vignettingFromDifferentObjects.py 文件源码

def addImg(self, i):
        img = self._read(i)

        if self._first:
            img = self._firstImg(img)
        elif self.scale_factor != 1:
            img = rescale(img, self.scale_factor)
        try:
            f = FitHistogramPeaks(img)
        except AssertionError:
            return
        #sp = getSignalPeak(f.fitParams)
        mn = getSignalMinimum(f.fitParams)
        # non-backround indices:
        ind = img > mn  # sp[1] - self.nstd * sp[2]
        # blur:
        # blurred = minimum_filter(img, 3)#remove artefacts
        #blurred = maximum_filter(blurred, self.ksize)
#         blurred = img
#         gblurred = gaussian_filter(img, self.ksize)
#         ind = minimum_filter(ind, self.ksize)
        nind = np.logical_not(ind)
        gblurred = maskedFilter(img, nind, ksize=2 * self.ksize,
                                fill_mask=False,
                                fn="mean")

        #blurred[ind] = gblurred[ind]
        # scale [0-1]:
        mn = img[nind].mean()
        if np.isnan(mn):
            mn = 0
        mx = gblurred[ind].max()
        gblurred -= mn
        gblurred /= (mx - mn)
#         img -= mn
#         img /= (mx - mn)
#         ind = np.logical_and(ind, img > self._m.avg)

        self._m.update(gblurred, ind)
        self.bglevel.append(mn)
        self._mx += mx

        self._n += 1

#         import pylab as plt
#         plt.imshow(self._m.avg)
#         plt.show()