/// <summary>
/// Get the average rgb-values from an image in a given rectangle
/// By default the function calculate the average rgb-values from the whole image
/// </summary>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Img = new ImageData(...);
/// double[] AverageColor = CommonFunctions.AverageRGBValues(img);
/// int left = 0;
/// int top = 5;
/// double[] AverageColorShifted = CommonFunctions.AverageRGBValues(img,left,top);
/// int width = 50;
/// int height = 100;
/// double[] AverageColorRectangle = CommonFunctions.AverageRGBValues(img,left,top,width,height);
/// ]]>
/// </code>
/// </example>
/// <param name="Img">Image</param>
/// <param name="Left">left of rectangle (default=0)</param>
/// <param name="Top">top of rectangle (default=0)</param>
/// <param name="Width">width of rectangle (default=full width)</param>
/// <param name="Height">height of rectangle (default=full height)</param>
/// <returns>averag rgb-values</returns>
static public double[] AverageRGBValues(ImageData Img, int Left = 0, int Top = 0, int Width = -1, int Height = -1)
{
Color CurrentColor;
long[] totals = new long[] { 0, 0, 0 };
if (Width == -1)
{
Width = Img.Width;
}
if (Height == -1)
{
Height = Img.Height;
}
for (int x = Left; x < Left + Width; x++)
{
for (int y = Top; y < Top + Height; y++)
{
CurrentColor = Img.GetPixel(x, y);
totals[0] += CurrentColor.R;
totals[1] += CurrentColor.G;
totals[2] += CurrentColor.B;
}
}
int count = Width * Height;
double[] retvar = new double[] { (totals[0] / (double)count), (totals[1] / (double)count), (totals[2] / (double)count) };
return(retvar);
}
/// <summary>
/// calculate the similarity of image A in a given rectangle and a reference image B
/// </summary>
/// <param name="Img">image A</param>
/// <param name="Reference">image B</param>
/// <param name="Left">offset from left of image A</param>
/// <param name="Top">offset from top of image A</param>
/// <param name="Width">width of rectangle (default: full width)</param>
/// <param name="Height">height of rectangle (default: full height)</param>
/// <returns>similarity (1=exact,0=none)</returns>
static public double Similarity(ImageData Img, ImageData Reference, int Left = 0, int Top = 0, int Width = -1, int Height = -1, int OffsetLeft = 0, int OffsetTop = 0)
{
double sim = 0.0;
Width = (Width == -1) ? Img.Width - Left : Width;
Height = (Height == -1) ? Img.Height - Top : Height;
if ((Img.Width == Reference.Width) && (Img.Height == Reference.Height))
{
for (Int32 column = Left; column < Left + Width; column++)
{
for (Int32 row = Top; row < Top + Height; row++)
{
Color a = Img.GetPixel(OffsetLeft + column, OffsetTop + row);
Color b = Reference.GetPixel(column, row);
int cr = Math.Abs(a.R - b.R);
int cg = Math.Abs(a.G - b.G);
int cb = Math.Abs(a.B - b.B);
sim += (cr + cg + cb) / 3;
}
}
sim /= 255.0;
sim /= (Img.Height * Img.Width);
}
return(1 - sim);
}
/// <summary>
/// Calculates the similarity of image "img" in a given rectangle and a reference image "reference"
/// </summary>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Screenshot = new ImageData(...);
/// ImageData Coin = new ImageData(...);
/// // do magic or using a clipped region of screenshot (500px from left and 100px from top)
/// int left_region = 500;
/// int top_region = 100;
/// double measure = Similarity(Screenshot,Coin,left_region,top_region);
/// ]]>
/// </code>
/// </example>
/// <param name="img">Image A</param>
/// <param name="reference">Image B</param>
/// <param name="left">The offset from left of image A</param>
/// <param name="top">The offset from top of image A</param>
/// <param name="width">The width of the rectangle (default: full width)</param>
/// <param name="height">The height of the rectangle (default: full height)</param>
/// <param name="offsetLeft">The left offset</param>
/// <param name="offsetTop">The top offset</param>
/// <returns>The similarity result (1=exact, 0=none)</returns>
public static double Similarity(ImageData img, ImageData reference, int left = 0, int top = 0, int width = -1,
int height = -1, int offsetLeft = 0, int offsetTop = 0)
{
double sim = 0.0;
width = (width == -1) ? img.Width - left : width;
height = (height == -1) ? img.Height - top : height;
if ((img.Width == reference.Width) && (img.Height == reference.Height))
{
for (Int32 column = left; column < left + width; column++)
{
for (Int32 row = top; row < top + height; row++)
{
Color a = img.GetPixel(offsetLeft + column, offsetTop + row);
Color b = reference.GetPixel(column, row);
int cr = Math.Abs(a.R - b.R);
int cg = Math.Abs(a.G - b.G);
int cb = Math.Abs(a.B - b.B);
sim += (cr + cg + cb) / 3; //TODO: Fix possible loss of fraction
}
}
sim /= 255.0;
sim /= (img.Height * img.Width);
}
return(1 - sim);
}
/// <summary>
/// Get the average rgb-values from an image in a given rectangle
/// By default the function calculate the average rgb-values from the whole image
/// </summary>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Img = new ImageData(...);
/// double[] AverageColor = CommonFunctions.AverageRGBValues(img);
/// int left = 0;
/// int top = 5;
/// double[] AverageColorShifted = CommonFunctions.AverageRGBValues(img,left,top);
/// int width = 50;
/// int height = 100;
/// double[] AverageColorRectangle = CommonFunctions.AverageRGBValues(img,left,top,width,height);
/// ]]>
/// </code>
/// </example>
/// <param name="Img">Image</param>
/// <param name="Left">left of rectangle (default=0)</param>
/// <param name="Top">top of rectangle (default=0)</param>
/// <param name="Width">width of rectangle (default=full width)</param>
/// <param name="Height">height of rectangle (default=full height)</param>
/// <returns>averag rgb-values</returns>
public static double[] AverageRGBValues(ImageData Img, int Left = 0, int Top = 0, int Width = -1, int Height = -1)
{
Color CurrentColor;
long[] totals = new long[] { 0, 0, 0 };
if (Width == -1)
Width = Img.Width;
if(Height==-1)
Height = Img.Height;
for (int x = Left; x < Left + Width; x++)
{
for (int y = Top; y < Top + Height; y++)
{
CurrentColor = Img.GetPixel(x, y);
totals[0] += CurrentColor.R;
totals[1] += CurrentColor.G;
totals[2] += CurrentColor.B;
}
}
int count = Width * Height;
double[] retvar = new double[] { (totals[0] / (double)count), (totals[1] / (double)count), (totals[2] / (double)count) };
return retvar;
}
/// <summary>
/// Gets the average RGB values from a given rectangle in an image
/// By default the average RGB values from the whole image are calculated
/// </summary>
/// <remarks>
/// to detect the color of bubbles or coins this function can be helpful in connection with IdentifyColor()
/// </remarks>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Img = new ImageData(...);
/// // average color in whole image
/// double[] AverageColor = CommonFunctions.AverageRGBValues(img);
/// int left = 0;
/// int top = 5;
/// // average color in clipped image
/// double[] AverageColorShifted = CommonFunctions.AverageRGBValues(img,left,top);
/// int width = 50;
/// int height = 100;
/// // average color in predefined rectangle
/// double[] AverageColorRectangle = CommonFunctions.AverageRGBValues(img,left,top,width,height);
/// ]]>
/// </code>
/// </example>
/// <param name="img">The image to process</param>
/// <param name="left">The left of the rectangle (default=0)</param>
/// <param name="top">The top of the rectangle (default=0)</param>
/// <param name="width">The width of the rectangle (default=full width)</param>
/// <param name="height">The height of the rectangle (default=full height)</param>
/// <returns>The average RGB values</returns>
public static double[] AverageRGBValues(ImageData img, int left = 0, int top = 0, int width = -1,
int height = -1)
{
long[] totals = { 0, 0, 0 };
if (width == -1)
{
width = img.Width;
}
if (height == -1)
{
height = img.Height;
}
for (int x = left; x < left + width; x++)
{
for (int y = top; y < top + height; y++)
{
Color currentColor = img.GetPixel(x, y);
totals[0] += currentColor.R;
totals[1] += currentColor.G;
totals[2] += currentColor.B;
}
}
int count = width * height;
double[] retvar = { (totals[0] / (double)count), (totals[1] / (double)count), (totals[2] / (double)count) };
return(retvar);
}
/// <summary>
/// identify the color of a part(rectangle) from an image by a given list of reference colors (majority vote)
/// </summary>
/// <remarks>
/// this tests every pixel in the given rectangle and majority votes the color from the given dictionary of possible colors
/// </remarks>
/// <param name="Img">image to look in</param>
/// <param name="statReference">list of possible colors</param>
/// <param name="Left">left of rectangle (default: 0)</param>
/// <param name="Top">top of rectangle (default: 0)</param>
/// <param name="Width">width of rectangle (default: full width)</param>
/// <param name="Height">height of rectangle (default: full height)</param>
/// <returns>Color</returns>
static public Color IdentifyColorByVoting(ImageData Img, Dictionary <Color, List <double> > statReference, int Left = 0, int Top = 0, int Width = -1, int Height = -1)
{
double[] av = CommonFunctions.AverageRGBValues(Img, Left, Top, Width, Height);
Color Foo = Color.White;
int[] votes = Enumerable.Repeat(0, statReference.Count).ToArray();
if (Width == -1)
{
Width = Img.Width;
}
if (Height == -1)
{
Height = Img.Height;
}
for (int x = Left; x < Left + Width; x++)
{
for (int y = Top; y < Top + Height; y++)
{
// color from image
Color CurrentColor = Img.GetPixel(x, y);
int best_dist = 255 * 50;
int best_idx = 0;
for (int i = 0; i < statReference.Count; i++)
{
List <double> RGB = statReference.ElementAt(i).Value;
// from from dictionary
Color CCol = Color.FromArgb(Convert.ToInt32(RGB.ElementAt(0)), Convert.ToInt32(RGB.ElementAt(1)), Convert.ToInt32(RGB.ElementAt(2)));
// distance
int current_dist = Math.Abs(CCol.R - CurrentColor.R) + Math.Abs(CCol.G - CurrentColor.G) + Math.Abs(CCol.B - CurrentColor.B);
if (current_dist < best_dist)
{
best_dist = current_dist;
best_idx = i;
}
}
votes[best_idx]++;
}
}
// this is faster than LINQ
int m = -1;
int ans = 0;
for (int i = 0; i < votes.Length; i++)
{
if (votes[i] > m)
{
m = votes[i];
ans = i;
}
}
return(statReference.ElementAt(ans).Key);
}
/// <summary>
/// Identifies the colors of the pixels in a rectangle and compares them with those from an image by a given list of
/// reference colors (majority vote)
/// </summary>
/// <remarks>
/// This tests every pixel in the given rectangle and majority votes the color from the given dictionary of possible
/// colors. Each pixel votes for a color.
///
/// if the image patch is
///
/// " red red "
/// " red blue "
///
/// then 4 pixels vote for similary colors to red and one pixel votes for a similar color to blue
///
/// </remarks>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Screenshot = new ImageData(...);
/// Dictionary<Color, List<double>> Choose = new Dictionary<Color, List<double>> ();
/// Choose.Add(Color.Red, new List<double> { 255, 144.23, 140.89 });
/// Choose.Add(Color.White, new List<double> { 218, 219, 222 });
/// Choose.Add(Color.Blue, new List<double> { 21, 108, 182 });
/// Choose.Add(Color.Green, new List<double> { 86, 191, 50 });
/// Choose.Add(Color.Yellow, new List<double> { 233, 203, 118 });
/// Choose.Add(Color.Orange, new List<double> { 246, 122, 11 });
/// Choose.Add(Color.Black, new List<double> { 94, 98, 98 });
/// Choose.Add(Color.Violet, new List<double> { 223, 80, 195 });
/// Choose.Add(Color.MediumSeaGreen, new List<double> { 106, 227, 216 });
/// // ...
/// Color PieceColor = CommonFunctions.IdentifyColorByVoting(Screenshot,Choose,leftoffset,topoffset,width,height);
/// ]]>
/// </code>
/// </example>
/// <param name="img">The image to look in</param>
/// <param name="statReference">The list of possible colors</param>
/// <param name="left">The left of the rectangle (default: 0)</param>
/// <param name="top">The top of the rectangle (default: 0)</param>
/// <param name="width">The width of the rectangle (default: full width)</param>
/// <param name="height">The height of the rectangle (default: full height)</param>
/// <returns>The best matching color</returns>
public static Color IdentifyColorByVoting(ImageData img, Dictionary <Color, List <double> > statReference,
int left = 0, int top = 0, int width = -1, int height = -1)
{
int[] votes = Enumerable.Repeat(0, statReference.Count).ToArray();
if (width == -1)
{
width = img.Width;
}
if (height == -1)
{
height = img.Height;
}
for (int x = left; x < left + width; x++)
{
for (int y = top; y < top + height; y++)
{
// color from image
Color currentColor = img.GetPixel(x, y);
int bestDist = 255 * 50;
int bestIndex = 0;
for (int i = 0; i < statReference.Count; i++)
{
List <double> RGB = statReference.ElementAt(i).Value;
// from from dictionary
Color cCol = Color.FromArgb(Convert.ToInt32(RGB.ElementAt(0)), Convert.ToInt32(RGB.ElementAt(1)),
Convert.ToInt32(RGB.ElementAt(2)));
// distance
int currentDist = Math.Abs(cCol.R - currentColor.R) + Math.Abs(cCol.G - currentColor.G) +
Math.Abs(cCol.B - currentColor.B);
if (currentDist < bestDist)
{
bestDist = currentDist;
bestIndex = i;
}
}
votes[bestIndex]++;
}
}
// this is faster than LINQ
int m = -1;
int ans = 0;
for (int i = 0; i < votes.Length; i++)
{
if (votes[i] > m)
{
m = votes[i];
ans = i;
}
}
return(statReference.ElementAt(ans).Key);
}
/// <summary>
/// get the red channel as array
/// </summary>
/// <param name="Img">image</param>
/// <returns>array[] of red channel</returns>
static public uint[,] ExtractRedChannel(ImageData Img)
{
uint[,] red = new uint[Img.Width, Img.Height];
for (Int32 column = 0; column < Img.Width; column++)
{
for (Int32 row = 0; row < Img.Height; row++)
{
Color c = Img.GetPixel(column, row);
red[column, row] = c.R;
}
}
return(red);
}
/// <summary>
/// Finds all pixels matching a specified color
/// </summary>
/// <example>
/// <code>
/// <![CDATA[
/// List<Point> WaterPixel = CommonFunctions.FindColors(ScreenShot.create(),Color.Blue,20);
/// ]]>
/// </code>
/// </example>
/// <param name="img">The image to look in</param>
/// <param name="searchColor">The color to look for</param>
/// <param name="tolerance">The tolerance to use</param>
/// <returns></returns>
public static List <Point> FindColors(ImageData img, Color searchColor, uint tolerance)
{
var collection = new List <Point>();
for (int column = 0; column < img.Width; column++)
{
for (int row = 0; row < img.Height; row++)
{
if (ColorsSimilar(img.GetPixel(column, row), searchColor, tolerance))
{
collection.Add(new Point(column, row));
}
}
}
return(collection);
}
/// <summary>
/// find first occurence of color with tolerance
/// </summary>
/// <param name="Img">image to look in</param>
/// <param name="SearchColor">color to look for</param>
/// <param name="Tolerance">tolerance</param>
/// <returns></returns>
static public bool[,] FindColors(ImageData Img, Color SearchColor, uint Tolerance)
{
bool[,] grid = new bool[Img.Width, Img.Height];
for (Int32 column = 0; column < Img.Width; column++)
{
for (Int32 row = 0; row < Img.Height; row++)
{
if (CommonFunctions.ColorsSimilar(Img.GetPixel(column, row), SearchColor, Tolerance))
{
grid[column, row] = true;
}
else
{
grid[column, row] = false;
}
}
}
return(grid);
}
/// <summary>
/// Finds all pixels matching a specified color
/// /accelerated/
/// </summary>
/// <remarks>
/// this function skips in both dimension (x and y) a predefined amount of pixels in each iteration.
/// You can use this function to test every n-th pixel
/// </remarks>
/// <param name="img">The image to look in</param>
/// <param name="searchColor">The color to look for</param>
/// <param name="skipX">The X pixels to skip each time</param>
/// <param name="skipY">The Y pixels to skip each time</param>
/// <param name="tolerance">The tolerance to use</param>
/// <returns></returns>
public static List <Point> FindColors(ImageData img, Color searchColor, uint tolerance, int skipX = 1, int skipY = 1)
{
if (skipX < 1 && skipY < 1)
{
return(null); // Cannot be non-positive numbers
}
var collection = new List <Point>();
for (int column = 0; column < img.Width; column = column + skipX)
{
for (int row = 0; row < img.Height; row = row + skipY)
{
if (ColorsSimilar(img.GetPixel(column, row), searchColor, tolerance))
{
collection.Add(new Point(column, row));
}
}
}
return(collection);
}
/// <summary>
/// Gets the average RGB values from a given rectangle in an image
/// By default the average RGB values from the whole image are calculated
/// </summary>
/// <remarks>
/// to detect the color of bubbles or coins this function can be helpful in connection with IdentifyColor()
/// </remarks>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Img = new ImageData(...);
/// // average color in whole image
/// double[] AverageColor = CommonFunctions.AverageRGBValues(img);
/// int left = 0;
/// int top = 5;
/// // average color in clipped image
/// double[] AverageColorShifted = CommonFunctions.AverageRGBValues(img,left,top);
/// int width = 50;
/// int height = 100;
/// // average color in predefined rectangle
/// double[] AverageColorRectangle = CommonFunctions.AverageRGBValues(img,left,top,width,height);
/// ]]>
/// </code>
/// </example>
/// <param name="img">The image to process</param>
/// <param name="left">The left of the rectangle (default=0)</param>
/// <param name="top">The top of the rectangle (default=0)</param>
/// <param name="width">The width of the rectangle (default=full width)</param>
/// <param name="height">The height of the rectangle (default=full height)</param>
/// <returns>The average RGB values</returns>
public static double[] AverageRGBValues(ImageData img, int left = 0, int top = 0, int width = -1,
int height = -1)
{
long[] totals = {0, 0, 0};
if (width == -1)
width = img.Width;
if (height == -1)
height = img.Height;
for (int x = left; x < left + width; x++)
{
for (int y = top; y < top + height; y++)
{
Color currentColor = img.GetPixel(x, y);
totals[0] += currentColor.R;
totals[1] += currentColor.G;
totals[2] += currentColor.B;
}
}
int count = width*height;
double[] retvar = {(totals[0]/(double) count), (totals[1]/(double) count), (totals[2]/(double) count)};
return retvar;
}
/// <summary>
/// Calculates the similarity of image "img" in a given rectangle and a reference image "reference"
/// </summary>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Screenshot = new ImageData(...);
/// ImageData Coin = new ImageData(...);
/// // do magic or using a clipped region of screenshot (500px from left and 100px from top)
/// int left_region = 500;
/// int top_region = 100;
/// double measure = Similarity(Screenshot,Coin,left_region,top_region);
/// ]]>
/// </code>
/// </example>
/// <param name="img">Image A</param>
/// <param name="reference">Image B</param>
/// <param name="left">The offset from left of image A</param>
/// <param name="top">The offset from top of image A</param>
/// <param name="width">The width of the rectangle (default: full width)</param>
/// <param name="height">The height of the rectangle (default: full height)</param>
/// <param name="offsetLeft">The left offset</param>
/// <param name="offsetTop">The top offset</param>
/// <returns>The similarity result (1=exact, 0=none)</returns>
public static double Similarity(ImageData img, ImageData reference, int left = 0, int top = 0, int width = -1,
int height = -1, int offsetLeft = 0, int offsetTop = 0)
{
double sim = 0.0;
width = (width == -1) ? img.Width - left : width;
height = (height == -1) ? img.Height - top : height;
if ((img.Width == reference.Width) && (img.Height == reference.Height))
{
for (Int32 column = left; column < left + width; column++)
{
for (Int32 row = top; row < top + height; row++)
{
Color a = img.GetPixel(offsetLeft + column, offsetTop + row);
Color b = reference.GetPixel(column, row);
int cr = Math.Abs(a.R - b.R);
int cg = Math.Abs(a.G - b.G);
int cb = Math.Abs(a.B - b.B);
sim += (cr + cg + cb)/3; //TODO: Fix possible loss of fraction
}
}
sim /= 255.0;
sim /= (img.Height*img.Width);
}
return 1 - sim;
}
/// <summary>
/// Get the pattern of the magics match sticks
/// </summary>
/// <param name="Image">image of character</param>
/// <returns>pattern</returns>
public float[] GetMagicMatchSticksState(ImageData Image)
{
int Width = Image.Width; // width of image
int Height = Image.Height; // height of image
int n = Num(); // num of magicsticks
float[] Pattern = new float[n]; // state
int lastx = -1, lasty = -1;
int tmpx = -1, tmpy = -1;
for (int i = 0; i < n; i++)
{
Pattern[i] = 0.0f;
}
for (int y = 0; y < Height; y++)
{
for (int x = 0; x < Width; x++)
{
// is the pixel black?
if (Image.GetPixel(x, y).R == 0)
{
tmpx = Convert.ToInt16(x * 100 / Width);
tmpy = Convert.ToInt16(y * 100 / Height);
if ((tmpx != lastx) || (tmpy != lasty))
{
lastx = tmpx;
lasty = tmpy;
for (int i = 0; i < n; i++)
{
// skip already activated receptors
if (Pattern[i] == 1.0f)
continue;
if (MagicStickList[i].GetMagicMatchStickState(tmpx, tmpy))
Pattern[i] = 1.0f;
}
}
}
}
}
return Pattern;
}
/// <summary>
/// Finds all pixels matching a specified color
/// /accelerated/
/// </summary>
/// <remarks>
/// this function skips in both dimension (x and y) a predefined amount of pixels in each iteration.
/// You can use this function to test every n-th pixel
/// </remarks>
/// <param name="img">The image to look in</param>
/// <param name="searchColor">The color to look for</param>
/// <param name="skipX">The X pixels to skip each time</param>
/// <param name="skipY">The Y pixels to skip each time</param>
/// <param name="tolerance">The tolerance to use</param>
/// <returns></returns>
public static List<Point> FindColors(ImageData img, Color searchColor, uint tolerance, int skipX = 1, int skipY = 1)
{
if (skipX < 1 && skipY < 1) return null; // Cannot be non-positive numbers
var collection = new List<Point>();
for (int column = 0; column < img.Width; column = column + skipX)
{
for (int row = 0; row < img.Height; row = row + skipY)
{
if (ColorsSimilar(img.GetPixel(column, row), searchColor, tolerance))
{
collection.Add(new Point(column, row));
}
}
}
return collection;
}
/// <summary>
/// Identifies the colors of the pixels in a rectangle and compares them with those from an image by a given list of
/// reference colors (majority vote)
/// </summary>
/// <remarks>
/// This tests every pixel in the given rectangle and majority votes the color from the given dictionary of possible
/// colors. Each pixel votes for a color.
///
/// if the image patch is
///
/// " red red "
/// " red blue "
///
/// then 4 pixels vote for similary colors to red and one pixel votes for a similar color to blue
///
/// </remarks>
/// <example>
/// <code>
/// <![CDATA[
/// ImageData Screenshot = new ImageData(...);
/// Dictionary<Color, List<double>> Choose = new Dictionary<Color, List<double>> ();
/// Choose.Add(Color.Red, new List<double> { 255, 144.23, 140.89 });
/// Choose.Add(Color.White, new List<double> { 218, 219, 222 });
/// Choose.Add(Color.Blue, new List<double> { 21, 108, 182 });
/// Choose.Add(Color.Green, new List<double> { 86, 191, 50 });
/// Choose.Add(Color.Yellow, new List<double> { 233, 203, 118 });
/// Choose.Add(Color.Orange, new List<double> { 246, 122, 11 });
/// Choose.Add(Color.Black, new List<double> { 94, 98, 98 });
/// Choose.Add(Color.Violet, new List<double> { 223, 80, 195 });
/// Choose.Add(Color.MediumSeaGreen, new List<double> { 106, 227, 216 });
/// // ...
/// Color PieceColor = CommonFunctions.IdentifyColorByVoting(Screenshot,Choose,leftoffset,topoffset,width,height);
/// ]]>
/// </code>
/// </example>
/// <param name="img">The image to look in</param>
/// <param name="statReference">The list of possible colors</param>
/// <param name="left">The left of the rectangle (default: 0)</param>
/// <param name="top">The top of the rectangle (default: 0)</param>
/// <param name="width">The width of the rectangle (default: full width)</param>
/// <param name="height">The height of the rectangle (default: full height)</param>
/// <returns>The best matching color</returns>
public static Color IdentifyColorByVoting(ImageData img, Dictionary<Color, List<double>> statReference,
int left = 0, int top = 0, int width = -1, int height = -1)
{
int[] votes = Enumerable.Repeat(0, statReference.Count).ToArray();
if (width == -1)
width = img.Width;
if (height == -1)
height = img.Height;
for (int x = left; x < left + width; x++)
{
for (int y = top; y < top + height; y++)
{
// color from image
Color currentColor = img.GetPixel(x, y);
int bestDist = 255*50;
int bestIndex = 0;
for (int i = 0; i < statReference.Count; i++)
{
List<double> RGB = statReference.ElementAt(i).Value;
// from from dictionary
Color cCol = Color.FromArgb(Convert.ToInt32(RGB.ElementAt(0)), Convert.ToInt32(RGB.ElementAt(1)),
Convert.ToInt32(RGB.ElementAt(2)));
// distance
int currentDist = Math.Abs(cCol.R - currentColor.R) + Math.Abs(cCol.G - currentColor.G) +
Math.Abs(cCol.B - currentColor.B);
if (currentDist < bestDist)
{
bestDist = currentDist;
bestIndex = i;
}
}
votes[bestIndex]++;
}
}
// this is faster than LINQ
int m = -1;
int ans = 0;
for (int i = 0; i < votes.Length; i++)
{
if (votes[i] > m)
{
m = votes[i];
ans = i;
}
}
return statReference.ElementAt(ans).Key;
}
/// <summary>
/// Finds all pixels matching a specified color
/// </summary>
/// <example>
/// <code>
/// <![CDATA[
/// List<Point> WaterPixel = CommonFunctions.FindColors(ScreenShot.create(),Color.Blue,20);
/// ]]>
/// </code>
/// </example>
/// <param name="img">The image to look in</param>
/// <param name="searchColor">The color to look for</param>
/// <param name="tolerance">The tolerance to use</param>
/// <returns></returns>
public static List<Point> FindColors(ImageData img, Color searchColor, uint tolerance)
{
var collection = new List<Point>();
for (int column = 0; column < img.Width; column++)
{
for (int row = 0; row < img.Height; row++)
{
if (ColorsSimilar(img.GetPixel(column, row), searchColor, tolerance))
{
collection.Add(new Point(column, row));
}
}
}
return collection;
}
/// <summary>
/// Retrieves the red channel as an array
/// </summary>
/// <param name="img">image</param>
/// <returns>The red channel as an array</returns>
public static uint[,] ExtractRedChannel(ImageData img)
{
var red = new uint[img.Width, img.Height];
for (Int32 column = 0; column < img.Width; column++)
{
for (Int32 row = 0; row < img.Height; row++)
{
Color c = img.GetPixel(column, row);
red[column, row] = c.R;
}
}
return red;
}
/// <summary>
/// find first occurence of color with tolerance
/// </summary>
/// <param name="Img">image to look in</param>
/// <param name="SearchColor">color to look for</param>
/// <param name="Tolerance">tolerance</param>
/// <returns></returns>
public static bool[,] FindColors(ImageData Img, Color SearchColor, uint Tolerance)
{
bool[,] grid = new bool[Img.Width, Img.Height];
for (Int32 column = 0; column < Img.Width; column++)
{
for (Int32 row = 0; row < Img.Height; row++)
{
if (CommonFunctions.ColorsSimilar(Img.GetPixel(column, row), SearchColor, Tolerance))
{
grid[column, row] = true;
}
else
{
grid[column, row] = false;
}
}
}
return grid;
}
/// <summary>
/// calculate the similarity of image A in a given rectangle and a reference image B
/// </summary>
/// <param name="Img">image A</param>
/// <param name="Reference">image B</param>
/// <param name="Left">offset from left of image A</param>
/// <param name="Top">offset from top of image A</param>
/// <param name="Width">width of rectangle (default: full width)</param>
/// <param name="Height">height of rectangle (default: full height)</param>
/// <returns>similarity (1=exact,0=none)</returns>
public static double Similarity(ImageData Img, ImageData Reference, int Left = 0, int Top = 0, int Width = -1, int Height = -1, int OffsetLeft = 0, int OffsetTop = 0)
{
double sim = 0.0;
Width = (Width == -1) ? Img.Width - Left : Width;
Height = (Height == -1) ? Img.Height - Top : Height;
if ((Img.Width == Reference.Width) && (Img.Height == Reference.Height))
{
for (Int32 column = Left; column < Left + Width; column++)
{
for (Int32 row = Top; row < Top + Height; row++)
{
Color a = Img.GetPixel(OffsetLeft + column, OffsetTop + row);
Color b = Reference.GetPixel(column, row);
int cr = Math.Abs(a.R - b.R);
int cg = Math.Abs(a.G - b.G);
int cb = Math.Abs(a.B - b.B);
sim += (cr + cg + cb) / 3;
}
}
sim /= 255.0;
sim /= (Img.Height * Img.Width);
}
return 1 - sim;
}
/// <summary>
/// identify the color of a part(rectangle) from an image by a given list of reference colors (majority vote)
/// </summary>
/// <remarks>
/// this tests every pixel in the given rectangle and majority votes the color from the given dictionary of possible colors
/// </remarks>
/// <param name="Img">image to look in</param>
/// <param name="statReference">list of possible colors</param>
/// <param name="Left">left of rectangle (default: 0)</param>
/// <param name="Top">top of rectangle (default: 0)</param>
/// <param name="Width">width of rectangle (default: full width)</param>
/// <param name="Height">height of rectangle (default: full height)</param>
/// <returns>Color</returns>
public static Color IdentifyColorByVoting(ImageData Img, Dictionary<Color, List<double>> statReference, int Left = 0, int Top = 0, int Width = -1, int Height = -1)
{
double[] av = CommonFunctions.AverageRGBValues(Img, Left, Top, Width, Height);
Color Foo = Color.White;
int[] votes = Enumerable.Repeat(0, statReference.Count).ToArray();
if (Width == -1)
Width = Img.Width;
if (Height == -1)
Height = Img.Height;
for (int x = Left; x < Left + Width; x++)
{
for (int y = Top; y < Top + Height; y++)
{
// color from image
Color CurrentColor = Img.GetPixel(x, y);
int best_dist = 255*50;
int best_idx = 0;
for (int i = 0; i < statReference.Count;i++ )
{
List<double> RGB = statReference.ElementAt(i).Value;
// from from dictionary
Color CCol = Color.FromArgb(Convert.ToInt32(RGB.ElementAt(0)), Convert.ToInt32(RGB.ElementAt(1)), Convert.ToInt32(RGB.ElementAt(2)));
// distance
int current_dist = Math.Abs(CCol.R - CurrentColor.R) + Math.Abs(CCol.G - CurrentColor.G) + Math.Abs(CCol.B - CurrentColor.B);
if (current_dist < best_dist)
{
best_dist = current_dist;
best_idx = i;
}
}
votes[best_idx]++;
}
}
// this is faster than LINQ
int m=-1;
int ans = 0;
for (int i=0;i<votes.Length;i++)
{
if(votes[i]>m){
m=votes[i];
ans=i;
}
}
return statReference.ElementAt(ans).Key;
}
