mirror of
https://github.com/ShareX/ShareX.git
synced 2024-10-05 20:54:31 +13:00
Merge pull request #3826 from sylveon/master
Add user customizable gaussian blur
This commit is contained in:
commit
d544515559
7 changed files with 181 additions and 105 deletions
|
@ -27,31 +27,36 @@ namespace ShareX.HelpersLib
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{
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public class ConvolutionMatrix
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{
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public int Size { get; private set; }
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public int[,] Matrix { get; set; }
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public int Factor { get; set; }
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public int Offset { get; set; }
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private readonly double[,] matrix;
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public int Width => matrix.GetLength(1);
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public int Height => matrix.GetLength(0);
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public byte Offset { get; set; }
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public ConvolutionMatrix() : this(3)
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{
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}
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public ConvolutionMatrix(int size)
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public ConvolutionMatrix(int size) : this(size, size)
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{
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Size = size;
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Matrix = new int[Size, Size];
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Factor = 1;
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}
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public void SetAll(int value)
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public ConvolutionMatrix(int height, int width)
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{
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for (int y = 0; y < Size; y++)
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matrix = new double[height, width];
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}
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public void SetAll(double value)
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{
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for (int x = 0; x < Size; x++)
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for (int y = 0; y < Height; y++)
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{
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Matrix[x, y] = value;
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for (int x = 0; x < Width; x++)
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{
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matrix[y, x] = value;
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}
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}
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}
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public ref double this[int y, int x] => ref matrix[y, x];
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}
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}
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@ -23,6 +23,7 @@ You should have received a copy of the GNU General Public License
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#endregion License Information (GPL v3)
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// Adapted from https://stackoverflow.com/questions/33569396/correctly-implement-a-2-pass-gaussian-blur
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// Filters: http://www.codeproject.com/Articles/2008/Image-Processing-for-Dummies-with-C-and-GDI-Part-2
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using System;
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@ -33,83 +34,57 @@ namespace ShareX.HelpersLib
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{
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public static class ConvolutionMatrixManager
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{
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public static Image Apply(this ConvolutionMatrix matrix, Image img)
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public static Image Apply(this ConvolutionMatrix kernel, Image img)
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{
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int factor = Math.Max(matrix.Factor, 1);
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Bitmap result = (Bitmap)img.Clone();
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using (UnsafeBitmap source = new UnsafeBitmap((Bitmap)img, true, ImageLockMode.ReadOnly))
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using (UnsafeBitmap dest = new UnsafeBitmap(result, true, ImageLockMode.WriteOnly))
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{
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int height = source.Height - 2;
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int width = source.Width - 2;
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ColorBgra[,] pixelColor = new ColorBgra[3, 3];
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int pixel;
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ColorBgra color = new ColorBgra();
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int originX = (kernel.Width - 1) / 2;
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int originY = (kernel.Height - 1) / 2;
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for (int y = 0; y < height; y++)
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for (int y = 0; y < source.Height; y++)
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{
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for (int x = 0; x < width; x++)
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for (int x = 0; x < source.Width; x++)
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{
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pixelColor[0, 0] = source.GetPixel(x, y);
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pixelColor[0, 1] = source.GetPixel(x, y + 1);
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pixelColor[0, 2] = source.GetPixel(x, y + 2);
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pixelColor[1, 0] = source.GetPixel(x + 1, y);
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pixelColor[1, 1] = source.GetPixel(x + 1, y + 1);
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pixelColor[1, 2] = source.GetPixel(x + 1, y + 2);
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pixelColor[2, 0] = source.GetPixel(x + 2, y);
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pixelColor[2, 1] = source.GetPixel(x + 2, y + 1);
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pixelColor[2, 2] = source.GetPixel(x + 2, y + 2);
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double r = 0.0;
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double g = 0.0;
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double b = 0.0;
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pixel = (((pixelColor[0, 0].Blue * matrix.Matrix[0, 0]) +
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(pixelColor[1, 0].Blue * matrix.Matrix[1, 0]) +
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(pixelColor[2, 0].Blue * matrix.Matrix[2, 0]) +
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(pixelColor[0, 1].Blue * matrix.Matrix[0, 1]) +
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(pixelColor[1, 1].Blue * matrix.Matrix[1, 1]) +
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(pixelColor[2, 1].Blue * matrix.Matrix[2, 1]) +
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(pixelColor[0, 2].Blue * matrix.Matrix[0, 2]) +
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(pixelColor[1, 2].Blue * matrix.Matrix[1, 2]) +
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(pixelColor[2, 2].Blue * matrix.Matrix[2, 2])) / factor) + matrix.Offset;
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// Apply each matrix multiplier to the color components for each pixel.
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for (int fy = 0; fy < kernel.Height; fy++)
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{
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int fyr = fy - originY;
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int offsetY = y + fyr;
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if (pixel < 0) pixel = 0;
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else if (pixel > 255) pixel = 255;
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offsetY.Clamp(0, source.Height - 1);
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color.Blue = (byte)pixel;
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for (int fx = 0; fx < kernel.Width; fx++)
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{
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int fxr = fx - originX;
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int offsetX = x + fxr;
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pixel = (((pixelColor[0, 0].Green * matrix.Matrix[0, 0]) +
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(pixelColor[1, 0].Green * matrix.Matrix[1, 0]) +
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(pixelColor[2, 0].Green * matrix.Matrix[2, 0]) +
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(pixelColor[0, 1].Green * matrix.Matrix[0, 1]) +
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(pixelColor[1, 1].Green * matrix.Matrix[1, 1]) +
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(pixelColor[2, 1].Green * matrix.Matrix[2, 1]) +
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(pixelColor[0, 2].Green * matrix.Matrix[0, 2]) +
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(pixelColor[1, 2].Green * matrix.Matrix[1, 2]) +
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(pixelColor[2, 2].Green * matrix.Matrix[2, 2])) / factor) + matrix.Offset;
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offsetX.Clamp(0, source.Width - 1);
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if (pixel < 0) pixel = 0;
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else if (pixel > 255) pixel = 255;
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ColorBgra currentColor = source.GetPixel(offsetX, offsetY);
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color.Green = (byte)pixel;
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r += kernel[fy, fx] * currentColor.Red;
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g += kernel[fy, fx] * currentColor.Green;
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b += kernel[fy, fx] * currentColor.Blue;
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}
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}
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pixel = (((pixelColor[0, 0].Red * matrix.Matrix[0, 0]) +
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(pixelColor[1, 0].Red * matrix.Matrix[1, 0]) +
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(pixelColor[2, 0].Red * matrix.Matrix[2, 0]) +
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(pixelColor[0, 1].Red * matrix.Matrix[0, 1]) +
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(pixelColor[1, 1].Red * matrix.Matrix[1, 1]) +
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(pixelColor[2, 1].Red * matrix.Matrix[2, 1]) +
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(pixelColor[0, 2].Red * matrix.Matrix[0, 2]) +
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(pixelColor[1, 2].Red * matrix.Matrix[1, 2]) +
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(pixelColor[2, 2].Red * matrix.Matrix[2, 2])) / factor) + matrix.Offset;
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r += kernel.Offset;
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r.Clamp(0, 255);
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if (pixel < 0) pixel = 0;
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else if (pixel > 255) pixel = 255;
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g += kernel.Offset;
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g.Clamp(0, 255);
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color.Red = (byte)pixel;
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b += kernel.Offset;
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b.Clamp(0, 255);
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color.Alpha = pixelColor[1, 1].Alpha;
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dest.SetPixel(x + 1, y + 1, color);
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dest.SetPixel(x, y, new ColorBgra((byte)b, (byte)g, (byte)r, source.GetPixel(x, y).Alpha));
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}
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}
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}
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@ -120,38 +95,67 @@ public static Image Apply(this ConvolutionMatrix matrix, Image img)
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public static ConvolutionMatrix Smooth(int weight = 1)
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{
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ConvolutionMatrix cm = new ConvolutionMatrix();
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cm.SetAll(1);
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cm.Matrix[1, 1] = weight;
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cm.Factor = weight + 8;
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double factor = weight + 8;
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cm.SetAll(1 / factor);
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cm[1, 1] = weight / factor;
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return cm;
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}
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public static ConvolutionMatrix GaussianBlur(int weight = 4)
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private static double GaussianFunction(double x, double sigma)
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{
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ConvolutionMatrix cm = new ConvolutionMatrix();
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cm.SetAll(1);
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cm.Matrix[1, 1] = weight;
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cm.Matrix[1, 0] = cm.Matrix[0, 1] = cm.Matrix[2, 1] = cm.Matrix[1, 2] = 2;
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cm.Factor = weight + 12;
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double left = 1.0 / (Math.Sqrt(2 * Math.PI) * sigma);
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double exponentNumerator = -x * x;
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double exponentDenominator = 2 * Math.Pow(sigma, 2);
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double right = Math.Exp(exponentNumerator / exponentDenominator);
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return left * right;
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}
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public static ConvolutionMatrix GaussianBlur(int height, int width, double sigma)
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{
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ConvolutionMatrix cm = new ConvolutionMatrix(height, width);
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double sum = 0.0;
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double midpointX = (width - 1) / 2.0;
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double midpointY = (height - 1) / 2.0;
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for (int y = 0; y < height; y++)
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{
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for (int x = 0; x < width; x++)
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{
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sum += cm[y, x] = GaussianFunction(x - midpointX, sigma) * GaussianFunction(y - midpointY, sigma);
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}
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}
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// Normalise kernel so that the sum of all weights equals 1
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for (int y = 0; y < height; y++)
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{
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for (int x = 0; x < width; x++)
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{
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cm[y, x] /= sum;
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}
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}
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return cm;
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}
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public static ConvolutionMatrix MeanRemoval(int weight = 9)
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{
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ConvolutionMatrix cm = new ConvolutionMatrix();
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cm.SetAll(-1);
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cm.Matrix[1, 1] = weight;
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cm.Factor = weight - 8;
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double factor = weight - 8;
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cm.SetAll(-1 / factor);
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cm[1, 1] = weight / factor;
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return cm;
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}
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public static ConvolutionMatrix Sharpen(int weight = 11)
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{
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ConvolutionMatrix cm = new ConvolutionMatrix();
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double factor = weight - 8;
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cm.SetAll(0);
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cm.Matrix[1, 1] = weight;
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cm.Matrix[1, 0] = cm.Matrix[0, 1] = cm.Matrix[2, 1] = cm.Matrix[1, 2] = -2;
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cm.Factor = weight - 8;
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cm[1, 1] = weight / factor;
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cm[1, 0] = cm[0, 1] = cm[2, 1] = cm[1, 2] = -2 / factor;
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return cm;
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}
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@ -159,8 +163,8 @@ public static ConvolutionMatrix Emboss()
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{
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ConvolutionMatrix cm = new ConvolutionMatrix();
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cm.SetAll(-1);
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cm.Matrix[1, 1] = 4;
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cm.Matrix[1, 0] = cm.Matrix[0, 1] = cm.Matrix[2, 1] = cm.Matrix[1, 2] = 0;
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cm[1, 1] = 4;
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cm[1, 0] = cm[0, 1] = cm[2, 1] = cm[1, 2] = 0;
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cm.Offset = 127;
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return cm;
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}
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@ -168,9 +172,9 @@ public static ConvolutionMatrix Emboss()
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public static ConvolutionMatrix EdgeDetect()
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{
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ConvolutionMatrix cm = new ConvolutionMatrix();
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cm.Matrix[0, 0] = cm.Matrix[1, 0] = cm.Matrix[2, 0] = -1;
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cm.Matrix[0, 1] = cm.Matrix[1, 1] = cm.Matrix[2, 1] = 0;
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cm.Matrix[0, 2] = cm.Matrix[1, 2] = cm.Matrix[2, 2] = 1;
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cm[0, 0] = cm[0, 1] = cm[0, 2] = -1;
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cm[1, 0] = cm[1, 1] = cm[1, 2] = 0;
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cm[2, 0] = cm[2, 1] = cm[2, 2] = 1;
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cm.Offset = 127;
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return cm;
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}
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@ -149,5 +149,10 @@ public static bool IsEvenNumber(this int num)
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{
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return num % 2 == 0;
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}
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public static void Clamp<T>(ref this T val, T min, T max) where T : struct, IComparable<T>
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{
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MathHelpers.Clamp(ref val, min, max);
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}
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}
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}
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@ -185,5 +185,23 @@ public static Vector2 Lerp(Vector2 pos1, Vector2 pos2, float amount)
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float y = Lerp(pos1.Y, pos2.Y, amount);
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return new Vector2(x, y);
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}
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public static void Clamp<T>(ref T val, T min, T max) where T : IComparable<T>
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{
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if (val.CompareTo(min) < 0)
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{
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val = min;
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}
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else if (val.CompareTo(max) > 0)
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{
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val = max;
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}
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}
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public static T Clamp<T>(T val, T min, T max) where T : IComparable<T>
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{
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Clamp(ref val, min, max);
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return val;
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}
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}
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}
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@ -33,6 +33,7 @@
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<GenerateSerializationAssemblies>Off</GenerateSerializationAssemblies>
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<Prefer32Bit>false</Prefer32Bit>
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<AllowUnsafeBlocks>true</AllowUnsafeBlocks>
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<LangVersion>7.2</LangVersion>
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</PropertyGroup>
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<PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Release|AnyCPU' ">
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<DebugType>none</DebugType>
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|
@ -48,6 +49,7 @@
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<AllowUnsafeBlocks>true</AllowUnsafeBlocks>
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<GenerateSerializationAssemblies>Off</GenerateSerializationAssemblies>
|
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<DebugSymbols>false</DebugSymbols>
|
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<LangVersion>7.2</LangVersion>
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</PropertyGroup>
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<PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'Steam|AnyCPU'">
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<OutputPath>bin\Steam\</OutputPath>
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|
@ -59,6 +61,7 @@
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<ErrorReport>prompt</ErrorReport>
|
||||
<CodeAnalysisRuleSet>MinimumRecommendedRules.ruleset</CodeAnalysisRuleSet>
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<Prefer32Bit>false</Prefer32Bit>
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<LangVersion>7.2</LangVersion>
|
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</PropertyGroup>
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<PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'WindowsStore|AnyCPU'">
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<OutputPath>bin\WindowsStore\</OutputPath>
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||||
|
@ -70,6 +73,7 @@
|
|||
<ErrorReport>prompt</ErrorReport>
|
||||
<CodeAnalysisRuleSet>MinimumRecommendedRules.ruleset</CodeAnalysisRuleSet>
|
||||
<Prefer32Bit>false</Prefer32Bit>
|
||||
<LangVersion>7.2</LangVersion>
|
||||
</PropertyGroup>
|
||||
<PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'WindowsStoreDebug|AnyCPU'">
|
||||
<DebugSymbols>true</DebugSymbols>
|
||||
|
@ -82,6 +86,7 @@
|
|||
<ErrorReport>prompt</ErrorReport>
|
||||
<CodeAnalysisRuleSet>MinimumRecommendedRules.ruleset</CodeAnalysisRuleSet>
|
||||
<Prefer32Bit>false</Prefer32Bit>
|
||||
<LangVersion>7.2</LangVersion>
|
||||
</PropertyGroup>
|
||||
<ItemGroup>
|
||||
<Reference Include="System" />
|
||||
|
|
|
@ -24,6 +24,7 @@ You should have received a copy of the GNU General Public License
|
|||
#endregion License Information (GPL v3)
|
||||
|
||||
using ShareX.HelpersLib;
|
||||
using System;
|
||||
using System.ComponentModel;
|
||||
using System.Drawing;
|
||||
|
||||
|
@ -32,11 +33,50 @@ namespace ShareX.ImageEffectsLib
|
|||
[Description("Gaussian blur")]
|
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internal class GaussianBlur : ImageEffect
|
||||
{
|
||||
private double sigma;
|
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private int size;
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|
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[DefaultValue(0.7955555)]
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public double Sigma
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||||
{
|
||||
get => sigma;
|
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set => sigma = Math.Max(value, 0.1);
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||||
}
|
||||
|
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[DefaultValue(3)]
|
||||
public int Size
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||||
{
|
||||
get => size;
|
||||
set
|
||||
{
|
||||
size = value.Min(1);
|
||||
|
||||
if (size.IsEvenNumber())
|
||||
{
|
||||
size++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public GaussianBlur()
|
||||
{
|
||||
this.ApplyDefaultPropertyValues();
|
||||
}
|
||||
|
||||
public override Image Apply(Image img)
|
||||
{
|
||||
using (img)
|
||||
ConvolutionMatrix kernelHoriz = ConvolutionMatrixManager.GaussianBlur(1, size, sigma);
|
||||
|
||||
ConvolutionMatrix kernelVert = new ConvolutionMatrix(size, 1);
|
||||
for (int i = 0; i < size; i++)
|
||||
{
|
||||
return ConvolutionMatrixManager.GaussianBlur().Apply(img);
|
||||
kernelVert[i, 0] = kernelHoriz[0, i];
|
||||
}
|
||||
|
||||
using (img)
|
||||
using (Image horizPass = kernelHoriz.Apply(img))
|
||||
{
|
||||
return kernelVert.Apply(horizPass);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
@ -53,11 +53,11 @@ internal class MatrixConvolution : ImageEffect
|
|||
[DefaultValue(0)]
|
||||
public int X2Y2 { get; set; }
|
||||
|
||||
[DefaultValue(1)]
|
||||
public int Factor { get; set; }
|
||||
[DefaultValue(1.0)]
|
||||
public double Factor { get; set; }
|
||||
|
||||
[DefaultValue(0)]
|
||||
public int Offset { get; set; }
|
||||
public byte Offset { get; set; }
|
||||
|
||||
public MatrixConvolution()
|
||||
{
|
||||
|
@ -69,16 +69,15 @@ public override Image Apply(Image img)
|
|||
using (img)
|
||||
{
|
||||
ConvolutionMatrix cm = new ConvolutionMatrix();
|
||||
cm.Matrix[0, 0] = X0Y0;
|
||||
cm.Matrix[1, 0] = X1Y0;
|
||||
cm.Matrix[2, 0] = X2Y0;
|
||||
cm.Matrix[0, 1] = X0Y1;
|
||||
cm.Matrix[1, 1] = X1Y1;
|
||||
cm.Matrix[2, 1] = X2Y1;
|
||||
cm.Matrix[0, 2] = X0Y2;
|
||||
cm.Matrix[1, 2] = X1Y2;
|
||||
cm.Matrix[2, 2] = X2Y2;
|
||||
cm.Factor = Factor;
|
||||
cm[0, 0] = X0Y0 / Factor;
|
||||
cm[0, 1] = X1Y0 / Factor;
|
||||
cm[0, 2] = X2Y0 / Factor;
|
||||
cm[1, 0] = X0Y1 / Factor;
|
||||
cm[1, 1] = X1Y1 / Factor;
|
||||
cm[1, 2] = X2Y1 / Factor;
|
||||
cm[2, 0] = X0Y2 / Factor;
|
||||
cm[2, 1] = X1Y2 / Factor;
|
||||
cm[2, 2] = X2Y2 / Factor;
|
||||
cm.Offset = Offset;
|
||||
return cm.Apply(img);
|
||||
}
|
||||
|
|
Loading…
Reference in a new issue