_DUMP_CrackDetection.py 文件源码

def _process(self):
        d = self.display
        img = d.widget.image
        out = np.empty(shape=img.shape[:3], dtype=bool)
        width = self.pWidth.value()
        debug = self.pDebug.value()
        laps, linelikellyness, params = [], [], []
        ki = self.pKSizeIntensity.value()
        ki += 1 - ki % 2  # enusre odd number

        t = d.tools['Selection']
        path = t.findPath(PerspectiveGridROI)
        shape = path.nCells if path is not None else (6, 10)
        border = path.vertices() if path is not None else None
        if border is None:
            print('No [Grid] found, assume image is corrected and there is \
no border around the image')

        v = self.pMask.value()
        if v != '-':
            grid = d.widget.cItems[v].image_full
        else:
            grid = None
            print('Please define [Grid Mask] to improve precision')

        for n, im in enumerate(img):

            if self.pDetect.value():
                kwargs = detectLabelCrackParams(img, shape)
                self.pKSizeProp.setValue(kwargs['ksize_length'])
                self.pThreshProp.setValue(kwargs['thresh_length'] * 100)
                self.pKSizeIntensity.setValue(kwargs['ksize_intensity'])
                self.pThreshIntensity.setValue(kwargs['thresh_intensity'])
            else:
                kwargs = dict(ksize_intensity=ki,
                              ksize_length=self.pKSizeProp.value(),
                              thresh_length=self.pThreshProp.value() / 100,
                              norientations=self.pNorient.value(),
                              thresh_intensity=self.pThreshIntensity.value())

            cracks, h, orient, lap,  mx = labelCracks(im, grid,
                                                      cracks_are_bright=not self.pDark.value(),
                                                      **kwargs)
            params.append(evalCracks(cracks, h, orient, shape, border))
            if width > 1:
                cracks = maximum_filter(cracks, width)
            out[n] = cracks

            if debug:
                laps.append(lap)
                linelikellyness.append(mx)

        return out, laps, linelikellyness, params