dbls, self.T1, self.T2)
oofimage.setFromBool(image, bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
bools = oofimage.threshold(dbls,.5)
hough = imageops.houghTrans(bools)
def __call__(self, image):
dbls = oofimage.grayify(image)
temp = imageops.laplacian(dbls)
scaled = imageops.scaleArray2(temp, 0.0, 1.0)
imageops.setFromArray(image, scaled)
def __call__(self,image):
dbls=oofimage.grayify(image)
dbls=imageops.spread2(dbls,self.T)
imageops.setFromArray(image,dbls)