Пример #1
0
    def __init__(self, data, voxel, threshold = -1, interactivity = True, number = 100.0, inputSigma = -1,
                 nObj = 10,  biggestObjects = True, binaryClosingIterations = 2, binaryOpeningIterations = 0,
                 seeds = None, cmap = matplotlib.cm.Greys_r):

        """

        Inicialitacni metoda.
        Input:
            data - data pro prahovani, se kterymi se pracuje
            voxel - velikost voxelu
            threshold
            interactivity - zapnuti / vypnuti gui
            number - maximalni hodnota slideru pro gauss. filtrovani (max sigma)
            inputSigma - pocatecni hodnota pro gauss. filtr
            nObj - pocet nejvetsich objektu k vraceni
            biggestObjects - oznacuje, zda se maji vracet nejvetsi objekty
            binaryClosingIterations - iterace binary closing
            binaryOpeningIterations - iterace binary opening
            seeds - matice s kliknutim uzivatele- pokud se maji vracet specifikce objekty
            cmap - grey

        """

        logger.debug('Spoustim prahovani dat...')

        self.inputDimension = numpy.ndim(data)
        if(self.inputDimension != 3):

            logger.debug('Vstup nema 3 dimenze! Ma jich ' + str(self.inputDimension) + '.')
            self.errorsOccured = True
            return

        else:

            self.errorsOccured = False

        self.interactivity = interactivity
        self.cmap = cmap
        self.number = number
        self.inputSigma = inputSigma
        self.threshold = threshold
        self.nObj = nObj
        self.biggestObjects = biggestObjects
        self.ICBinaryClosingIterations = binaryClosingIterations
        self.ICBinaryOpeningIterations = binaryOpeningIterations
        self.seeds = seeds

        if (sys.version_info[0] < 3):

            import copy
            self.data = copy.copy(data)
            self.voxel = copy.copy(voxel)

        else:

            self.data = data.copy()
            self.voxel = voxel.copy()

        ## Kalkulace objemove jednotky (voxel) (V = a*b*c)
        voxel1 = self.voxel[0]
        voxel2 = self.voxel[1]
        voxel3 = self.voxel[2]
        self.voxelV = voxel1 * voxel2 * voxel3

        self.numpyAMaxKeepDims = False

        self.arrSeed = None

        if self.interactivity == True:

            self.fig = matpyplot.figure()

            ## Maximalni a minimalni pouzita hodnota prahovani v datech (bud v
            ## celych datech nebo vybranych seedu)
            self.min0 = numpy.amin(numpy.amin(self.data, axis = 0))
            if self.seeds == None:

                self.max0 = numpy.amax(numpy.amax(self.data, axis = 0))
                self.max0 = self.max0 + abs(abs(self.min0) - abs(self.max0)) / 10

            else:

                self.arrSeed = thresholding_functions.getSeeds(data, self.seeds)

                ## Pokud existuji vhodne labely, vytvori se nova data k
                ## vraceni.
                ## Pokud ne, vrati se "None" typ.  { Deprecated: Pokud ne,
                ## vrati se cela nafiltrovana data, ktera do funkce prisla
                ## (nedojde k vraceni specifickych objektu).  }
                if len(self.arrSeed) > 0:

                    ## Zbaveni se duplikatu.
                    self.arrSeed = list(set(self.arrSeed))
                    logger.debug( 'Hodnoty seedu: ')
                    logger.debug( self.arrSeed)

                    self.max0 = max(self.arrSeed)
                    self.max0 = self.max0 + abs(abs(self.min0) - abs(self.max0)) / 10

                    # Prahy
                    logger.debug( '')
                    logger.debug( 'Minimalni doporucena hodnota prahu: ' + str(min(self.arrSeed)))
                    logger.debug( 'Maximalni doporucena hodnota prahu: ' + str(max(self.arrSeed)))
                    logger.debug( '')

                else:

                    self.max0 = numpy.amax(numpy.amax(self.data, axis = 0))
                    self.max0 = self.max0 + abs(abs(self.min0) - abs(self.max0)) / 10

            ## Pridani subplotu do okna (do figure)
            self.ax1 = self.fig.add_subplot(131)
            self.ax2 = self.fig.add_subplot(132)
            self.ax3 = self.fig.add_subplot(133)

            ## Upraveni subplotu
            self.fig.subplots_adjust(left = 0.1, bottom = 0.3)

            ## Vykreslit obrazek
            self.ax1.imshow(numpy.amax(self.data, axis = 0, keepdims = self.numpyAMaxKeepDims), self.cmap)
            self.ax2.imshow(numpy.amax(self.data, axis = 1, keepdims = self.numpyAMaxKeepDims), self.cmap)
            self.ax3.imshow(numpy.amax(self.data, axis = 2, keepdims = self.numpyAMaxKeepDims), self.cmap)

            ## Zalozeni mist pro slidery
            self.axcolor = 'white' # lightgoldenrodyellow
            self.axmin = self.fig.add_axes([0.20, 0.24, 0.55, 0.03], axisbg = self.axcolor)
            self.axmax = self.fig.add_axes([0.20, 0.20, 0.55, 0.03], axisbg = self.axcolor)
            self.axclosing = self.fig.add_axes([0.20, 0.16, 0.55, 0.03], axisbg = self.axcolor)
            self.axopening = self.fig.add_axes([0.20, 0.12, 0.55, 0.03], axisbg = self.axcolor)
            self.axsigma = self.fig.add_axes([0.20, 0.08, 0.55, 0.03], axisbg = self.axcolor)

            ## Vlastni vytvoreni slideru

            minBinaryClosing = 0
            minBinaryOpening = 0
            minSigma = 0.00

            self.firstRun = True

            thres = self.threshold
            if thres == -1:
                thres = thresholding_functions.calculateAutomaticThreshold(self.data, self.arrSeed)

            self.smin = Slider(self.axmin, 'Minimal threshold   ' + str(self.min0),
                               self.min0, self.max0, valinit = thres, dragging = True)
            self.smax = Slider(self.axmax, 'Maximal threshold   ' + str(self.min0),
                               self.min0, self.max0, valinit = self.max0, dragging = True)

            if(self.ICBinaryClosingIterations >= 1):
                self.sclose = Slider(self.axclosing, 'Binary closing', minBinaryClosing, 100, valinit = self.ICBinaryClosingIterations, dragging = False)
            else:
                self.sclose = Slider(self.axclosing, 'Binary closing', minBinaryClosing, 100, valinit = 0, dragging = False)

            if(self.ICBinaryOpeningIterations >= 1):
                self.sopen = Slider(self.axopening, 'Binary opening',minBinaryOpening, 100, valinit = self.ICBinaryOpeningIterations, dragging = False)
            else:
                self.sopen = Slider(self.axopening, 'Binary opening', minBinaryOpening, 100, valinit = 0, dragging = False)

            self.ssigma = Slider(self.axsigma, 'Sigma', 0.00, self.number, valinit = self.inputSigma, dragging = False)

            ## Funkce slideru pri zmene jeho hodnoty
            self.smin.on_changed(self.updateImage)
            self.smax.on_changed(self.updateImage)
            self.sclose.on_changed(self.updateImage)
            self.sopen.on_changed(self.updateImage)
            self.ssigma.on_changed(self.updateImage)

            ## Zalozeni mist pro tlacitka
            self.axbuttnext1 = self.fig.add_axes([0.86, 0.24, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttprev1 = self.fig.add_axes([0.81, 0.24, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttnext2 = self.fig.add_axes([0.86, 0.20, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttprev2 = self.fig.add_axes([0.81, 0.20, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttnextclosing = self.fig.add_axes([0.86, 0.16, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttprevclosing = self.fig.add_axes([0.81, 0.16, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttnextopening = self.fig.add_axes([0.86, 0.12, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttprevopening = self.fig.add_axes([0.81, 0.12, 0.04, 0.03], axisbg = self.axcolor)
            self.axbuttreset = self.fig.add_axes([0.79, 0.08, 0.06, 0.03], axisbg = self.axcolor)
            self.axbuttcontinue = self.fig.add_axes([0.86, 0.08, 0.06, 0.03], axisbg = self.axcolor)

            ## Zalozeni tlacitek
            self.bnext1 = Button(self.axbuttnext1, '+1.0')
            self.bprev1 = Button(self.axbuttprev1, '-1.0')
            self.bnext2 = Button(self.axbuttnext2, '+1.0')
            self.bprev2 = Button(self.axbuttprev2, '-1.0')
            self.bnextclosing = Button(self.axbuttnextclosing, '+1.0')
            self.bprevclosing = Button(self.axbuttprevclosing, '-1.0')
            self.bnextopening = Button(self.axbuttnextopening, '+1.0')
            self.bprevopening = Button(self.axbuttprevopening, '-1.0')
            self.breset = Button(self.axbuttreset, 'Reset')
            self.bcontinue = Button(self.axbuttcontinue, 'Next UI')

            ## Funkce tlacitek pri jejich aktivaci
            self.bnext1.on_clicked(self.buttonMinNext)
            self.bprev1.on_clicked(self.buttonMinPrev)
            self.bnext2.on_clicked(self.buttonMaxNext)
            self.bprev2.on_clicked(self.buttonMaxPrev)
            self.bnextclosing.on_clicked(self.buttonNextClosing)
            self.bprevclosing.on_clicked(self.buttonPrevClosing)
            self.bnextopening.on_clicked(self.buttonNextOpening)
            self.bprevopening.on_clicked(self.buttonPrevOpening)
            self.breset.on_clicked(self.buttonReset)
            self.bcontinue.on_clicked(self.buttonContinue)

            self.smin.valtext.set_text('{}'.format(self.smin.val))
            self.smax.valtext.set_text('{}'.format(self.smax.val))
Пример #2
0
    def updateImage(self, val):

        """

        Hlavni update metoda.
        Cinny kod pro gaussovske filtrovani, prahovani, binarni uzavreni a otevreni a vraceni nejvetsich nebo oznacenych objektu.

        """

        if (sys.version_info[0] < 3):

            import copy
            self.imgFiltering = copy.copy(self.data)

        else:

            self.imgFiltering = self.data.copy()

        ## Filtrovani

        ## Zjisteni jakou sigmu pouzit
        if(self.firstRun == True and self.inputSigma >= 0):
            sigma = numpy.round(self.inputSigma, 2)
        else:
            sigma = numpy.round(self.ssigma.val, 2)
        sigmaNew = thresholding_functions.calculateSigma(self.voxel, sigma)

        self.imgFiltering = thresholding_functions.gaussFilter(self.imgFiltering, sigmaNew)

        del(sigmaNew)

        ## Prahovani (smin, smax)

        max_threshold = -1
        min_threshold = self.threshold

        if self.interactivity:

            self.smin.val = (numpy.round(self.smin.val, 2))
            self.smin.valtext.set_text('{}'.format(self.smin.val))
            self.smax.val = (numpy.round(self.smax.val, 2))
            self.smax.valtext.set_text('{}'.format(self.smax.val))

            min_threshold = self.smin.val
            max_threshold = self.smax.val

            self.threshold = min_threshold

        if (self.threshold == -1) and self.firstRun:

            min_threshold = thresholding_functions.calculateAutomaticThreshold(self.imgFiltering, self.arrSeed)

        self.imgFiltering = thresholding_functions.thresholding(self.imgFiltering, min_threshold, max_threshold, True, self.interactivity)

        ## Operace binarni otevreni a uzavreni.
        
        ## Nastaveni hodnot slideru.
        if (self.interactivity == True) :

            closeNum = int(numpy.round(self.sclose.val, 0))
            openNum = int(numpy.round(self.sopen.val, 0))
            self.sclose.valtext.set_text('{}'.format(closeNum))
            self.sopen.valtext.set_text('{}'.format(openNum))

        else:

            closeNum = self.ICBinaryClosingIterations
            openNum = self.ICBinaryOpeningIterations

        self.imgFiltering = thresholding_functions.binaryClosingOpening(self.imgFiltering, closeNum, openNum, True)

        ## Zjisteni nejvetsich objektu.
        self.getBiggestObjects()

        ## Vykresleni dat
        if (self.interactivity == True):
            self.drawVisualization()

        ## Nastaveni kontrolnich hodnot
        self.firstRun = False

        garbage.collect()

        self.debugInfo()