public void Test_ValidateImage_Correct()
{
var input = new double[, , ]
{
{
{ 1, 2, 3 },
{ 4, 5, 6 },
{ 7, 8, 9 }
},
{
{ 1, 2, 3 },
{ 4, 5, 6 },
{ 7, 8, 9 }
},
{
{ 1, 2, 3 },
{ 4, 5, 6 },
{ 7, 8, 9 }
}
};
var filter = new double[, , ]
{
{
{ 1.1, 1.2, 1.3 },
{ 1.4, 1.5, 1.6 }
},
{
{ 1.1, 1.2, 1.3 },
{ 1.4, 1.5, 1.6 }
}
};
var filter2 = new double[, , ]
{
{
{ 2.1, 2.2, 2.3 },
{ 2.4, 2.5, 2.6 }
},
{
{ 2.1, 2.2, 2.3 },
{ 2.4, 2.5, 2.6 }
}
};
var layer = new ConvolutionalLayer();
layer.Neurals.Add(new Filter {
Weights = new Array3D(filter)
});
layer.Neurals.Add(new Filter {
Weights = new Array3D(filter2)
});
layer.FormOutput(new Array3D(input));
}
public void Test_FormOutput_Correct()
{
var inputArray = new double[, , ]
{
{
{ 1, 3, 5, 8, 7, 4, 2, 8, 6 },
{ 4, 2, 3, 5, 1, 0, 1, 2, 7 },
{ 8, 3, 1, 2, 3, 6, 5, 8, 5 },
{ 7, 2, 4, 2, 9, 3, 6, 4, 6 },
{ 9, 8, 0, 8, 8, 3, 7, 1, 0 },
{ 9, 4, 1, 2, 2, 4, 7, 4, 3 },
{ 0, 5, 9, 1, 6, 4, 5, 4, 3 },
{ 3, 0, 5, 8, 6, 5, 7, 0, 1 },
{ 1, 4, 2, 3, 6, 1, 5, 4, 3 }
},
{
{ 4, 3, 5, 0, 1, 2, 4, 8, 9 },
{ 4, 8, 0, 1, 3, 4, 5, 6, 7 },
{ 4, 4, 2, 3, 6, 5, 4, 2, 1 },
{ 0, 7, 8, 6, 4, 4, 1, 0, 0 },
{ 1, 0, 1, 2, 4, 5, 6, 2, 3 },
{ 1, 2, 3, 7, 8, 8, 7, 4, 6 },
{ 0, 3, 3, 2, 1, 7, 2, 3, 0 },
{ 1, 8, 4, 4, 1, 2, 0, 0, 5 },
{ 7, 9, 9, 9, 1, 3, 1, 4, 6 }
},
{
{ 7, 1, 4, 3, 2, 1, 0, 4, 6 },
{ 5, 3, 1, 9, 7, 5, 3, 1, 1 },
{ 4, 2, 0, 8, 6, 4, 2, 0, 0 },
{ 7, 8, 7, 4, 3, 8, 0, 1, 4 },
{ 5, 2, 1, 3, 6, 5, 4, 7, 5 },
{ 1, 6, 2, 4, 2, 3, 7, 6, 1 },
{ 0, 3, 7, 1, 3, 0, 3, 1, 8 },
{ 6, 4, 8, 8, 9, 0, 1, 2, 1 },
{ 5, 6, 7, 8, 9, 0, 2, 4, 7 }
}
};
var filterFirstArray = new double[, , ]
{
{
{ 1, 4, 5 },
{ 0, 3, 4 },
{ 6, 8, 7 }
},
{
{ 4, 1, 0 },
{ 6, 3, 1 },
{ 5, 4, 2 }
},
{
{ 2, 2, 5 },
{ 3, 7, 4 },
{ 4, 1, 0 }
}
};
var filterSecondArray = new double[, , ]
{
{
{ 4, 7, 1 },
{ 3, 0, 2 },
{ 4, 2, 1 }
},
{
{ 3, 2, 2 },
{ 8, 3, 4 },
{ 7, 7, 1 }
},
{
{ 2, 3, 0 },
{ 4, 0, 7 },
{ 1, 5, 4 }
}
};
var expectedArray = new double[, , ]
{
{
{ 336, 320, 339, 402 },
{ 360, 402, 448, 266 },
{ 272, 377, 444, 353 },
{ 408, 486, 299, 253 }
},
{
{ 287, 312, 334, 336 },
{ 330, 335, 379, 317 },
{ 272, 300, 424, 352 },
{ 410, 481, 250, 248 }
}
};
var input = Converters.Convert(inputArray);
var filterFirst = Converters.Convert(filterFirstArray);
var filterSecond = Converters.Convert(filterSecondArray);
var expected = Converters.Convert(expectedArray);
var layer = new ConvolutionalLayer()
{
Stride = 2
};
layer.ActivationFunction = new ConstActivationFunction();
layer.Neurals.Add(new Filter {
Weights = filterFirst
});
layer.Neurals.Add(new Filter {
Weights = filterSecond
});
var result = layer.FormOutput(input) as Array3D;
for (var i = 0; i < expected.Height; i++)
{
for (var j = 0; j < expected.Width; j++)
{
for (var k = 0; k < expected.Depth; k++)
{
Assert.AreEqual(expected[i, j, k], result[i, j, k]);
}
}
}
}
/// <summary>
///
/// </summary>
/// <param name="originImage"></param>
/// <param name="mask1"></param>
/// <param name="mask2"></param>
/// <param name="filteredImage">Full path to store applyed filter image</param>
private void ApplyFilter(string originImage, double [,,] mask1, double [,,] mask2, string filteredImage)
{
Bitmap bitmap = new Bitmap(originImage);
var image = new Array3D(bitmap.Height, bitmap.Width, 3);
for (var i = 0; i < bitmap.Height; i++)
{
for (var j = 0; j < bitmap.Width; j++)
{
var pixel = bitmap.GetPixel(j, i);
image[i, j, 0] = pixel.R;
image[i, j, 1] = pixel.G;
image[i, j, 2] = pixel.B;
}
}
var filter = new ConvolutionalLayer
{
ActivationFunction = new ConstActivationFunction()
};
filter.Neurals.Add(new Filter {
Weights = Converters.Convert(mask1)
});
filter.Neurals.Add(new Filter {
Weights = Converters.Convert(mask2)
});
var output = filter.FormOutput(image) as Array3D;
var g1 = output.ExtractLayer(0);
var g2 = output.ExtractLayer(1);
var resultArray = new double[g1.Height, g1.Width];
for (var i = 0; i < g1.Height; i++)
{
for (var j = 0; j < g1.Width; j++)
{
resultArray[i, j] = Math.Sqrt(Math.Pow(g1[i, j], 2) + Math.Pow(g2[i, j], 2));
}
}
var imageBuffer = new byte[g1.Width * g1.Height * 4];
var indexBytes = 0;
for (var i = 0; i < g1.Height; i++)
{
for (var j = 0; j < g1.Width; j++)
{
imageBuffer[indexBytes++] = (byte)resultArray[i, j];
imageBuffer[indexBytes++] = 0;
imageBuffer[indexBytes++] = 0;
imageBuffer[indexBytes++] = 255;
}
}
unsafe
{
fixed(byte *ptr = imageBuffer)
{
using (Bitmap outImage = new Bitmap(g1.Width, g1.Height, g1.Width * 4, PixelFormat.Format32bppPArgb,
new IntPtr(ptr)))
{
outImage.Save(filteredImage);
}
}
}
}
