//Test the quantization, connected components on different color layers, and output the descriptor
private void OutputPatterns_Click(object sender, RoutedEventArgs e)
{
//Create output directories
Directory.CreateDirectory(outdir + "\\cc\\");
Directory.CreateDirectory(outdir + "\\quantized\\");
Directory.CreateDirectory(outdir + "\\mesh\\");
//read in the patterns and save out their layers
String[] files = System.IO.Directory.GetFiles(System.IO.Path.Combine(imagedir));
List <PatternItem> patterns = PatternIO.GetPatterns(imagedir);
foreach (PatternItem p in patterns)
{
Bitmap image = new Bitmap(p.FullPath);
String basename = p.Name;
//TODO: sometimes keys are not found in patterns.csv...will need to look into recovering missing info. For now, just ignore those patterns
if (!palettes.ContainsKey(basename))
{
continue;
}
PaletteData palette = palettes[basename];
ColorTemplate template = new ColorTemplate(image, palette);
//output the template descriptor
SegmentMesh mesh = new SegmentMesh(template);
PatternIO.SaveMesh(mesh, p, Path.Combine(outdir, "mesh"));
if (outputDebugImages)
{
Bitmap result = template.DebugQuantization();
PatternIO.SavePattern(result, p, Path.Combine(outdir, "quantized"), "_quantized");
PatternIO.SavePattern(result, p, Path.Combine(outdir, "quantized"), "_original");
//save the connected components
UnionFind <Color> uf = new UnionFind <Color>((a, b) => (a.GetHashCode() == b.GetHashCode()));
Color[,] resultArray = Util.BitmapToArray(result);
int[,] cc = uf.ConnectedComponentsNoiseRemoval(resultArray);
int numColors = palette.colors.Count();
for (int i = 0; i < numColors; i++)
{
Bitmap debug = uf.RenderComponents(cc, resultArray, palette.colors[i]);
PatternIO.SavePattern(debug, p, Path.Combine(outdir, "cc"), "_" + i);
debug.Dispose();
}
result.Dispose();
}
image.Dispose();
}
}
public SegmentMesh(ColorTemplate template)
{
int numGroups = template.NumSlots();
imageWidth = template.Width();
imageHeight = template.Height();
groups = new List <SegmentGroup>();
segments = new List <Segment>();
//now populate the segments and segment groups
//filter out groups that have no members (due to quantization)
Dictionary <int, int> slotToGroup = new Dictionary <int, int>();
for (int i = 0; i < numGroups; i++)
{
if (template.PixelsInSlot(i) > 0)
{
slotToGroup.Add(i, groups.Count());
groups.Add(new SegmentGroup(template.OriginalSlotColor(i)));
}
}
UnionFind <Color> uf = new UnionFind <Color>((a, b) => (a.GetHashCode() == b.GetHashCode()));
Bitmap image = template.DebugQuantization();
assignments = uf.ConnectedComponentsNoiseRemoval(Util.BitmapToArray(image));
Dictionary <int, Segment> idToSegment = new Dictionary <int, Segment>();
int totalAdjacencyPerimeter = 0;
Dictionary <int, HashSet <Point> > idToPerimeter = new Dictionary <int, HashSet <Point> >();
//populate segments
int width = image.Width;
int height = image.Height;
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
int id = assignments[i, j];
if (!idToSegment.ContainsKey(id))
{
idToSegment.Add(id, new Segment(id));
idToPerimeter.Add(id, new HashSet <Point>());
}
idToSegment[id].points.Add(new Point(i, j));
idToSegment[id].groupId = slotToGroup[template.GetSlotId(i, j)];
//look for 8-neighbor adjacencies, 2 pixels away
//TODO: measure adjacency strength and filter?
for (int dx = -2; dx <= 2; dx++)
{
for (int dy = -2; dy <= 2; dy++)
{
int x = i + dx;
int y = j + dy;
if (x >= 0 && x < width && y >= 0 && y < height)
{
int nid = assignments[x, y];
if (nid != id)
{
idToSegment[id].adjacencies.Add(nid);
//keep track of the total perimeter, and individual segment perimeters
//don't double count the same point for each segment
if (!idToPerimeter[id].Contains(new Point(x, y)))
{
idToPerimeter[id].Add(new Point(x, y));
totalAdjacencyPerimeter++;
//keep track of the adjacecy strength per segment
if (!idToSegment[id].adjacencyStrength.ContainsKey(nid))
{
idToSegment[id].adjacencyStrength.Add(nid, 0);
}
idToSegment[id].adjacencyStrength[nid]++;
}
else
{
Console.WriteLine("Point already counted");
}
}
}
else
{
//might as well be consistent here, and take into account the borders of the image when determining
//enclosure. We don't need to do this for the totalAdjacencyPerimeter, because that is just a normalization
//for the adjacency strengths of segments within the image
if (!idToPerimeter[id].Contains(new Point(x, y)))
{
idToPerimeter[id].Add(new Point(x, y));
}
}
}
}
}
}
//finalize segment list and adjacency list
Dictionary <int, int> idToIdx = new Dictionary <int, int>();
foreach (int id in idToSegment.Keys)
{
segments.Add(idToSegment[id]);
idToIdx.Add(id, segments.Count() - 1);
}
//finalize adjacencies
for (int i = 0; i < segments.Count(); i++)
{
SortedSet <int> renamedAdj = new SortedSet <int>();
foreach (int a in segments[i].adjacencies)
{
renamedAdj.Add(idToIdx[a]);
}
segments[i].adjacencies = renamedAdj;
//finalize adjacency strengths
int sid = assignments[segments[i].points.First().X, segments[i].points.First().Y];
Dictionary <int, double> renamedAdjStrength = new Dictionary <int, double>();
foreach (int nid in segments[i].adjacencyStrength.Keys)
{
double pixelsAdj = segments[i].adjacencyStrength[nid];
renamedAdjStrength.Add(idToIdx[nid], pixelsAdj / totalAdjacencyPerimeter);
segments[i].enclosureStrength.Add(idToIdx[nid], new Tuple <double, double>(pixelsAdj / idToPerimeter[sid].Count(), pixelsAdj / idToPerimeter[nid].Count()));
}
segments[i].adjacencyStrength = renamedAdjStrength;
}
//finalize groups
for (int i = 0; i < segments.Count(); i++)
{
int groupId = segments[i].groupId;
groups[groupId].members.Add(i);
}
//finalize segment list
ClassifySegments();
foreach (Segment s in segments)
{
ComputeFeatures(s);
}
foreach (SegmentGroup g in groups)
{
ComputeFeatures(g);
}
}
public SegmentMesh(ColorTemplate template)
{
int numGroups = template.NumSlots();
imageWidth = template.Width();
imageHeight = template.Height();
groups = new List<SegmentGroup>();
segments = new List<Segment>();
//now populate the segments and segment groups
//filter out groups that have no members (due to quantization)
Dictionary<int, int> slotToGroup = new Dictionary<int, int>();
for (int i = 0; i < numGroups; i++)
{
if (template.PixelsInSlot(i) > 0)
{
slotToGroup.Add(i, groups.Count());
groups.Add(new SegmentGroup(template.OriginalSlotColor(i)));
}
}
UnionFind<Color> uf = new UnionFind<Color>((a, b) => (a.GetHashCode() == b.GetHashCode()));
Bitmap image = template.DebugQuantization();
assignments = uf.ConnectedComponentsNoiseRemoval(Util.BitmapToArray(image));
Dictionary<int, Segment> idToSegment = new Dictionary<int, Segment>();
int totalAdjacencyPerimeter = 0;
Dictionary<int, HashSet<Point>> idToPerimeter = new Dictionary<int, HashSet<Point>>();
//populate segments
int width = image.Width;
int height = image.Height;
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
int id = assignments[i, j];
if (!idToSegment.ContainsKey(id))
{
idToSegment.Add(id, new Segment(id));
idToPerimeter.Add(id, new HashSet<Point>());
}
idToSegment[id].points.Add(new Point(i, j));
idToSegment[id].groupId = slotToGroup[template.GetSlotId(i, j)];
//look for 8-neighbor adjacencies, 2 pixels away
//TODO: measure adjacency strength and filter?
for (int dx = -2; dx <= 2; dx++)
{
for (int dy = -2; dy <= 2; dy++)
{
int x = i + dx;
int y = j + dy;
if (x >= 0 && x < width && y >= 0 && y < height)
{
int nid = assignments[x, y];
if (nid != id)
{
idToSegment[id].adjacencies.Add(nid);
//keep track of the total perimeter, and individual segment perimeters
//don't double count the same point for each segment
if (!idToPerimeter[id].Contains(new Point(x, y)))
{
idToPerimeter[id].Add(new Point(x, y));
totalAdjacencyPerimeter++;
//keep track of the adjacecy strength per segment
if (!idToSegment[id].adjacencyStrength.ContainsKey(nid))
idToSegment[id].adjacencyStrength.Add(nid, 0);
idToSegment[id].adjacencyStrength[nid]++;
}
else
{
Console.WriteLine("Point already counted");
}
}
}
else
{
//might as well be consistent here, and take into account the borders of the image when determining
//enclosure. We don't need to do this for the totalAdjacencyPerimeter, because that is just a normalization
//for the adjacency strengths of segments within the image
if (!idToPerimeter[id].Contains(new Point(x,y)))
{
idToPerimeter[id].Add(new Point(x,y));
}
}
}
}
}
}
//finalize segment list and adjacency list
Dictionary<int, int> idToIdx = new Dictionary<int, int>();
foreach (int id in idToSegment.Keys)
{
segments.Add(idToSegment[id]);
idToIdx.Add(id, segments.Count() - 1);
}
//finalize adjacencies
for (int i = 0; i < segments.Count(); i++)
{
SortedSet<int> renamedAdj = new SortedSet<int>();
foreach (int a in segments[i].adjacencies)
renamedAdj.Add(idToIdx[a]);
segments[i].adjacencies = renamedAdj;
//finalize adjacency strengths
int sid = assignments[segments[i].points.First().X, segments[i].points.First().Y];
Dictionary<int, double> renamedAdjStrength = new Dictionary<int, double>();
foreach (int nid in segments[i].adjacencyStrength.Keys)
{
double pixelsAdj = segments[i].adjacencyStrength[nid];
renamedAdjStrength.Add(idToIdx[nid], pixelsAdj / totalAdjacencyPerimeter);
segments[i].enclosureStrength.Add(idToIdx[nid], new Tuple<double, double>(pixelsAdj / idToPerimeter[sid].Count(), pixelsAdj / idToPerimeter[nid].Count()));
}
segments[i].adjacencyStrength = renamedAdjStrength;
}
//finalize groups
for (int i = 0; i < segments.Count(); i++)
{
int groupId = segments[i].groupId;
groups[groupId].members.Add(i);
}
//finalize segment list
ClassifySegments();
foreach (Segment s in segments)
{
ComputeFeatures(s);
}
foreach (SegmentGroup g in groups)
{
ComputeFeatures(g);
}
}
//Test the quantization, connected components on different color layers, and output the descriptor
private void OutputPatterns_Click(object sender, RoutedEventArgs e)
{
//Create output directories
Directory.CreateDirectory(outdir + "\\cc\\");
Directory.CreateDirectory(outdir + "\\quantized\\");
Directory.CreateDirectory(outdir + "\\mesh\\");
//read in the patterns and save out their layers
String[] files = System.IO.Directory.GetFiles(System.IO.Path.Combine(imagedir));
List<PatternItem> patterns = PatternIO.GetPatterns(imagedir);
foreach (PatternItem p in patterns)
{
Bitmap image= new Bitmap(p.FullPath);
String basename = p.Name;
//TODO: sometimes keys are not found in patterns.csv...will need to look into recovering missing info. For now, just ignore those patterns
if (!palettes.ContainsKey(basename))
continue;
PaletteData palette = palettes[basename];
ColorTemplate template = new ColorTemplate(image, palette);
//output the template descriptor
SegmentMesh mesh = new SegmentMesh(template);
PatternIO.SaveMesh(mesh, p, Path.Combine(outdir, "mesh"));
if (outputDebugImages)
{
Bitmap result = template.DebugQuantization();
PatternIO.SavePattern(result, p, Path.Combine(outdir, "quantized"), "_quantized");
PatternIO.SavePattern(result, p, Path.Combine(outdir, "quantized"), "_original");
//save the connected components
UnionFind<Color> uf = new UnionFind<Color>((a, b) => (a.GetHashCode() == b.GetHashCode()));
Color[,] resultArray = Util.BitmapToArray(result);
int[,] cc = uf.ConnectedComponentsNoiseRemoval(resultArray);
int numColors = palette.colors.Count();
for (int i = 0; i < numColors; i++)
{
Bitmap debug = uf.RenderComponents(cc, resultArray, palette.colors[i]);
PatternIO.SavePattern(debug, p, Path.Combine(outdir, "cc"), "_" + i);
debug.Dispose();
}
result.Dispose();
}
image.Dispose();
}
}
