def processImage(self, imgdata, filtarray):
imgarray = imgdata['image']
looptdiff = time.time()-self.proct0
self.proct0 = time.time()
dogarrays = apDog.diffOfGaussParam(filtarray, self.params)
proctdiff = time.time()-self.proct0
f = open("dog_image_timing.dat", "a")
datstr = "%d\t%.5f\t%.5f\n"%(self.stats['count'], proctdiff, looptdiff)
f.write(datstr)
f.close()
apDisplay.printMsg("finished DoG filter")
peaktree = apPeaks.findPeaks(imgdata, dogarrays, self.params, maptype="dogmap")
return peaktree
def processImage(self, imgdata, filtarray):
imgarray = imgdata['image']
looptdiff = time.time()-self.proct0
self.proct0 = time.time()
dogarrays = apDog.diffOfGaussParam(filtarray, self.params)
proctdiff = time.time()-self.proct0
f = open("dog_image_timing.dat", "a")
datstr = "%d\t%.5f\t%.5f\n"%(self.stats['count'], proctdiff, looptdiff)
f.write(datstr)
f.close()
apDisplay.printMsg("finished DoG filter")
peaktree = apPeaks.findPeaks(imgdata, dogarrays, self.params, maptype="dogmap")
return peaktree
def findPeaks(self, imgdata, ccmaplist):
return apPeaks.findPeaks(imgdata, ccmaplist, self.params)
def onRunDogPicker(self, evt):
apDisplay.printColor("===============\nRunning experimental DoGPicker","cyan")
### remove existing maps
lefts = glob.glob("maps/leftimage.dogmap*.jpg")
for imgname in lefts:
apFile.removeFile(imgname, warn=False)
rights = glob.glob("maps/rightimage.dogmap*.jpg")
for imgname in rights:
apFile.removeFile(imgname, warn=False)
pixdiam = self.diam.GetValue()
sizerange = self.srange.GetValue()
minthresh = self.minthresh.GetValue()
maxthresh = self.maxthresh.GetValue()
peakarea = self.peakarea.GetValue()
invert = self.partContrast(None)
maxpeaks = self.maxpeaks.GetValue()
numslices = self.numslices.GetValue()
if invert is True:
apDisplay.printMsg("Picking dark particles on light backgound, i.e. ice")
else:
apDisplay.printMsg("Picking light particles on dark backgound, i.e. stain")
self.Close()
apParam.createDirectory("maps")
#1. set DoG parameters / hack to use existing pipeline function
dogparams = {
'apix': 1.0, # set to 1 because we are using pixels
'bin': 1.0, # set to 1 because we are using pixels
'diam': pixdiam, # diameter of particles
'sizerange': sizerange, # diameter range of particles
'numslices': numslices, # number of slices to perform
'kfactor': 1.2, # does not matter
'overlapmult': 1.5,
'rundir': os.getcwd(),
'maxpeaks': maxpeaks,
'maxthresh': maxthresh,
'thresh': minthresh,
'maxsize': peakarea,
'peaktype': 'maximum',
'background': False,
'doubles': False,
}
#2a. get image 1
img1 = numpy.asarray(self.parent.panel1.imagedata, dtype=numpy.float32)
if invert is True:
img1 = apImage.invertImage(img1)
#3a. run DoG picker on image 1
dogarrays1 = apDog.diffOfGaussParam(img1, dogparams)
#4a: threshold & find peaks image 1
imgdict1 = { 'filename': 'leftimage', 'image': img1, }
peaktree1 = apPeaks.findPeaks(imgdict1, dogarrays1, dogparams, maptype="dogmap", pikfile=False)
#5a: insert into self.parent.picks1
self.parent.picks1 = self.peaktreeToPicks(peaktree1)
#===
#2b: get image 2
img2 = numpy.asarray(self.parent.panel2.imagedata, dtype=numpy.float32)
if invert is True:
img2 = apImage.invertImage(img2)
#3b. run DoG picker on image 2
dogarrays2 = apDog.diffOfGaussParam(img2, dogparams)
#4b: threshold & find peaks image 2
imgdict2 = { 'filename': 'rightimage', 'image': img2, }
peaktree2 = apPeaks.findPeaks(imgdict2, dogarrays2, dogparams, maptype="dogmap", pikfile=False)
#5b: insert into self.parent.picks2
self.parent.picks2 = self.peaktreeToPicks(peaktree2)
self.parent.onImportPicks(None, pixdiam, showmaps=True)
apDisplay.printColor("Finished DoGPicker\n===================","cyan")
def onRunDogPicker(self, evt):
apDisplay.printColor("===============\nRunning experimental DoGPicker",
"cyan")
### remove existing maps
lefts = glob.glob("maps/leftimage.dogmap*.jpg")
for imgname in lefts:
apFile.removeFile(imgname, warn=False)
rights = glob.glob("maps/rightimage.dogmap*.jpg")
for imgname in rights:
apFile.removeFile(imgname, warn=False)
pixdiam = self.diam.GetValue()
sizerange = self.srange.GetValue()
minthresh = self.minthresh.GetValue()
maxthresh = self.maxthresh.GetValue()
peakarea = self.peakarea.GetValue()
invert = self.partContrast(None)
maxpeaks = self.maxpeaks.GetValue()
numslices = self.numslices.GetValue()
if invert is True:
apDisplay.printMsg(
"Picking dark particles on light backgound, i.e. ice")
else:
apDisplay.printMsg(
"Picking light particles on dark backgound, i.e. stain")
self.Close()
apParam.createDirectory("maps")
#1. set DoG parameters / hack to use existing pipeline function
dogparams = {
'apix': 1.0, # set to 1 because we are using pixels
'bin': 1.0, # set to 1 because we are using pixels
'diam': pixdiam, # diameter of particles
'sizerange': sizerange, # diameter range of particles
'numslices': numslices, # number of slices to perform
'kfactor': 1.2, # does not matter
'overlapmult': 1.5,
'rundir': os.getcwd(),
'maxpeaks': maxpeaks,
'maxthresh': maxthresh,
'thresh': minthresh,
'maxsize': peakarea,
'peaktype': 'maximum',
'background': False,
'doubles': False,
}
#2a. get image 1
img1 = numpy.asarray(self.parent.panel1.imagedata, dtype=numpy.float32)
if invert is True:
img1 = apImage.invertImage(img1)
#3a. run DoG picker on image 1
dogarrays1 = apDog.diffOfGaussParam(img1, dogparams)
#4a: threshold & find peaks image 1
imgdict1 = {
'filename': 'leftimage',
'image': img1,
}
peaktree1 = apPeaks.findPeaks(imgdict1,
dogarrays1,
dogparams,
maptype="dogmap",
pikfile=False)
#5a: insert into self.parent.picks1
self.parent.picks1 = self.peaktreeToPicks(peaktree1)
#===
#2b: get image 2
img2 = numpy.asarray(self.parent.panel2.imagedata, dtype=numpy.float32)
if invert is True:
img2 = apImage.invertImage(img2)
#3b. run DoG picker on image 2
dogarrays2 = apDog.diffOfGaussParam(img2, dogparams)
#4b: threshold & find peaks image 2
imgdict2 = {
'filename': 'rightimage',
'image': img2,
}
peaktree2 = apPeaks.findPeaks(imgdict2,
dogarrays2,
dogparams,
maptype="dogmap",
pikfile=False)
#5b: insert into self.parent.picks2
self.parent.picks2 = self.peaktreeToPicks(peaktree2)
self.parent.onImportPicks(None, pixdiam, showmaps=True)
apDisplay.printColor("Finished DoGPicker\n===================", "cyan")
def findPeaks(self,imgdata,ccmaplist):
return apPeaks.findPeaks(imgdata, ccmaplist, self.params)