public static void Sum_Avx(NativeImage <float> img1, NativeImage <float> img2, NativeImage <float> res)
{
var w8 = res.Width / 8 * 8;
for (var j = 0; j < res.Height; j++)
{
var p1 = img1.PixelAddr(0, j);
var p2 = img2.PixelAddr(0, j);
var r = res.PixelAddr(0, j);
for (var i = 0; i < w8; i += 8)
{
Avx.StoreAligned(r, Avx.Add(Avx.LoadAlignedVector256(p1), Avx.LoadAlignedVector256(p2)));
p1 += 8;
p2 += 8;
r += 8;
}
for (var i = w8; i < res.Width; i++)
{
*r++ = *p1++ + *p2++;
}
}
}
public static void Sum_RefMethod(NativeImage <float> img1, NativeImage <float> img2, NativeImage <float> res)
{
for (var j = 0; j < res.Height; j++)
{
for (var i = 0; i < res.Width; i++)
{
res.Pixel(i, j) = img1.Pixel(i, j) + img2.Pixel(i, j);
}
}
}
public static void Sum_GetSetMethods(NativeImage <float> img1, NativeImage <float> img2, NativeImage <float> res)
{
for (var j = 0; j < res.Height; j++)
{
for (var i = 0; i < res.Width; i++)
{
res.SetUnsafe(i, j, img1.GetUnsafe(i, j) + img2.GetUnsafe(i, j));
}
}
}
public static void Sum_ThisProperty(NativeImage <float> img1, NativeImage <float> img2, NativeImage <float> res)
{
for (var j = 0; j < res.Height; j++)
{
for (var i = 0; i < res.Width; i++)
{
res[i, j] = img1[i, j] + img2[i, j];
}
}
}
public Median(NativeImage <float> src, int rad, NativeImage <float> res)
{
this.src = src;
this.rad = rad;
this.res = res;
diam = 2 * rad + 1;
N = diam * diam;
arr = new float[N];
w1 = src.Width - 1;
h1 = src.Height - 1;
}
public Convolution(NativeImage <float> img, NativeImage <float> kernel, NativeImage <float> res)
{
this.img = img;
this.kernel = kernel;
this.res = res;
ofsx = kernel.Width / 2;
ofsy = kernel.Height / 2;
kw1 = kernel.Width - 1;
kh1 = kernel.Height - 1;
iw1 = img.Width - 1;
ih1 = img.Height - 1;
}
public static void Rotate180(NativeImage <float> src, NativeImage <float> dst)
{
var w = src.Width - 1;
var h = src.Height - 1;
for (var j = 0; j <= h; j++)
{
for (var i = 0; i <= w; i++)
{
dst[w - i, h - j] = src[i, j];
}
}
}
public static void Rotate180_Optimized(NativeImage <float> src, NativeImage <float> dst)
{
var w = src.Width;
for (var j = 0; j < src.Height; j++)
{
var s = src.PixelAddr(0, j);
var d = dst.PixelAddr(src.Width, j);
for (var i = 0; i < w; i++)
{
*--d = *s++;
}
}
}
public void TestConvolve()
{
var img = Shape(3, 4, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f);
var kernel = Shape(2, 3, 1.0f, 0.0f, 0.0f, 2.0f, 3.0f, 1.0f);
var expected = Shape(3, 4, 10.0f, 14.0f, 21.0f, 19.0f, 23.0f, 30.0f, 40.0f, 44.0f, 51.0f, 58.0f, 62.0f, 69.0f);
var res = new NativeImage <float>(3, 4);
ImageOperations.Convolve(img, kernel, res);
Assert.True(BitmapEquals(res, expected));
ImageOperations.Convolve_Optimized(img, kernel, res);
Assert.True(BitmapEquals(res, expected));
ImageOperations.Convolve_Avx(img, kernel, res);
Assert.True(BitmapEquals(res, expected));
}
static NativeImage <T> Shape <T>(int w, int h, params T[] data)
where T : unmanaged
{
var res = new NativeImage <T>(w, h);
for (int j = 0; j < h; j++)
{
for (int i = 0; i < w; i++)
{
var k = j * w + i;
res[i, j] = k < data.Length ? data[k] : default;
}
}
return(res);
}
public static void Sum_Optimized(NativeImage <float> img1, NativeImage <float> img2, NativeImage <float> res)
{
var w = res.Width;
for (var j = 0; j < res.Height; j++)
{
var p1 = img1.PixelAddr(0, j);
var p2 = img2.PixelAddr(0, j);
var r = res.PixelAddr(0, j);
for (var i = 0; i < w; i++)
{
r[i] = p1[i] + p2[i];
}
}
}
static bool BitmapEquals <T>(NativeImage <T> img1, NativeImage <T> img2)
where T : unmanaged
{
if (img1.Width != img2.Width || img1.Height != img2.Height)
{
return(false);
}
for (int j = 0; j < img1.Height; j++)
{
for (int i = 0; i < img1.Width; i++)
{
if (!EqualityComparer <T> .Default.Equals(img1[i, j], img2[i, j]))
{
return(false);
}
}
}
return(true);
}
public void TestSum()
{
var img1 = Shape(2, 3, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f);
var img2 = Shape(2, 3, 2.0f, 4.0f, 1.0f, 5.0f, 3.0f, 7.0f);
var img3 = Shape(2, 3, 3.0f, 6.0f, 4.0f, 9.0f, 8.0f, 13.0f);
var res = new NativeImage <float>(2, 3);
ImageOperations.Sum_GetSetMethods(img1, img2, res);
Assert.True(BitmapEquals(img3, res));
ImageOperations.Sum_RefMethod(img1, img2, res);
Assert.True(BitmapEquals(img3, res));
ImageOperations.Sum_ThisProperty(img1, img2, res);
Assert.True(BitmapEquals(img3, res));
ImageOperations.Sum_Avx(img1, img2, res);
Assert.True(BitmapEquals(img3, res));
ImageOperations.Sum_Optimized(img1, img2, res);
Assert.True(BitmapEquals(img3, res));
}
public static void Rotate180_Avx(NativeImage <float> src, NativeImage <float> dst)
{
var w8 = src.Width / 8 * 8;
for (var j = 0; j < src.Height; j++)
{
var s = src.PixelAddr(0, j);
var d = dst.PixelAddr(src.Width, j);
for (var i = 0; i < w8; i += 8)
{
var v = Avx.Permute(Avx.LoadAlignedVector256(s), 0x1b);
s += 8;
d -= 8;
Avx.Store(d, Avx.Permute2x128(v, v, 1));
}
for (var i = w8; i < src.Width; i++)
{
*--d = *s++;
}
}
}
public Benchmarks()
{
img1 = new NativeImage <float>(size, size);
img2 = new NativeImage <float>(size, size);
kernel = new NativeImage <float>(7, 7);
res = new NativeImage <float>(size, size);
for (var j = 0; j < res.Height; j++)
{
for (var i = 0; i < res.Width; i++)
{
img1[i, j] = 1.0f;
img2[i, j] = 2.0f;
}
}
for (var j = 0; j < kernel.Height; j++)
{
for (var i = 0; i < kernel.Width; i++)
{
kernel[i, j] = 1.0f;
}
}
}
public static void MedianFilter(NativeImage <float> src, int rad, NativeImage <float> res)
{
new Median(src, rad, res).Perform();
}
public static void Convolve_AvxIsolated(NativeImage <float> img, NativeImage <float> kernel, NativeImage <float> res)
{
using var tmp = new NativeImage <float>(kernel.Width, kernel.Height);
Rotate180(kernel, tmp);
new Convolution(img, tmp, res).PerformVectorIsolated();
}
