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);
}
}
private void Vis(bool figureQuality = false)
{
Directory.CreateDirectory(outdir + "\\viscolor\\");
Directory.CreateDirectory(outdir + "\\vis\\");
//read in the patterns and save out their layers
List<PatternItem> patterns = PatternIO.GetPatterns(imagedir);
foreach (PatternItem p in patterns)
{
String basename = p.Name;
//Read the vis permutation description if available
String specs = Path.Combine(outdir, "vis", p.Directory, Util.ConvertFileName(basename, "", ".txt"));
if (!File.Exists(specs))
continue;
Bitmap image = new Bitmap(p.FullPath);
if (!palettes.ContainsKey(basename))
continue;
PaletteData palette = palettes[basename];
ColorTemplate template = new ColorTemplate(image, palette);
int[] slotToColor = new int[template.NumSlots()];
for (int i = 0; i < slotToColor.Count(); i++)
slotToColor[i] = i;
Dictionary<int, int> groupToSlot = new Dictionary<int, int>();
PaletteData data = new PaletteData();
int ngroups = 0;
for (int i = 0; i < slotToColor.Count(); i++)
{
slotToColor[i] = i;
data.colors.Add(new Color());
data.lab.Add(new CIELAB());
if (template.PixelsInSlot(i) > 0)
groupToSlot.Add(ngroups++, i);
}
Bitmap vis = null;
Graphics g = null;
String[] lines = File.ReadAllLines(specs);
//read the score and if it's the original or not
double score = 0;
bool orig = false;
int nresult = 0;
int y = 0;
int x = 0;
int ncol = 8;
int iwidth = 200;
int iheight = 200;
int padding = (figureQuality) ? 8 : 15 ;
Font font = new Font("Arial", 8);
int colorIdx = 0;
foreach (String line in lines)
{
if (line.StartsWith("Count"))
{
int count = Int32.Parse(line.Split(' ').Last());
//initialize the result image
int nrow = count / ncol + 1;
vis = new Bitmap(ncol*iwidth, nrow*iheight);
g = Graphics.FromImage(vis);
} else if (line.StartsWith("Score"))
{
//add the result to the visualization
x = (nresult % ncol)*iwidth;
y = (nresult / ncol)*iheight;
if (colorIdx > 0)
{
Bitmap result = (renderFinal) ? GetFinalRendering(Util.ConvertFileName(basename, "",""), data): template.SolidColor(data, slotToColor);
//sometimes we can't get the nice image, so render the quantized image in this case
if (result == null)
result = template.SolidColor(data, slotToColor);
g.DrawImage(result, x, y, iwidth-padding, iheight-padding);
String label = String.Format("{0:0.00}", score);
Color color = Color.Black;
if (orig)
{
label += ", ***";
color = Color.Red;
}
if(!figureQuality) g.DrawString(label, font, new SolidBrush(color), x, y + iheight-padding);
result.Dispose();
colorIdx = 0;
//data.colors.Clear();
//data.lab.Clear();
nresult++;
}
score = Double.Parse(line.Split(' ')[1]);
orig = Boolean.Parse(line.Split(' ')[2]);
}
else
{
//rgb floats
int[] fields = line.Split(new string[] { " " }, StringSplitOptions.RemoveEmptyEntries).Select<String, int>(s => ((int)(Math.Round(double.Parse(s) * 255)))).ToArray<int>();
Color color = Color.FromArgb(fields[0], fields[1], fields[2]);
data.colors[groupToSlot[colorIdx]] = color;
data.lab[groupToSlot[colorIdx]] = Util.RGBtoLAB(color);
colorIdx++;
}
}
//save the last image
if (data.colors.Count() > 0)
{
x = (nresult % ncol) * iwidth;
y = (nresult / ncol) * iheight;
Bitmap result = (renderFinal)? GetFinalRendering(Util.ConvertFileName(basename, "",""), data): template.SolidColor(data, slotToColor);
//sometimes we can't get the nice image, so render the quantized image in this case
if (result == null)
result = template.SolidColor(data, slotToColor);
g.DrawImage(result, x, y, iwidth - padding, iheight - padding);
Color color = Color.Black;
String label = String.Format("{0:0.00}", score);
if (orig)
{
label += ", ***";
color = Color.Red;
}
if (!figureQuality) g.DrawString(label, font, new SolidBrush(color), x, y + iheight - padding);
result.Dispose();
//data.colors.Clear();
//data.lab.Clear();
colorIdx = 0;
nresult++;
}
PatternIO.SavePattern(vis, p, Path.Combine(outdir, "viscolor"));
vis.Dispose();
}
}
//render an image of the original pattern, plus columns of patterns generated by different models (trained on diff styles)
private void VisAllStyles()
{
Directory.CreateDirectory(outdir + "\\stylecolor\\");
Directory.CreateDirectory(outdir + "\\styles\\");
//read in the patterns and save out their layers
List<PatternItem> patterns = PatternIO.GetPatterns(Path.Combine(imagedir,"../styles"));
foreach (PatternItem p in patterns)
{
String basename = p.Name;
//Read the style description if available
String specs = Path.Combine(outdir, "styles", p.Directory, Util.ConvertFileName(basename, "", ".txt"));
if (!File.Exists(specs))
continue;
Bitmap image = new Bitmap(p.FullPath);
if (!palettes.ContainsKey(basename))
continue;
PaletteData palette = palettes[basename];
ColorTemplate template = new ColorTemplate(image, palette);
int[] slotToColor = new int[template.NumSlots()];
for (int i = 0; i < slotToColor.Count(); i++)
slotToColor[i] = i;
List<List<String>> lines = File.ReadAllLines(specs).Select(line => line.Split(',').ToList<String>()).ToList<List<String>>();
if (lines.Count() == 0)
continue;
Dictionary<String, int> styleToRowIdx = new Dictionary<String, int>();
String origStyle = "";
foreach (List<String> line in lines)
{
origStyle = line[0];
if (!styleToRowIdx.ContainsKey(line[1]))
styleToRowIdx.Add(line[1], 0);
}
//read the score and if it's the original or not
double score = 0;
int iwidth = 100;
int iheight = 100;
int padding = 15;
int headerSpace = 30;
int width = (styleToRowIdx.Keys.Count() + 1) * iwidth;
int height = (lines.Count() / styleToRowIdx.Keys.Count()) * iheight + headerSpace;
Font font = new Font("Arial", 10);
Bitmap vis = new Bitmap(width, height);
Graphics g = Graphics.FromImage(vis);
//write out the headings, highlight the original style heading
var headers = styleToRowIdx.Keys.ToList<String>();
int ncol = headers.Count()+1;
Color headerColor = Color.Black;
g.DrawString("original", font, new SolidBrush(headerColor), 0, 0);
for (int i=0; i<headers.Count(); i++)
{
if (headers[i] == origStyle)
g.DrawString(headers[i], font, new SolidBrush(headerColor), (i+1)*iwidth, 0);
else
g.DrawString(headers[i], font, new SolidBrush(headerColor), (i+1)*iwidth, 0);
}
//draw the original
Bitmap original = (renderFinal)? image: template.DebugQuantization();
g.DrawImage(original, 0, headerSpace, iwidth-padding, iheight-padding);
original.Dispose();
PaletteData data = new PaletteData();
Dictionary<int, int> groupToSlot = new Dictionary<int, int>();
int ngroups = 0;
for (int i = 0; i < slotToColor.Count(); i++)
{
slotToColor[i] = i;
data.colors.Add(new Color());
data.lab.Add(new CIELAB());
if (template.PixelsInSlot(i) > 0)
groupToSlot.Add(ngroups++, i);
}
foreach (List<String> line in lines)
{
//draw the colorized thumbnail in the right location
String style = line[1];
String[] colors = line[2].Split('^');
int colorIdx = 0;
foreach (String color in colors)
{
//rgb floats
int[] fields = color.Split(new string[] { " " }, StringSplitOptions.RemoveEmptyEntries).Select<String, int>(s => ((int)(Math.Round(double.Parse(s) * 255)))).ToArray<int>();
Color c = Color.FromArgb(fields[0], fields[1], fields[2]);
data.colors[groupToSlot[colorIdx]] = c;
data.lab[groupToSlot[colorIdx]] = Util.RGBtoLAB(c);
colorIdx++;
}
int x = (headers.IndexOf(style)+1)*iwidth;
int y = styleToRowIdx[style]*iheight+headerSpace;
styleToRowIdx[style]++;
Bitmap result = (renderFinal)?GetFinalRendering(Util.ConvertFileName(basename, "",""), data):template.SolidColor(data, slotToColor);
//sometimes we can't get the nice image, so render the quantized image in this case
if (result == null)
result = template.SolidColor(data, slotToColor);
g.DrawImage(result, x, y, iwidth-padding, iheight-padding);
result.Dispose();
}
PatternIO.SavePattern(vis, p, Path.Combine(outdir, "stylecolor"));
vis.Dispose();
}
}
private void Recolor()
{
String suboutdir = Path.Combine(outdir, "recolored");
Directory.CreateDirectory(suboutdir);
//read in the patterns and save out their layers
List<PatternItem> patterns = PatternIO.GetPatterns(imagedir);
foreach (PatternItem p in patterns)
{
String basename = p.Name;
if (!palettes.ContainsKey(basename))
continue;
PaletteData palette = palettes[basename];
//Read the recoloring description if available
String specs = Path.Combine(outdir, "specs", p.Directory, Util.ConvertFileName(basename, "", ".txt"));
if (!File.Exists(specs))
continue;
Bitmap image = new Bitmap(p.FullPath);
//TODO: save and reload color templates functionality
ColorTemplate template = new ColorTemplate(image, palette);
PaletteData data = new PaletteData();
String[] lines = File.ReadAllLines(specs);
int[] slotToColor = new int[template.NumSlots()];
Dictionary<int, int> groupToSlot = new Dictionary<int, int>();
int ngroups = 0;
for (int i = 0; i < slotToColor.Count(); i++)
{
slotToColor[i] = i;
if (template.PixelsInSlot(i) > 0)
groupToSlot.Add(ngroups++, i);
}
//TODO: handle recoloring when # groups is less than number of original slots, because of quantization issues.
//Right now, this is rather ugly..
data.colors = new List<Color>();
data.lab = new List<CIELAB>();
for (int i = 0; i < slotToColor.Count(); i++)
{
data.colors.Add(new Color());
data.lab.Add(new CIELAB());
}
int groupid = 0;
foreach (String line in lines)
{
//rgb floats
int[] fields = line.Split(new string[]{" "},StringSplitOptions.RemoveEmptyEntries).Select<String, int>(s=>((int)(Math.Round(double.Parse(s)*255)))).ToArray<int>();
Color color = Color.FromArgb(fields[0], fields[1], fields[2]);
data.colors[groupToSlot[groupid]] = color;
data.lab[groupToSlot[groupid]] = Util.RGBtoLAB(color);
groupid++;
}
Bitmap orig = (renderFinal)? image : template.DebugQuantization();
PatternIO.SavePattern(orig, p, suboutdir, "_original");
orig.Dispose();
Bitmap result = (renderFinal)? GetFinalRendering(Util.ConvertFileName(basename, "",""), data): template.SolidColor(data, slotToColor);
//sometimes we can't get the nice image, so render the quantized image in this case. TODO: or maybe skip rendering this visualization at all
if (result == null)
result = template.SolidColor(data, slotToColor);
PatternIO.SavePattern(result, p, suboutdir, "_recolored");
result.Dispose();
}
}