diff --git a/libs/image/kis_convolution_painter.cc b/libs/image/kis_convolution_painter.cc
index 01349625df..384f59f55f 100644
--- a/libs/image/kis_convolution_painter.cc
+++ b/libs/image/kis_convolution_painter.cc
@@ -1,188 +1,189 @@
 /*
  *  Copyright (c) 2005 Cyrille Berger <cberger@cberger.net>
  *
  *  This program is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU General Public License as published by
  *  the Free Software Foundation; either version 2 of the License, or
  *  (at your option) any later version.
  *
  *  This program is distributed in the hope that it will be useful,
  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  *  GNU General Public License for more details.
  *
  *  You should have received a copy of the GNU General Public License
  *  along with this program; if not, write to the Free Software
  *  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  */
 
 #include "kis_convolution_painter.h"
 
 #include <stdlib.h>
 #include <string.h>
 #include <cfloat>
 
 #include <QBrush>
 #include <QColor>
 #include <QPen>
 #include <QMatrix>
 #include <QImage>
 #include <QMap>
 #include <QPainter>
 #include <QRect>
 #include <QString>
 #include <QVector>
 
 #include <kis_debug.h>
 #include <klocalizedstring.h>
 
 #include "kis_convolution_kernel.h"
 #include "kis_global.h"
 #include "kis_image.h"
 #include "kis_layer.h"
 #include "kis_paint_device.h"
 #include "kis_painter.h"
 #include "KoColorSpace.h"
 #include <KoChannelInfo.h>
 #include "kis_types.h"
 
 #include "kis_selection.h"
 
 #include "kis_convolution_worker.h"
 #include "kis_convolution_worker_spatial.h"
 
 #include "config_convolution.h"
 
 #ifdef HAVE_FFTW3
 #include "kis_convolution_worker_fft.h"
 #endif
 
 
 bool KisConvolutionPainter::useFFTImplementation(const KisConvolutionKernelSP kernel) const
 {
     bool result = false;
 
 #ifdef HAVE_FFTW3
     #define THRESHOLD_SIZE 5
 
     result =
         m_enginePreference == FFTW ||
         (m_enginePreference == NONE &&
          (kernel->width() > THRESHOLD_SIZE ||
           kernel->height() > THRESHOLD_SIZE));
 #else
     Q_UNUSED(kernel);
 #endif
 
     return result;
 }
 
 template<class factory>
 KisConvolutionWorker<factory>* KisConvolutionPainter::createWorker(const KisConvolutionKernelSP kernel,
                                                                    KisPainter *painter,
                                                                    KoUpdater *progress)
 {
     KisConvolutionWorker<factory> *worker;
 
 #ifdef HAVE_FFTW3
     if (useFFTImplementation(kernel)) {
         worker = new KisConvolutionWorkerFFT<factory>(painter, progress);
     } else {
         worker = new KisConvolutionWorkerSpatial<factory>(painter, progress);
     }
 #else
     Q_UNUSED(kernel);
     worker = new KisConvolutionWorkerSpatial<factory>(painter, progress);
 #endif
 
     return worker;
 }
 
 
 bool KisConvolutionPainter::supportsFFTW()
 {
 #ifdef HAVE_FFTW3
     return true;
 #else
     return false;
 #endif
 }
 
 
 KisConvolutionPainter::KisConvolutionPainter()
     : KisPainter(),
       m_enginePreference(NONE)
 {
 }
 
 KisConvolutionPainter::KisConvolutionPainter(KisPaintDeviceSP device)
     : KisPainter(device),
       m_enginePreference(NONE)
 {
 }
 
 KisConvolutionPainter::KisConvolutionPainter(KisPaintDeviceSP device, KisSelectionSP selection)
     : KisPainter(device, selection),
       m_enginePreference(NONE)
 {
 }
 
 KisConvolutionPainter::KisConvolutionPainter(KisPaintDeviceSP device, TestingEnginePreference enginePreference)
     : KisPainter(device),
       m_enginePreference(enginePreference)
 {
 }
 
 void KisConvolutionPainter::applyMatrix(const KisConvolutionKernelSP kernel, const KisPaintDeviceSP src, QPoint srcPos, QPoint dstPos, QSize areaSize, KisConvolutionBorderOp borderOp)
 {
     /**
      * Force BORDER_IGNORE op for the wraparound mode,
      * because the paint device has its own special
      * iterators, which do everything for us.
      */
     if (src->defaultBounds()->wrapAroundMode()) {
         borderOp = BORDER_IGNORE;
     }
 
     // Determine whether we convolve border pixels, or not.
     switch (borderOp) {
     case BORDER_REPEAT: {
         const QRect boundsRect = src->defaultBounds()->bounds();
         const QRect requestedRect = QRect(srcPos, areaSize);
         QRect dataRect = requestedRect | boundsRect;
+
         KIS_SAFE_ASSERT_RECOVER(boundsRect != KisDefaultBounds().bounds()) {
             dataRect = requestedRect | src->exactBounds();
         }
 
         /**
          * FIXME: Implementation can return empty destination device
          * on faults and has no way to report this. This will cause a crash
          * on sequential convolutions inside iteratiors.
          *
          * o implementation should do it's work or assert otherwise
          *   (or report the issue somehow)
          * o check other cases of the switch for the vulnerability
          */
 
         if(dataRect.isValid()) {
             KisConvolutionWorker<RepeatIteratorFactory> *worker;
             worker = createWorker<RepeatIteratorFactory>(kernel, this, progressUpdater());
             worker->execute(kernel, src, srcPos, dstPos, areaSize, dataRect);
             delete worker;
         }
         break;
     }
     case BORDER_IGNORE:
     default: {
         KisConvolutionWorker<StandardIteratorFactory> *worker;
         worker = createWorker<StandardIteratorFactory>(kernel, this, progressUpdater());
         worker->execute(kernel, src, srcPos, dstPos, areaSize, QRect());
         delete worker;
     }
     }
 }
 
 bool KisConvolutionPainter::needsTransaction(const KisConvolutionKernelSP kernel) const
 {
     return !useFFTImplementation(kernel);
 }
diff --git a/libs/image/kis_edge_detection_kernel.cpp b/libs/image/kis_edge_detection_kernel.cpp
index a15a6b9fb8..7872414e08 100644
--- a/libs/image/kis_edge_detection_kernel.cpp
+++ b/libs/image/kis_edge_detection_kernel.cpp
@@ -1,659 +1,651 @@
 /*
  *  Copyright (c) 2017 Wolthera van Hövell tot Westerflier <griffinvalley@gmail.com>
  *
  *  This program is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU General Public License as published by
  *  the Free Software Foundation; either version 2 of the License, or
  *  (at your option) any later version.
  *
  *  This program is distributed in the hope that it will be useful,
  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  *  GNU General Public License for more details.
  *
  *  You should have received a copy of the GNU General Public License
  *  along with this program; if not, write to the Free Software
  *  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  */
 
 #include "kis_edge_detection_kernel.h"
-#include "kis_convolution_kernel.h"
 #include "kis_global.h"
-#include <KoColorSpace.h>
+#include "kis_convolution_kernel.h"
+#include <kis_convolution_painter.h>
 #include <KoCompositeOpRegistry.h>
 #include <QRect>
-#include <QVector3D>
-#include <kis_convolution_painter.h>
+#include <KoColorSpace.h>
 #include <kis_iterator_ng.h>
+#include <QVector3D>
 #include <kis_random_accessor_ng.h>
 
-KisEdgeDetectionKernel::KisEdgeDetectionKernel() {}
+KisEdgeDetectionKernel::KisEdgeDetectionKernel()
+{
+
+}
 /*
  * This code is very similar to the gaussian kernel code, except unlike the gaussian code,
  * edge-detection kernels DO use the diagonals.
  * Except for the simple mode. We implement the simple mode because it is an analog to
  * the old sobel filter.
  */
 
 Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> KisEdgeDetectionKernel::createHorizontalMatrix(qreal radius,
                                                                                                     FilterType type,
                                                                                                     bool reverse)
 {
     int kernelSize = kernelSizeFromRadius(radius);
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix(kernelSize, kernelSize);
 
     KIS_ASSERT_RECOVER_NOOP(kernelSize & 0x1);
     const int center = kernelSize / 2;
 
-    if (type == Prewit) {
+    if (type==Prewit) {
         for (int x = 0; x < kernelSize; x++) {
-            for (int y = 0; y < kernelSize; y++) {
+            for (int y=0; y<kernelSize; y++) {
                 qreal xDistance;
                 if (reverse) {
                     xDistance = x - center;
                 } else {
                     xDistance = center - x;
                 }
                 matrix(x, y) = xDistance;
             }
         }
-    } else if (type == Simple) {
+    } else if(type==Simple) {
         matrix.resize(kernelSize, 1);
         for (int x = 0; x < kernelSize; x++) {
             qreal xDistance;
             if (reverse) {
                 xDistance = x - center;
             } else {
                 xDistance = center - x;
             }
-            if (x == center) {
+            if (x==center) {
                 matrix(x, 0) = 0;
             } else {
-                matrix(x, 0) = (1 / xDistance);
+                matrix(x, 0) = (1/xDistance);
             }
         }
     } else {
         for (int x = 0; x < kernelSize; x++) {
-            for (int y = 0; y < kernelSize; y++) {
-                if (x == center && y == center) {
+            for (int y=0; y<kernelSize; y++) {
+                if (x==center && y==center) {
                     matrix(x, y) = 0;
                 } else {
                     qreal xD, yD;
                     if (reverse) {
                         xD = x - center;
                         yD = y - center;
                     } else {
                         xD = center - x;
                         yD = center - y;
                     }
-                    matrix(x, y) = xD / (xD * xD + yD * yD);
+                    matrix(x, y) = xD / (xD*xD + yD*yD);
                 }
             }
         }
     }
     return matrix;
 }
 
 Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> KisEdgeDetectionKernel::createVerticalMatrix(qreal radius,
                                                                                                   FilterType type,
                                                                                                   bool reverse)
 {
     int kernelSize = kernelSizeFromRadius(radius);
 
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix(kernelSize, kernelSize);
     KIS_ASSERT_RECOVER_NOOP(kernelSize & 0x1);
     const int center = kernelSize / 2;
 
-    if (type == Prewit) {
+    if (type==Prewit) {
         for (int y = 0; y < kernelSize; y++) {
-            for (int x = 0; x < kernelSize; x++) {
+            for (int x=0; x<kernelSize; x++) {
                 qreal yDistance;
                 if (reverse) {
                     yDistance = y - center;
                 } else {
                     yDistance = center - y;
                 }
                 matrix(x, y) = yDistance;
             }
         }
-    } else if (type == Simple) {
+    } else if(type==Simple) {
         matrix.resize(1, kernelSize);
         for (int y = 0; y < kernelSize; y++) {
             qreal yDistance;
             if (reverse) {
                 yDistance = y - center;
             } else {
                 yDistance = center - y;
             }
-            if (y == center) {
+            if (y==center) {
                 matrix(0, y) = 0;
             } else {
-                matrix(0, y) = (1 / yDistance);
+                matrix(0, y) = (1/yDistance);
             }
         }
     } else {
         for (int y = 0; y < kernelSize; y++) {
-            for (int x = 0; x < kernelSize; x++) {
-                if (x == center && y == center) {
+            for (int x=0; x<kernelSize; x++) {
+                if (x==center && y==center) {
                     matrix(x, y) = 0;
                 } else {
                     qreal xD, yD;
                     if (reverse) {
                         xD = x - center;
                         yD = y - center;
                     } else {
                         xD = center - x;
                         yD = center - y;
                     }
-                    matrix(x, y) = yD / (xD * xD + yD * yD);
+                    matrix(x, y) = yD / (xD*xD + yD*yD);
                 }
             }
         }
     }
     return matrix;
 }
 
 KisConvolutionKernelSP KisEdgeDetectionKernel::createHorizontalKernel(qreal radius,
                                                                       KisEdgeDetectionKernel::FilterType type,
                                                                       bool denormalize,
                                                                       bool reverse)
 {
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix = createHorizontalMatrix(radius, type, reverse);
     if (denormalize) {
         return KisConvolutionKernel::fromMatrix(matrix, 0.5, 1);
     } else {
         return KisConvolutionKernel::fromMatrix(matrix, 0, matrix.sum());
     }
 }
 
 KisConvolutionKernelSP KisEdgeDetectionKernel::createVerticalKernel(qreal radius,
                                                                     KisEdgeDetectionKernel::FilterType type,
                                                                     bool denormalize,
                                                                     bool reverse)
 {
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix = createVerticalMatrix(radius, type, reverse);
     if (denormalize) {
         return KisConvolutionKernel::fromMatrix(matrix, 0.5, 1);
     } else {
         return KisConvolutionKernel::fromMatrix(matrix, 0, matrix.sum());
     }
 }
 
 int KisEdgeDetectionKernel::kernelSizeFromRadius(qreal radius)
 {
     return qMax((int)(2 * ceil(sigmaFromRadius(radius)) + 1), 3);
 }
 
 qreal KisEdgeDetectionKernel::sigmaFromRadius(qreal radius)
 {
     return 0.3 * radius + 0.3;
 }
 
 void KisEdgeDetectionKernel::applyEdgeDetection(KisPaintDeviceSP device,
-                                                const QRect& rect,
+                                                const QRect &rect,
                                                 qreal xRadius,
                                                 qreal yRadius,
                                                 KisEdgeDetectionKernel::FilterType type,
-                                                const QBitArray& channelFlags,
-                                                KoUpdater* progressUpdater,
+                                                const QBitArray &channelFlags,
+                                                KoUpdater *progressUpdater,
                                                 FilterOutput output,
                                                 bool writeToAlpha)
 {
     QPoint srcTopLeft = rect.topLeft();
     KisPainter finalPainter(device);
     finalPainter.setChannelFlags(channelFlags);
     finalPainter.setProgress(progressUpdater);
     if (output == pythagorean || output == radian) {
         KisPaintDeviceSP x_denormalised = new KisPaintDevice(device->colorSpace());
         KisPaintDeviceSP y_denormalised = new KisPaintDevice(device->colorSpace());
 
         x_denormalised->prepareClone(device);
         y_denormalised->prepareClone(device);
 
+
         KisConvolutionKernelSP kernelHorizLeftRight = KisEdgeDetectionKernel::createHorizontalKernel(xRadius, type);
         KisConvolutionKernelSP kernelVerticalTopBottom = KisEdgeDetectionKernel::createVerticalKernel(yRadius, type);
 
         qreal horizontalCenter = qreal(kernelHorizLeftRight->width()) / 2.0;
         qreal verticalCenter = qreal(kernelVerticalTopBottom->height()) / 2.0;
 
         KisConvolutionPainter horizPainterLR(x_denormalised);
         horizPainterLR.setChannelFlags(channelFlags);
         horizPainterLR.setProgress(progressUpdater);
-        horizPainterLR.applyMatrix(kernelHorizLeftRight,
-                                   device,
+        horizPainterLR.applyMatrix(kernelHorizLeftRight, device,
                                    srcTopLeft - QPoint(0, ceil(horizontalCenter)),
                                    srcTopLeft - QPoint(0, ceil(horizontalCenter)),
-                                   rect.size() + QSize(0, 2 * ceil(horizontalCenter)),
-                                   BORDER_REPEAT);
+                                   rect.size() + QSize(0, 2 * ceil(horizontalCenter)), BORDER_REPEAT);
+
 
         KisConvolutionPainter verticalPainterTB(y_denormalised);
         verticalPainterTB.setChannelFlags(channelFlags);
         verticalPainterTB.setProgress(progressUpdater);
-        verticalPainterTB.applyMatrix(kernelVerticalTopBottom,
-                                      device,
+        verticalPainterTB.applyMatrix(kernelVerticalTopBottom, device,
                                       srcTopLeft - QPoint(0, ceil(verticalCenter)),
                                       srcTopLeft - QPoint(0, ceil(verticalCenter)),
-                                      rect.size() + QSize(0, 2 * ceil(verticalCenter)),
-                                      BORDER_REPEAT);
+                                      rect.size() + QSize(0, 2 * ceil(verticalCenter)), BORDER_REPEAT);
 
         KisSequentialIterator yItterator(y_denormalised, rect);
         KisSequentialIterator xItterator(x_denormalised, rect);
         KisSequentialIterator finalIt(device, rect);
         const int pixelSize = device->colorSpace()->pixelSize();
         const int channels = device->colorSpace()->channelCount();
         const int alphaPos = device->colorSpace()->alphaPos();
         KIS_SAFE_ASSERT_RECOVER_RETURN(alphaPos >= 0);
 
         QVector<float> yNormalised(channels);
         QVector<float> xNormalised(channels);
         QVector<float> finalNorm(channels);
 
-        while (yItterator.nextPixel() && xItterator.nextPixel() && finalIt.nextPixel()) {
+        while(yItterator.nextPixel() && xItterator.nextPixel() && finalIt.nextPixel()) {
             device->colorSpace()->normalisedChannelsValue(yItterator.rawData(), yNormalised);
             device->colorSpace()->normalisedChannelsValue(xItterator.rawData(), xNormalised);
             device->colorSpace()->normalisedChannelsValue(finalIt.rawData(), finalNorm);
 
             if (output == pythagorean) {
-                for (int c = 0; c < channels; c++) {
-                    finalNorm[c] = 2 * sqrt(((xNormalised[c] - 0.5) * (xNormalised[c] - 0.5)) +
-                                            ((yNormalised[c] - 0.5) * (yNormalised[c] - 0.5)));
+                for (int c = 0; c<channels; c++) {
+                    finalNorm[c] = 2 * sqrt( ((xNormalised[c]-0.5)*(xNormalised[c]-0.5)) + ((yNormalised[c]-0.5)*(yNormalised[c]-0.5)));
                 }
-            } else { // radian
-                for (int c = 0; c < channels; c++) {
-                    finalNorm[c] = atan2(xNormalised[c] - 0.5, yNormalised[c] - 0.5);
+            } else { //radian
+                for (int c = 0; c<channels; c++) {
+                    finalNorm[c] = atan2(xNormalised[c]-0.5, yNormalised[c]-0.5);
                 }
             }
 
             if (writeToAlpha) {
                 KoColor col(finalIt.rawData(), device->colorSpace());
                 qreal alpha = 0;
 
-                for (int c = 0; c < (channels - 1); c++) {
-                    alpha = alpha + finalNorm[c];
+                for (int c = 0; c<(channels-1); c++) {
+                    alpha = alpha+finalNorm[c];
                 }
 
-                alpha = qMin(alpha / (channels - 1), col.opacityF());
+                alpha = qMin(alpha/(channels-1), col.opacityF());
                 col.setOpacity(alpha);
                 memcpy(finalIt.rawData(), col.data(), pixelSize);
             } else {
                 quint8* f = finalIt.rawData();
                 finalNorm[alphaPos] = 1.0;
                 device->colorSpace()->fromNormalisedChannelsValue(f, finalNorm);
                 memcpy(finalIt.rawData(), f, pixelSize);
             }
+
         }
     } else {
         KisConvolutionKernelSP kernel;
         qreal center = 0;
         bool denormalize = !writeToAlpha;
         if (output == xGrowth) {
             kernel = KisEdgeDetectionKernel::createHorizontalKernel(xRadius, type, denormalize);
             center = qreal(kernel->width()) / 2.0;
         } else if (output == xFall) {
             kernel = KisEdgeDetectionKernel::createHorizontalKernel(xRadius, type, denormalize, true);
             center = qreal(kernel->width()) / 2.0;
         } else if (output == yGrowth) {
             kernel = KisEdgeDetectionKernel::createVerticalKernel(yRadius, type, denormalize);
             center = qreal(kernel->height()) / 2.0;
-        } else { // yFall
+        } else { //yFall
             kernel = KisEdgeDetectionKernel::createVerticalKernel(yRadius, type, denormalize, true);
             center = qreal(kernel->height()) / 2.0;
         }
 
         if (writeToAlpha) {
             KisPaintDeviceSP denormalised = new KisPaintDevice(device->colorSpace());
             denormalised->prepareClone(device);
 
             KisConvolutionPainter kernelP(denormalised);
             kernelP.setChannelFlags(channelFlags);
             kernelP.setProgress(progressUpdater);
-            kernelP.applyMatrix(kernel,
-                                device,
+            kernelP.applyMatrix(kernel, device,
                                 srcTopLeft - QPoint(0, ceil(center)),
                                 srcTopLeft - QPoint(0, ceil(center)),
-                                rect.size() + QSize(0, 2 * ceil(center)),
-                                BORDER_REPEAT);
+                                rect.size() + QSize(0, 2 * ceil(center)), BORDER_REPEAT);
             KisSequentialIterator iterator(denormalised, rect);
             KisSequentialIterator finalIt(device, rect);
             const int pixelSize = device->colorSpace()->pixelSize();
             const int channels = device->colorSpace()->colorChannelCount();
             QVector<float> normalised(channels);
             while (iterator.nextPixel() && finalIt.nextPixel()) {
                 device->colorSpace()->normalisedChannelsValue(iterator.rawData(), normalised);
                 KoColor col(finalIt.rawData(), device->colorSpace());
                 qreal alpha = 0;
-                for (int c = 0; c < channels; c++) {
-                    alpha = alpha + normalised[c];
+                for (int c = 0; c<channels; c++) {
+                    alpha = alpha+normalised[c];
                 }
-                alpha = qMin(alpha / channels, col.opacityF());
+                alpha = qMin(alpha/channels, col.opacityF());
                 col.setOpacity(alpha);
                 memcpy(finalIt.rawData(), col.data(), pixelSize);
+
             }
 
         } else {
             KisConvolutionPainter kernelP(device);
             kernelP.setChannelFlags(channelFlags);
             kernelP.setProgress(progressUpdater);
-            kernelP.applyMatrix(kernel,
-                                device,
+            kernelP.applyMatrix(kernel, device,
                                 srcTopLeft - QPoint(0, ceil(center)),
                                 srcTopLeft - QPoint(0, ceil(center)),
-                                rect.size() + QSize(0, 2 * ceil(center)),
-                                BORDER_REPEAT);
+                                rect.size() + QSize(0, 2 * ceil(center)), BORDER_REPEAT);
 
             KisSequentialIterator finalIt(device, rect);
             int numConseqPixels = finalIt.nConseqPixels();
             while (finalIt.nextPixels(numConseqPixels)) {
                 numConseqPixels = finalIt.nConseqPixels();
                 device->colorSpace()->setOpacity(finalIt.rawData(), 1.0, numConseqPixels);
             }
         }
     }
 }
 
 void KisEdgeDetectionKernel::applyCannyEdgeDetection(KisPaintDeviceSP _device,
                                                      const QRect& rect,
                                                      qreal xRadius,
                                                      qreal yRadius,
                                                      const QBitArray& channelFlags,
                                                      KoUpdater* progressUpdater,
                                                      int thresholdMax,
                                                      int thresholdMin)
 {
     QPoint srcTopLeft = rect.topLeft();
 
     auto bounds = _device->defaultBounds();
     auto device = KisPainter::convertToAlphaAsGray(_device);
     device->setDefaultBounds(bounds);
 
     KisPaintDeviceSP x_denormalised = new KisPaintDevice(device->colorSpace());
     KisPaintDeviceSP y_denormalised = new KisPaintDevice(device->colorSpace());
 
     x_denormalised->prepareClone(device);
     y_denormalised->prepareClone(device);
 
     KisConvolutionKernelSP kernelHorizLeftRight =
         KisEdgeDetectionKernel::createHorizontalKernel(xRadius, KisEdgeDetectionKernel::SobelVector);
     KisConvolutionKernelSP kernelVerticalTopBottom =
         KisEdgeDetectionKernel::createVerticalKernel(yRadius, KisEdgeDetectionKernel::SobelVector);
 
     qreal horizontalCenter = qreal(kernelHorizLeftRight->width()) / 2.0;
     qreal verticalCenter = qreal(kernelVerticalTopBottom->height()) / 2.0;
 
     KisConvolutionPainter horizPainterLR(x_denormalised);
     horizPainterLR.setChannelFlags(channelFlags);
     horizPainterLR.setProgress(progressUpdater);
     horizPainterLR.applyMatrix(kernelHorizLeftRight,
                                device,
                                srcTopLeft - QPoint(0, ceil(horizontalCenter)),
                                srcTopLeft - QPoint(0, ceil(horizontalCenter)),
                                rect.size() + QSize(0, 2 * ceil(horizontalCenter)),
                                BORDER_REPEAT);
 
     KisConvolutionPainter verticalPainterTB(y_denormalised);
     verticalPainterTB.setChannelFlags(channelFlags);
     verticalPainterTB.setProgress(progressUpdater);
     verticalPainterTB.applyMatrix(kernelVerticalTopBottom,
                                   device,
                                   srcTopLeft - QPoint(0, ceil(verticalCenter)),
                                   srcTopLeft - QPoint(0, ceil(verticalCenter)),
                                   rect.size() + QSize(0, 2 * ceil(verticalCenter)),
                                   BORDER_REPEAT);
 
     KisSequentialIterator yIterator(y_denormalised, rect);
     KisSequentialIterator xIterator(x_denormalised, rect);
     KisSequentialIterator sobelIterator(device, rect);
 
     QVector<float> yNormalised(1);
     QVector<float> xNormalised(1);
     QVector<float> finalNorm(1);
 
     while (yIterator.nextPixel() && xIterator.nextPixel() && sobelIterator.nextPixel()) {
         device->colorSpace()->normalisedChannelsValue(yIterator.rawData(), yNormalised);
         device->colorSpace()->normalisedChannelsValue(xIterator.rawData(), xNormalised);
         device->colorSpace()->normalisedChannelsValue(sobelIterator.rawData(), finalNorm);
         finalNorm[0] = 2 * sqrt(((xNormalised[0] - 0.5) * (xNormalised[0] - 0.5)) +
                                 ((yNormalised[0] - 0.5) * (yNormalised[0] - 0.5)));
         quint8* f = sobelIterator.rawData();
         device->colorSpace()->fromNormalisedChannelsValue(f, finalNorm);
         memcpy(sobelIterator.rawData(), f, device->colorSpace()->pixelSize());
     }
 
     KisRandomAccessorSP randomSobel = device->createRandomAccessorNG(rect.x(), rect.y());
     KisRandomConstAccessorSP gx_iter = x_denormalised->createRandomConstAccessorNG(rect.x(), rect.y());
     KisRandomConstAccessorSP gy_iter = x_denormalised->createRandomConstAccessorNG(rect.x(), rect.y());
 
     for (int x = rect.x() + 1; x < rect.x() + rect.width() - 1; x++) {
         for (int y = rect.y() + 1; y < rect.y() + rect.height() - 1; y++) {
             randomSobel->moveTo(x, y);
             const float current = *randomSobel->rawData();
             float firstIntensity, secondIntensity;
             gx_iter->moveTo(x, y);
             gy_iter->moveTo(x, y);
             const float direction = atan2(*gx_iter->rawDataConst(), *gy_iter->rawDataConst());
 
             if (direction <= 1 || direction > 7) {
                 randomSobel->moveTo(x + 1, y);
                 firstIntensity = *randomSobel->rawData();
                 randomSobel->moveTo(x - 1, y);
                 secondIntensity = *randomSobel->rawData();
             }
 
             if (direction > 1 || direction <= 3) {
                 randomSobel->moveTo(x + 1, y + 1);
                 firstIntensity = *randomSobel->rawData();
                 randomSobel->moveTo(x - 1, y - 1);
                 secondIntensity = *randomSobel->rawData();
             }
 
             if (direction > 3 || direction <= 5) {
                 randomSobel->moveTo(x, y + 1);
                 firstIntensity = *randomSobel->rawData();
                 randomSobel->moveTo(x, y - 1);
                 secondIntensity = *randomSobel->rawData();
             }
 
             if (direction > 5 || direction <= 7) {
                 randomSobel->moveTo(x + 1, y - 1);
                 firstIntensity = *randomSobel->rawData();
                 randomSobel->moveTo(x - 1, y + 1);
                 secondIntensity = *randomSobel->rawData();
             }
 
             randomSobel->moveTo(x, y);
 
             if (2 * current <= (firstIntensity + secondIntensity)) {
                 quint8* temp = new quint8();
                 finalNorm[0] = 0.0;
                 device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                 memcpy(randomSobel->rawData(), temp, device->pixelSize());
             }
         }
     }
 
     for (int x = rect.x() + 1; x < rect.x() + rect.width() - 1; x++) {
         for (int y = rect.y() + 1; y < rect.y() + rect.height() - 1; y++) {
             randomSobel->moveTo(x, y);
             quint8 intensity = *randomSobel->rawData();
             if (intensity < thresholdMin) {
                 quint8* temp = new quint8();
                 finalNorm[0] = 0.0;
                 device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                 memcpy(randomSobel->rawData(), temp, device->pixelSize());
             } else if (intensity < thresholdMax) {
                 randomSobel->moveTo(x + 1, y);
                 quint8 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
                 randomSobel->moveTo(x - 1, y);
                 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
                 randomSobel->moveTo(x, y + 1);
                 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
                 randomSobel->moveTo(x, y - 1);
                 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
                 randomSobel->moveTo(x + 1, y + 1);
                 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
                 randomSobel->moveTo(x - 1, y - 1);
                 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
                 randomSobel->moveTo(x + 1, y - 1);
                 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
                 randomSobel->moveTo(x - 1, y + 1);
                 intensity = *randomSobel->rawData();
                 if (intensity > thresholdMax) {
                     quint8* temp = new quint8();
                     finalNorm[0] = 1.0;
                     device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                     memcpy(randomSobel->rawData(), temp, device->pixelSize());
                     continue;
                 }
 
             } else {
                 quint8* temp = new quint8();
                 finalNorm[0] = 1.0;
                 device->colorSpace()->fromNormalisedChannelsValue(temp, finalNorm);
                 memcpy(randomSobel->rawData(), temp, device->pixelSize());
             }
         }
     }
 
     KisPainter::copyAreaOptimized(rect.topLeft(), device, _device, rect);
 }
 
 void KisEdgeDetectionKernel::convertToNormalMap(KisPaintDeviceSP device,
-                                                const QRect& rect,
+                                                const QRect &rect,
                                                 qreal xRadius,
                                                 qreal yRadius,
                                                 KisEdgeDetectionKernel::FilterType type,
                                                 int channelToConvert,
                                                 QVector<int> channelOrder,
                                                 QVector<bool> channelFlip,
-                                                const QBitArray& channelFlags,
-                                                KoUpdater* progressUpdater)
+                                                const QBitArray &channelFlags,
+                                                KoUpdater *progressUpdater)
 {
     QPoint srcTopLeft = rect.topLeft();
     KisPainter finalPainter(device);
     finalPainter.setChannelFlags(channelFlags);
     finalPainter.setProgress(progressUpdater);
     KisPaintDeviceSP x_denormalised = new KisPaintDevice(device->colorSpace());
     KisPaintDeviceSP y_denormalised = new KisPaintDevice(device->colorSpace());
     x_denormalised->prepareClone(device);
     y_denormalised->prepareClone(device);
 
-    KisConvolutionKernelSP kernelHorizLeftRight =
-        KisEdgeDetectionKernel::createHorizontalKernel(yRadius, type, true, !channelFlip[1]);
-    KisConvolutionKernelSP kernelVerticalTopBottom =
-        KisEdgeDetectionKernel::createVerticalKernel(xRadius, type, true, !channelFlip[0]);
+    KisConvolutionKernelSP kernelHorizLeftRight = KisEdgeDetectionKernel::createHorizontalKernel(yRadius, type, true, !channelFlip[1]);
+    KisConvolutionKernelSP kernelVerticalTopBottom = KisEdgeDetectionKernel::createVerticalKernel(xRadius, type, true, !channelFlip[0]);
 
     qreal horizontalCenter = qreal(kernelHorizLeftRight->width()) / 2.0;
     qreal verticalCenter = qreal(kernelVerticalTopBottom->height()) / 2.0;
 
     KisConvolutionPainter horizPainterLR(y_denormalised);
     horizPainterLR.setChannelFlags(channelFlags);
     horizPainterLR.setProgress(progressUpdater);
-    horizPainterLR.applyMatrix(kernelHorizLeftRight,
-                               device,
+    horizPainterLR.applyMatrix(kernelHorizLeftRight, device,
                                srcTopLeft - QPoint(ceil(horizontalCenter), 0),
                                srcTopLeft - QPoint(ceil(horizontalCenter), 0),
-                               rect.size() + QSize(2 * ceil(horizontalCenter), 0),
-                               BORDER_REPEAT);
+                               rect.size() + QSize(2 * ceil(horizontalCenter), 0), BORDER_REPEAT);
+
 
     KisConvolutionPainter verticalPainterTB(x_denormalised);
     verticalPainterTB.setChannelFlags(channelFlags);
     verticalPainterTB.setProgress(progressUpdater);
-    verticalPainterTB.applyMatrix(kernelVerticalTopBottom,
-                                  device,
+    verticalPainterTB.applyMatrix(kernelVerticalTopBottom, device,
                                   srcTopLeft - QPoint(0, ceil(verticalCenter)),
                                   srcTopLeft - QPoint(0, ceil(verticalCenter)),
-                                  rect.size() + QSize(0, 2 * ceil(verticalCenter)),
-                                  BORDER_REPEAT);
+                                  rect.size() + QSize(0, 2 * ceil(verticalCenter)), BORDER_REPEAT);
 
     KisSequentialIterator yItterator(y_denormalised, rect);
     KisSequentialIterator xItterator(x_denormalised, rect);
     KisSequentialIterator finalIt(device, rect);
     const int pixelSize = device->colorSpace()->pixelSize();
     const int channels = device->colorSpace()->channelCount();
     const int alphaPos = device->colorSpace()->alphaPos();
     KIS_SAFE_ASSERT_RECOVER_RETURN(alphaPos >= 0);
 
     QVector<float> yNormalised(channels);
     QVector<float> xNormalised(channels);
     QVector<float> finalNorm(channels);
 
-    while (yItterator.nextPixel() && xItterator.nextPixel() && finalIt.nextPixel()) {
+    while(yItterator.nextPixel() && xItterator.nextPixel() && finalIt.nextPixel()) {
         device->colorSpace()->normalisedChannelsValue(yItterator.rawData(), yNormalised);
         device->colorSpace()->normalisedChannelsValue(xItterator.rawData(), xNormalised);
 
         qreal z = 1.0;
-        if (channelFlip[2] == true) {
-            z = -1.0;
+        if (channelFlip[2]==true){
+            z=-1.0;
         }
-        QVector3D normal =
-            QVector3D((xNormalised[channelToConvert] - 0.5) * 2, (yNormalised[channelToConvert] - 0.5) * 2, z);
+        QVector3D normal = QVector3D((xNormalised[channelToConvert]-0.5)*2, (yNormalised[channelToConvert]-0.5)*2, z);
         normal.normalize();
         finalNorm.fill(1.0);
-        for (int c = 0; c < 3; c++) {
-            finalNorm[device->colorSpace()->channels().at(channelOrder[c])->displayPosition()] =
-                (normal[channelOrder[c]] / 2) + 0.5;
+        for (int c = 0; c<3; c++) {
+            finalNorm[device->colorSpace()->channels().at(channelOrder[c])->displayPosition()] = (normal[channelOrder[c]]/2)+0.5;
         }
 
-        finalNorm[alphaPos] = 1.0;
+        finalNorm[alphaPos]= 1.0;
 
         quint8* pixel = finalIt.rawData();
         device->colorSpace()->fromNormalisedChannelsValue(pixel, finalNorm);
         memcpy(finalIt.rawData(), pixel, pixelSize);
+
     }
 }
diff --git a/libs/image/kis_edge_detection_kernel.h b/libs/image/kis_edge_detection_kernel.h
index ce1f6e7092..dbc5704473 100644
--- a/libs/image/kis_edge_detection_kernel.h
+++ b/libs/image/kis_edge_detection_kernel.h
@@ -1,162 +1,153 @@
 /*
  *  Copyright (c) 2017 Wolthera van Hövell tot Westerflier <griffinvalley@gmail.com>
  *
  *  This program is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU General Public License as published by
  *  the Free Software Foundation; either version 2 of the License, or
  *  (at your option) any later version.
  *
  *  This program is distributed in the hope that it will be useful,
  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  *  GNU General Public License for more details.
  *
  *  You should have received a copy of the GNU General Public License
  *  along with this program; if not, write to the Free Software
  *  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  */
 
 #ifndef KIS_EDGE_DETECTION_KERNEL_H
 #define KIS_EDGE_DETECTION_KERNEL_H
 
-#include "kis_types.h"
 #include "kritaimage_export.h"
+#include "kis_types.h"
 
 #include <Eigen/Core>
 
 class QRect;
 
 class KRITAIMAGE_EXPORT KisEdgeDetectionKernel
 {
-    public:
+public:
     KisEdgeDetectionKernel();
 
-    enum FilterType
-    {
-        Simple,     // A weird simple method used in our old sobel filter
-        Prewit,     // The simpler prewitt detection, which doesn't smooth.
-        SobelVector // Sobel does smooth. The creation of bigger kernels is based on an approach regarding vectors.
+    enum FilterType {
+        Simple, //A weird simple method used in our old sobel filter
+        Prewit, //The simpler prewitt detection, which doesn't smooth.
+        SobelVector //Sobel does smooth. The creation of bigger kernels is based on an approach regarding vectors.
     };
 
-    enum FilterOutput
-    {
+    enum FilterOutput {
         pythagorean,
         xGrowth,
         xFall,
         yGrowth,
         yFall,
         radian
     };
 
     /**
      * @brief createHorizontalMatrix
      * @param radius the radius. 1 makes a 3x3 kernel.
      * @param type One of the entries in the enum Filtertype
      * @param reverse which direction the gradient goes.
      * The horizontal gradient by default detects the rightmost edges.
      * Reversed it selects the leftmost edges.
      * @return
      */
 
-    static Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> createHorizontalMatrix(qreal radius,
-                                                                                       FilterType type,
-                                                                                       bool reverse = false);
+    static Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic>
+        createHorizontalMatrix(qreal radius, FilterType type, bool reverse = false);
     /**
      * @brief createVerticalMatrix
      * @param radius the radius. 1 makes a 3x3 kernel.
      * @param type One of the entries in the enum Filtertype
      * @param reverse which direction the gradient goes.
      * The vertical gradient by default detects the topmost edges.
      * Reversed it selects the bottommost edges.
      * @return
      */
-    static Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> createVerticalMatrix(qreal radius,
-                                                                                     FilterType type,
-                                                                                     bool reverse = false);
+    static Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic>
+        createVerticalMatrix(qreal radius, FilterType type, bool reverse = false);
 
-    static KisConvolutionKernelSP createHorizontalKernel(qreal radius,
-                                                         FilterType type,
-                                                         bool denormalize = true,
-                                                         bool reverse = false);
+    static KisConvolutionKernelSP
+        createHorizontalKernel(qreal radius, FilterType type, bool denormalize = true, bool reverse = false);
 
-    static KisConvolutionKernelSP createVerticalKernel(qreal radius,
-                                                       FilterType type,
-                                                       bool denormalize = true,
-                                                       bool reverse = false);
+    static KisConvolutionKernelSP
+        createVerticalKernel(qreal radius, FilterType type, bool denormalize = true, bool reverse = false);
 
     static int kernelSizeFromRadius(qreal radius);
     static qreal sigmaFromRadius(qreal radius);
 
     /**
      * @brief applyEdgeDetection
      * This applies the edge detection filter to the device.
      * @param device the device to apply to.
      * @param rect the affected rect.
      * @param xRadius the radius of the horizontal sampling, radius of 0 is effectively disabling it.
      * @param yRadius the radius of the vertical sampling, refius of 0 is effectively disabling it.
      * @param type the type can be prewitt, sobel or simple, each of which
      * have a different sampling for the eventual edge detection.
      * @param channelFlags the affected channels.
      * @param progressUpdater the progress updater if it exists.
      * @param output the output mode.
      * @param writeToAlpha whether or not to have the result applied to the transparency than the color channels,
      * this is useful for fringe effects.
      */
     static void applyEdgeDetection(KisPaintDeviceSP device,
-                                   const QRect& rect,
-                                   qreal xRadius,
-                                   qreal yRadius,
-                                   FilterType type,
-                                   const QBitArray& channelFlags,
-                                   KoUpdater* progressUpdater,
-                                   FilterOutput output = pythagorean,
-                                   bool writeToAlpha = false);
+                              const QRect& rect,
+                              qreal xRadius, qreal yRadius,
+                              FilterType type,
+                              const QBitArray &channelFlags,
+                              KoUpdater *progressUpdater,
+                              FilterOutput output = pythagorean,
+                              bool writeToAlpha = false);
 
     /**
      * @brief applyCannyEdgeDetection
      * This applies the canny edge detection filter to the device.
      * @param device the device to apply to.
      * @param rect the affected rect.
      * @param xRadius the radius of the horizontal sampling, radius of 0 is effectively disabling it.
      * @param yRadius the radius of the vertical sampling, refius of 0 is effectively disabling it.
      * @param channelFlags the affected channels.
      * @param progressUpdater the progress updater if it exists.
      * @param writeToAlpha whether or not to have the result applied to the transparency than the color channels,
      * this is useful for fringe effects.
      */
     static void applyCannyEdgeDetection(KisPaintDeviceSP device,
                                         const QRect& rect,
                                         qreal xRadius,
                                         qreal yRadius,
                                         const QBitArray& channelFlags,
                                         KoUpdater* progressUpdater,
                                         int thresholdMax,
                                         int thresholdMin);
 
     /**
      * @brief converToNormalMap
      * Convert a channel of the device to a normal map. The channel will be interpreted as a heightmap.
      * @param device the device
      * @param rect the rectangle to apply this to.
      * @param xRadius the xradius
      * @param yRadius the yradius
      * @param type the edge detection filter.
      * @param channelToConvert the channel to use as a grayscale.
      * @param channelOrder the order in which the xyz coordinates ought to be written to the pixels.
      * @param channelFlip whether to flip the channels
      * @param channelFlags the channel flags
      * @param progressUpdater
      */
     static void convertToNormalMap(KisPaintDeviceSP device,
-                                   const QRect& rect,
-                                   qreal xRadius,
-                                   qreal yRadius,
-                                   FilterType type,
-                                   int channelToConvert,
-                                   QVector<int> channelOrder,
-                                   QVector<bool> channelFlip,
-                                   const QBitArray& channelFlags,
-                                   KoUpdater* progressUpdater);
+                                  const QRect & rect,
+                                  qreal xRadius,
+                                  qreal yRadius,
+                                  FilterType type,
+                                  int channelToConvert,
+                                  QVector<int> channelOrder,
+                                  QVector<bool> channelFlip,
+                                  const QBitArray &channelFlags,
+                                  KoUpdater *progressUpdater);
 };
 
 #endif // KIS_EDGE_DETECTION_KERNEL_H
diff --git a/plugins/filters/edgedetection/kis_edge_detection_filter.cpp b/plugins/filters/edgedetection/kis_edge_detection_filter.cpp
index 94541cab63..23dc3cea3a 100644
--- a/plugins/filters/edgedetection/kis_edge_detection_filter.cpp
+++ b/plugins/filters/edgedetection/kis_edge_detection_filter.cpp
@@ -1,185 +1,168 @@
 /*
  * Copyright (c) 2017 Wolthera van Hövell tot Westerflier <griffinvalley@gmail.com>
  *
  *  This program is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU General Public License as published by
  *  the Free Software Foundation; either version 2 of the License, or
  *  (at your option) any later version.
  *
  *  This program is distributed in the hope that it will be useful,
  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  *  GNU General Public License for more details.
  *
  *  You should have received a copy of the GNU General Public License
  *  along with this program; if not, write to the Free Software
  *  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  */
 #include "kis_edge_detection_filter.h"
 #include "kis_wdg_edge_detection.h"
+#include <kis_edge_detection_kernel.h>
 #include <kis_convolution_kernel.h>
 #include <kis_convolution_painter.h>
-#include <kis_edge_detection_kernel.h>
 
-#include <KoColorModelStandardIds.h>
 #include <KoColorSpaceRegistry.h>
+#include <KoColorModelStandardIds.h>
 
-#include "kis_lod_transform.h"
 #include <filter/kis_filter_category_ids.h>
 #include <filter/kis_filter_configuration.h>
+#include <kis_selection.h>
 #include <kis_paint_device.h>
 #include <kis_processing_information.h>
-#include <kis_selection.h>
+#include "kis_lod_transform.h"
 
 #include <kpluginfactory.h>
 
-#include <filter/kis_filter_registry.h>
 #include <klocalizedstring.h>
+#include <filter/kis_filter_registry.h>
 
-K_PLUGIN_FACTORY_WITH_JSON(KritaEdgeDetectionFilterFactory,
-                           "kritaedgedetection.json",
-                           registerPlugin<KritaEdgeDetectionFilter>();)
+K_PLUGIN_FACTORY_WITH_JSON(KritaEdgeDetectionFilterFactory, "kritaedgedetection.json", registerPlugin<KritaEdgeDetectionFilter>();)
 
-KritaEdgeDetectionFilter::KritaEdgeDetectionFilter(QObject* parent, const QVariantList&)
+KritaEdgeDetectionFilter::KritaEdgeDetectionFilter(QObject *parent, const QVariantList &)
     : QObject(parent)
 {
     KisFilterRegistry::instance()->add(KisFilterSP(new KisEdgeDetectionFilter()));
 }
 
-KritaEdgeDetectionFilter::~KritaEdgeDetectionFilter() {}
+KritaEdgeDetectionFilter::~KritaEdgeDetectionFilter()
+{
+}
 
-KisEdgeDetectionFilter::KisEdgeDetectionFilter()
-    : KisFilter(id(), FiltersCategoryEdgeDetectionId, i18n("&Edge Detection..."))
+KisEdgeDetectionFilter::KisEdgeDetectionFilter(): KisFilter(id(), FiltersCategoryEdgeDetectionId, i18n("&Edge Detection..."))
 {
     setSupportsPainting(true);
     setSupportsAdjustmentLayers(true);
     setSupportsLevelOfDetail(true);
     setColorSpaceIndependence(FULLY_INDEPENDENT);
     setShowConfigurationWidget(true);
 }
 
-void KisEdgeDetectionFilter::processImpl(KisPaintDeviceSP device,
-                                         const QRect& rect,
-                                         const KisFilterConfigurationSP config,
-                                         KoUpdater* progressUpdater) const
+void KisEdgeDetectionFilter::processImpl(KisPaintDeviceSP device, const QRect &rect, const KisFilterConfigurationSP config, KoUpdater *progressUpdater) const
 {
     Q_ASSERT(device != 0);
 
     KisFilterConfigurationSP configuration = config ? config : new KisFilterConfiguration(id().id(), 1);
 
     KisLodTransformScalar t(device);
 
     QVariant value;
     configuration->getProperty("horizRadius", value);
-    qreal horizontalRadius = t.scale(value.toFloat());
+    float horizontalRadius = t.scale(value.toFloat());
     configuration->getProperty("vertRadius", value);
-    qreal verticalRadius = t.scale(value.toFloat());
+    float verticalRadius = t.scale(value.toFloat());
 
     QBitArray channelFlags;
     if (configuration) {
         channelFlags = configuration->channelFlags();
     }
 
     if (config->getString("type") == "canny") {
         KisFilterSP gaussian = KisFilterRegistry::instance()->get("gaussian blur");
         KisFilterConfigurationSP gaussianConf = gaussian->defaultConfiguration();
         gaussian->process(device, rect, gaussianConf, progressUpdater);
 
         int max = configuration->getInt("max_threshold", 200);
         int min = configuration->getInt("min_threshold", 100);
         KisEdgeDetectionKernel::applyCannyEdgeDetection(
             device, rect, horizontalRadius, verticalRadius, channelFlags, progressUpdater, max, min);
         return;
     }
 
     KisEdgeDetectionKernel::FilterType type = KisEdgeDetectionKernel::SobelVector;
-
     if (config->getString("type") == "prewitt") {
         type = KisEdgeDetectionKernel::Prewit;
-    }
-
-    if (config->getString("type") == "simple") {
+    } else if (config->getString("type") == "simple") {
         type = KisEdgeDetectionKernel::Simple;
     }
 
     KisEdgeDetectionKernel::FilterOutput output = KisEdgeDetectionKernel::pythagorean;
     if (config->getString("output") == "xGrowth") {
         output = KisEdgeDetectionKernel::xGrowth;
     } else if (config->getString("output") == "xFall") {
         output = KisEdgeDetectionKernel::xFall;
     } else if (config->getString("output") == "yGrowth") {
         output = KisEdgeDetectionKernel::yGrowth;
     } else if (config->getString("output") == "yFall") {
         output = KisEdgeDetectionKernel::yFall;
     } else if (config->getString("output") == "radian") {
         output = KisEdgeDetectionKernel::radian;
     }
 
     KisEdgeDetectionKernel::applyEdgeDetection(device,
                                                rect,
                                                horizontalRadius,
                                                verticalRadius,
                                                type,
                                                channelFlags,
                                                progressUpdater,
                                                output,
                                                config->getBool("transparency", false));
 }
 
 KisFilterConfigurationSP KisEdgeDetectionFilter::defaultConfiguration() const
 {
     KisFilterConfigurationSP config = factoryConfiguration();
     config->setProperty("horizRadius", 1);
     config->setProperty("vertRadius", 1);
     config->setProperty("type", "prewitt");
     config->setProperty("output", "pythagorean");
     config->setProperty("lockAspect", true);
     config->setProperty("transparency", false);
 
     return config;
 }
 
-KisConfigWidget* KisEdgeDetectionFilter::createConfigurationWidget(QWidget* parent,
-                                                                   const KisPaintDeviceSP dev,
-                                                                   bool) const
+KisConfigWidget *KisEdgeDetectionFilter::createConfigurationWidget(QWidget *parent, const KisPaintDeviceSP dev, bool) const
 {
     Q_UNUSED(dev);
     return new KisWdgEdgeDetection(parent);
 }
 
-QRect KisEdgeDetectionFilter::neededRect(const QRect& rect, const KisFilterConfigurationSP _config, int lod) const
+QRect KisEdgeDetectionFilter::neededRect(const QRect &rect, const KisFilterConfigurationSP _config, int lod) const
 {
     KisLodTransformScalar t(lod);
 
     QVariant value;
     /**
      * NOTE: integer division by two is done on purpose,
      *       because the kernel size is always odd
      */
-    const int halfWidth = _config->getProperty("horizRadius", value)
-                              ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2
-                              : 5;
-    const int halfHeight = _config->getProperty("vertRadius", value)
-                               ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2
-                               : 5;
+    const int halfWidth = _config->getProperty("horizRadius", value) ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2 : 5;
+    const int halfHeight = _config->getProperty("vertRadius", value) ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2 : 5;
 
     return rect.adjusted(-halfWidth * 2, -halfHeight * 2, halfWidth * 2, halfHeight * 2);
 }
 
-QRect KisEdgeDetectionFilter::changedRect(const QRect& rect, const KisFilterConfigurationSP _config, int lod) const
+QRect KisEdgeDetectionFilter::changedRect(const QRect &rect, const KisFilterConfigurationSP _config, int lod) const
 {
     KisLodTransformScalar t(lod);
 
     QVariant value;
 
-    const int halfWidth = _config->getProperty("horizRadius", value)
-                              ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2
-                              : 5;
-    const int halfHeight = _config->getProperty("vertRadius", value)
-                               ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2
-                               : 5;
+    const int halfWidth = _config->getProperty("horizRadius", value) ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2 : 5;
+    const int halfHeight = _config->getProperty("vertRadius", value) ? KisEdgeDetectionKernel::kernelSizeFromRadius(t.scale(value.toFloat())) / 2 : 5;
 
-    return rect.adjusted(-halfWidth, -halfHeight, halfWidth, halfHeight);
+    return rect.adjusted( -halfWidth, -halfHeight, halfWidth, halfHeight);
 }
 
 #include "kis_edge_detection_filter.moc"
diff --git a/plugins/tools/selectiontools/KisMagneticWorker.cc b/plugins/tools/selectiontools/KisMagneticWorker.cc
index 17b14cb820..8a21ac8069 100644
--- a/plugins/tools/selectiontools/KisMagneticWorker.cc
+++ b/plugins/tools/selectiontools/KisMagneticWorker.cc
@@ -1,284 +1,282 @@
 /*
  *  Copyright (c) 2019 Kuntal Majumder <hellozee@disroot.org>
  *
  *  This library is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU Lesser General Public License as published by
  *  the Free Software Foundation; version 2.1 of the License.
  *
  *  This library is distributed in the hope that it will be useful,
  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  *  GNU Lesser General Public License for more details.
  *
  *  You should have received a copy of the GNU Lesser General Public License
  *  along with this program; if not, write to the Free Software
  *  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  */
 
 #include "KisMagneticWorker.h"
 
-#include <kis_algebra_2d.h>
-#include <kis_filter.h>
-#include <kis_filter_configuration.h>
-#include <kis_filter_registry.h>
 #include <kis_gaussian_kernel.h>
-#include <kis_painter.h>
 #include <lazybrush/kis_lazy_fill_tools.h>
+#include <kis_algebra_2d.h>
+#include <kis_painter.h>
 
-#include <QPainter>
-#include <QPolygon>
 #include <QtCore>
+#include <QPolygon>
+#include <QPainter>
 
 #include <boost/graph/astar_search.hpp>
 #include <krita_utils.h>
 
 #include "KisMagneticGraph.h"
 
-struct DistanceMap
-{
+struct DistanceMap {
     typedef VertexDescriptor key_type;
     typedef double data_type;
     typedef std::pair<key_type, data_type> value_type;
 
-    explicit DistanceMap(double const& dval)
+    explicit DistanceMap(double const &dval)
         : m_default(dval)
-    {}
+    { }
 
-    data_type& operator[](key_type const& k)
+    data_type &operator [] (key_type const &k)
     {
         if (m.find(k) == m.end())
             m[k] = m_default;
         return m[k];
     }
 
-    private:
+private:
     std::map<key_type, data_type> m;
-    data_type const m_default;
+    data_type const               m_default;
 };
 
-struct PredecessorMap
-{
+struct PredecessorMap {
     PredecessorMap() = default;
 
-    PredecessorMap(PredecessorMap const& that) = default;
+    PredecessorMap(PredecessorMap const &that) = default;
 
     typedef VertexDescriptor key_type;
     typedef VertexDescriptor value_type;
     typedef boost::read_write_property_map_tag category;
 
-    VertexDescriptor& operator[](VertexDescriptor v) { return m_map[v]; }
+    VertexDescriptor &operator [] (VertexDescriptor v)
+    {
+        return m_map[v];
+    }
 
     std::map<VertexDescriptor, VertexDescriptor> m_map;
 };
 
-VertexDescriptor get(PredecessorMap const& m, VertexDescriptor v)
+VertexDescriptor get(PredecessorMap const &m, VertexDescriptor v)
 {
     auto found = m.m_map.find(v);
     return found != m.m_map.end() ? found->second : v;
 }
 
-void put(PredecessorMap& m, VertexDescriptor key, VertexDescriptor value)
+void put(PredecessorMap &m, VertexDescriptor key, VertexDescriptor value)
 {
     m.m_map[key] = value;
 }
 
 double EuclideanDistance(VertexDescriptor p1, VertexDescriptor p2)
 {
     return std::sqrt(std::pow(p1.y - p2.y, 2) + std::pow(p1.x - p2.x, 2));
 }
 
 class AStarHeuristic : public boost::astar_heuristic<KisMagneticGraph, double>
 {
-    private:
+private:
     VertexDescriptor m_goal;
 
-    public:
-    explicit AStarHeuristic(VertexDescriptor goal)
-        : m_goal(goal)
-    {}
+public:
+    explicit AStarHeuristic(VertexDescriptor goal) :
+        m_goal(goal)
+    { }
 
-    double operator()(VertexDescriptor v) { return EuclideanDistance(v, m_goal); }
+    double operator () (VertexDescriptor v)
+    {
+        return EuclideanDistance(v, m_goal);
+    }
 };
 
-struct GoalFound
-{};
+struct GoalFound { };
 
 class AStarGoalVisitor : public boost::default_astar_visitor
 {
-    public:
-    explicit AStarGoalVisitor(VertexDescriptor goal)
-        : m_goal(goal)
-    {}
+public:
+    explicit AStarGoalVisitor(VertexDescriptor goal) : m_goal(goal){ }
 
-    void examine_vertex(VertexDescriptor u, KisMagneticGraph const& g)
+    void examine_vertex(VertexDescriptor u, KisMagneticGraph const &g)
     {
         Q_UNUSED(g)
         if (u == m_goal) {
             throw GoalFound();
         }
     }
 
-    private:
+private:
     VertexDescriptor m_goal;
 };
 
-struct WeightMap
-{
+struct WeightMap {
     typedef std::pair<VertexDescriptor, VertexDescriptor> key_type;
     typedef double data_type;
     typedef std::pair<key_type, data_type> value_type;
 
     WeightMap() = default;
 
-    explicit WeightMap(const KisMagneticGraph& g)
-        : m_graph(g)
-    {}
+    explicit WeightMap(const KisMagneticGraph &g) :
+        m_graph(g)
+    { }
 
-    data_type& operator[](key_type const& k)
+    data_type &operator [] (key_type const &k)
     {
         if (m_map.find(k) == m_map.end()) {
             double edge_gradient = (m_graph.getIntensity(k.first) + m_graph.getIntensity(k.second)) / 2;
             m_map[k] = EuclideanDistance(k.first, k.second) + 255.0 - edge_gradient;
         }
         return m_map[k];
     }
 
-    private:
+private:
     std::map<key_type, data_type> m_map;
-    KisMagneticGraph m_graph;
+    KisMagneticGraph              m_graph;
 };
 
 KisMagneticLazyTiles::KisMagneticLazyTiles(KisPaintDeviceSP dev)
 {
     m_dev = KisPainter::convertToAlphaAsGray(dev);
     QSize s = dev->defaultBounds()->bounds().size();
-    m_tileSize = KritaUtils::optimalPatchSize();
-    m_tilesPerRow = (int)std::ceil((double)s.width() / (double)m_tileSize.width());
-    int tilesPerColumn = (int)std::ceil((double)s.height() / (double)m_tileSize.height());
+    m_tileSize    = KritaUtils::optimalPatchSize();
+    m_tilesPerRow = (int) std::ceil((double) s.width() / (double) m_tileSize.width());
+    int tilesPerColumn = (int) std::ceil((double) s.height() / (double) m_tileSize.height());
     m_dev->setDefaultBounds(dev->defaultBounds());
 
     for (int i = 0; i < tilesPerColumn; i++) {
         for (int j = 0; j < m_tilesPerRow; j++) {
-            int width = std::min(s.width() - j * m_tileSize.width(), m_tileSize.width());
+            int width  = std::min(s.width() - j * m_tileSize.width(), m_tileSize.width());
             int height = std::min(s.height() - i * m_tileSize.height(), m_tileSize.height());
-            QRect temp(j * m_tileSize.width(), i * m_tileSize.height(), width, height);
+            QRect temp(j *m_tileSize.width(), i *m_tileSize.height(), width, height);
             m_tiles.push_back(temp);
         }
     }
     m_radiusRecord = QVector<qreal>(m_tiles.size(), -1);
 }
 
-void KisMagneticLazyTiles::filter(qreal radius, QRect& rect)
+void KisMagneticLazyTiles::filter(qreal radius, QRect &rect)
 {
-    auto divide = [](QPoint p, QSize s) { return QPoint(p.x() / s.width(), p.y() / s.height()); };
+    auto divide = [](QPoint p, QSize s){
+                      return QPoint(p.x() / s.width(), p.y() / s.height());
+                  };
 
     QPoint firstTile = divide(rect.topLeft(), m_tileSize);
-    QPoint lastTile = divide(rect.bottomRight(), m_tileSize);
+    QPoint lastTile  = divide(rect.bottomRight(), m_tileSize);
     for (int i = firstTile.y(); i <= lastTile.y(); i++) {
         for (int j = firstTile.x(); j <= lastTile.x(); j++) {
             int currentTile = i * m_tilesPerRow + j;
             if (radius != m_radiusRecord[currentTile]) {
                 QRect bounds = m_tiles[currentTile];
                 KisGaussianKernel::applyTightLoG(m_dev, bounds, radius, -1.0, QBitArray(), nullptr);
                 KisLazyFillTools::normalizeAlpha8Device(m_dev, bounds);
                 m_radiusRecord[currentTile] = radius;
             }
         }
     }
 }
 
-KisMagneticWorker::KisMagneticWorker(const KisPaintDeviceSP& dev)
-    : m_lazyTileFilter(dev)
-{}
+KisMagneticWorker::KisMagneticWorker(const KisPaintDeviceSP &dev) :
+    m_lazyTileFilter(dev)
+{ }
 
 QVector<QPointF> KisMagneticWorker::computeEdge(int bounds, QPoint begin, QPoint end, qreal radius)
 {
     QRect rect;
-    KisAlgebra2D::accumulateBounds(QVector<QPoint>{ begin, end }, &rect);
+    KisAlgebra2D::accumulateBounds(QVector<QPoint> { begin, end }, &rect);
     rect = kisGrowRect(rect, bounds);
     m_lazyTileFilter.filter(radius, rect);
 
     VertexDescriptor goal(end);
     VertexDescriptor start(begin);
 
     m_graph = new KisMagneticGraph(m_lazyTileFilter.device(), rect);
 
     // How many maps does it require?
-    // Take a look here, if it doesn't make sense,
-    // https://www.boost.org/doc/libs/1_70_0/libs/graph/doc/astar_search.html
+    // Take a look here, if it doesn't make sense, https://www.boost.org/doc/libs/1_70_0/libs/graph/doc/astar_search.html
     PredecessorMap pmap;
     DistanceMap dmap(std::numeric_limits<double>::max());
     dmap[start] = 0;
     std::map<VertexDescriptor, double> rmap;
     std::map<VertexDescriptor, boost::default_color_type> cmap;
     std::map<VertexDescriptor, double> imap;
     WeightMap wmap(*m_graph);
     AStarHeuristic heuristic(goal);
     QVector<QPointF> result;
 
     try {
         boost::astar_search_no_init(
-            *m_graph,
-            start,
-            heuristic,
+            *m_graph, start, heuristic,
             boost::visitor(AStarGoalVisitor(goal))
-                .distance_map(boost::associative_property_map<DistanceMap>(dmap))
-                .predecessor_map(boost::ref(pmap))
-                .weight_map(boost::associative_property_map<WeightMap>(wmap))
-                .vertex_index_map(boost::associative_property_map<std::map<VertexDescriptor, double>>(imap))
-                .rank_map(boost::associative_property_map<std::map<VertexDescriptor, double>>(rmap))
-                .color_map(boost::associative_property_map<std::map<VertexDescriptor, boost::default_color_type>>(cmap))
-                .distance_combine(std::plus<double>())
-                .distance_compare(std::less<double>()));
-    } catch (GoalFound const&) {
+            .distance_map(boost::associative_property_map<DistanceMap>(dmap))
+            .predecessor_map(boost::ref(pmap))
+            .weight_map(boost::associative_property_map<WeightMap>(wmap))
+            .vertex_index_map(boost::associative_property_map<std::map<VertexDescriptor, double> >(imap))
+            .rank_map(boost::associative_property_map<std::map<VertexDescriptor, double> >(rmap))
+            .color_map(boost::associative_property_map<std::map<VertexDescriptor, boost::default_color_type> >
+                           (cmap))
+            .distance_combine(std::plus<double>())
+            .distance_compare(std::less<double>())
+            );
+    } catch (GoalFound const &) {
         for (VertexDescriptor u = goal; u != start; u = pmap[u]) {
             result.push_front(QPointF(u.x, u.y));
         }
     }
 
     result.push_front(QPoint(start.x, start.y));
 
     return result;
 } // KisMagneticWorker::computeEdge
 
 qreal KisMagneticWorker::intensity(QPoint pt)
 {
     return m_graph->getIntensity(VertexDescriptor(pt));
 }
 
 void KisMagneticWorker::saveTheImage(vQPointF points)
 {
     QImage img = m_lazyTileFilter.device()->convertToQImage(nullptr, m_lazyTileFilter.device()->exactBounds());
 
     const QPointF offset = m_lazyTileFilter.device()->exactBounds().topLeft();
-    for (QPointF& pt : points) {
+    for (QPointF &pt : points) {
         pt -= offset;
     }
 
     img = img.convertToFormat(QImage::Format_ARGB32);
     QPainter gc(&img);
 
     QPainterPath path;
 
     for (int i = 0; i < points.size(); i++) {
         if (i == 0) {
             path.moveTo(points[i]);
         } else {
             path.lineTo(points[i]);
         }
     }
 
     gc.setPen(Qt::blue);
     gc.drawPath(path);
 
     gc.setPen(Qt::green);
     gc.drawEllipse(points[0], 3, 3);
     gc.setPen(Qt::red);
     gc.drawEllipse(points[points.count() - 1], 2, 2);
 
-    for (QRect& r : m_lazyTileFilter.tiles()) {
+    for (QRect &r : m_lazyTileFilter.tiles() ) {
         gc.drawRect(r);
     }
 
     img.save("result.png");
 } // KisMagneticWorker::saveTheImage