public static GridHierarchy CreateFromPixels(PixelData pixels)
{
GridHierarchy result = new GridHierarchy(pixels.Width, pixels.Height, 1);
for (var i = 0; i <= pixels.Width - 1; i++)
{
for (var j = 0; j <= pixels.Height - 1; j++)
{
Cluster cluster = new Cluster()
{
Position = new Vector2(i, j),
Color = pixels.Colors[i, j]
};
result.Grid[i, j].Add(cluster);
result.Clusters.Add(cluster);
}
}
foreach (var cluster in result.Clusters)
{
var neighbours = result.GetNeighbours(cluster);
var colorDirection = VectorHelper.GetAveragePosition(neighbours.Select(v => v.ColorVector - cluster.ColorVector));
cluster.ColorDirection = colorDirection;
}
return(result);
}
public ClusteringAI(PixelData pixels, int maxRank = 10)
{
DateTime start = DateTime.Now;
Debug.WriteLine("Initialize Start");
Hierarchies.Add(GridHierarchy.CreateFromPixels(pixels));
Debug.WriteLine($"Initialize Over,TimeConsuming:{DateTime.Now - start}");
Debug.WriteLine($"Generation Start");
for (var i = 0; i <= maxRank - 1; i++)
{
start = DateTime.Now;
Hierarchies.Add(Hierarchies.Last().Generate());
Debug.WriteLine($"Total:{maxRank},Current:{i + 1},Time Consuming:{DateTime.Now - start},Hierarchy[{Hierarchies.Last()}]");
}
Debug.WriteLine(pixels.Colors.Length);
// Paint lines
Lines.AddRange(GenerateLines(Hierarchies[9].Clusters.ToList()));
// Paint pixels
foreach (var item in Hierarchies[8].Clusters)
{
BuildResult2(Lines, item);
}
}
public ClusteringAI(PixelData pixels, int maxRank = 10)
{
DateTime start = DateTime.Now;
Debug.WriteLine("Initialize Start");
Hierarchies.Add(GridHierarchy.CreateFromPixels(pixels));
Debug.WriteLine($"Initialize Over,TimeConsuming:{DateTime.Now - start}");
Debug.WriteLine($"Generation Start");
for (var i = 0; i <= maxRank - 1; i++)
{
start = DateTime.Now;
Hierarchies.Add(Hierarchies.Last().Generate());
Debug.WriteLine($"Total:{maxRank},Current:{i + 1},Time Consuming:{DateTime.Now - start},Hierarchy[{Hierarchies.Last()}]");
}
Debug.WriteLine(pixels.Colors.Length);
int mid = 4;
for (var i = maxRank - 1; i >= mid; i += -2)
{
//Lines.AddRange(GenerateOutlines(Hierarchies[i]));
Lines.AddRange(GenerateLines(Hierarchies[i]));
}
//var index = 8;
//Lines.AddRange(GenerateLines(Hierarchies[index]));
//Lines.AddRange(DeepGenerateLines(Hierarchies[mid].Clusters, Hierarchies[mid].Rank));
}
public override IHierarchy Generate()
{
float rate = 2.0F;
float newSize = this.Size * rate;
GridHierarchy result = new GridHierarchy(System.Convert.ToInt32(Math.Ceiling(this.Width / (double)rate) + 1), System.Convert.ToInt32(Math.Ceiling(this.Height / (double)rate) + 1), newSize)
{
Rank = this.Rank + 1
};
// Combine to a new cluster
foreach (var cluster in Clusters)
{
Cluster similar = cluster.GetMostSimilar(GetNeighbours(cluster)).FirstOrDefault();
if (similar != null)
{
if (cluster.Parent == null && similar.Parent == null)
{
result.Clusters.Add(Cluster.Combine(cluster, similar));
}
else
{
Cluster.Combine(cluster, similar);
}
}
else
{
result.Clusters.Add(cluster);
}
}
// Initialize properties
foreach (var cluster in result.Clusters)
{
cluster.Position = cluster.GetAveragePosition();
cluster.Color = cluster.GetAverageColor();
//cluster.ColorDirection = cluster.GetAverageColorDirection();
}
// Locate to cell
foreach (var SubCluster in result.Clusters)
{
Vector2 p = SubCluster.Position;
int x = System.Convert.ToInt32(p.X / (double)result.Size);
int y = System.Convert.ToInt32(p.Y / (double)result.Size);
result.Grid[x, y].Add(SubCluster);
}
foreach (var cluster in result.Clusters)
{
var neighbours = result.GetNeighbours(cluster);
var colorDirection = VectorHelper.GetAveragePosition(neighbours.Select(v => v.ColorVector - cluster.ColorVector));
cluster.ColorDirection = colorDirection;
}
return(result);
}
public static GridHierarchy CreateFromPixels(PixelData pixels)
{
GridHierarchy result = new GridHierarchy(pixels.Width, pixels.Height, 1);
for (var i = 0; i <= pixels.Width - 1; i++)
{
for (var j = 0; j <= pixels.Height - 1; j++)
{
Cluster cluster = new Cluster()
{
Position = new Vector2(i, j),
Color = pixels.Colors[i, j]
};
result.Grid[i, j].Add(cluster);
result.Clusters.Add(cluster);
}
}
return(result);
}
public ClusteringAI(PixelData pixels, int maxRank = 10)
{
DateTime start = DateTime.Now;
Debug.WriteLine("Initialize Start");
Hierarchies.Add(GridHierarchy.CreateFromPixels(pixels));
Debug.WriteLine($"Initialize Over,TimeConsuming:{DateTime.Now - start}");
Debug.WriteLine($"Generation Start");
for (var i = 0; i <= maxRank - 1; i++)
{
start = DateTime.Now;
Hierarchies.Add(Hierarchies.Last().Generate());
Debug.WriteLine($"Total:{maxRank},Current:{i + 1},Time Consuming:{DateTime.Now - start},Hierarchy[{Hierarchies.Last().ToString()}]");
}
Debug.WriteLine(pixels.Colors.Length);
for (var i = maxRank - 1; i >= 0; i += -1)
{
Lines.AddRange(GenerateLines(Hierarchies[i]));
}
}
public override IHierarchy Generate()
{
float rate = 2.0F;
float newSize = this.Size * rate;
GridHierarchy result = new GridHierarchy(System.Convert.ToInt32(Math.Ceiling(this.Width / (double)rate) + 1), System.Convert.ToInt32(Math.Ceiling(this.Height / (double)rate) + 1), newSize)
{
Rank = this.Rank + 1
};
// Combine to a new cluster
//foreach (var cluster in Clusters)
//{
// Cluster similar = cluster.GetMostSimilar(GetNeighbours(cluster)).FirstOrDefault();
// if (similar != null)
// {
// if (cluster.Parent == null && similar.Parent == null)
// result.Clusters.Add(Cluster.Combine(cluster, similar));
// else
// Cluster.Combine(cluster, similar);
// }
// else
// {
// result.Clusters.Add(cluster);
// }
//}
Parallel.ForEach(Clusters, cluster =>
{
Cluster similar = cluster.GetMostSimilar(GetNeighbours(cluster)).FirstOrDefault();
if (similar != null)
{
if (cluster.Parent == null && similar.Parent == null)
{
result.Clusters.Add(Cluster.Combine(cluster, similar));
}
else
{
Cluster.Combine(cluster, similar);
}
}
else
{
result.Clusters.Add(cluster);
}
});
// Initialize properties
Parallel.ForEach(result.Clusters, cluster =>
{
cluster.Position = cluster.GetAveragePosition();
cluster.Color = cluster.GetAverageColor();
});
// Locate to cell
Parallel.ForEach(result.Clusters, cluster =>
{
Vector2 p = cluster.Position;
int x = System.Convert.ToInt32(p.X / (double)result.Size);
int y = System.Convert.ToInt32(p.Y / (double)result.Size);
result.Grid[x, y].Add(cluster);
});
// Calculate edge vector
Parallel.ForEach(result.Clusters, cluster =>
{
cluster.EdgeVector = result.GetNeighboursEdgeVector(cluster);;
});
return(result);
}