/**
* Extract a palette by hill climbing on the given image
* key - image name in the base directory (directory)
* saliencyPattern - the label appended to the image name, to find the saliency map filename (i.e. "_Judd" for "[imagename]_Judd.[imagename extension]")
* debug - if images should be resized smaller
* paletteSize - the size of the palette to be extracted
*/
public PaletteData HillClimbPalette(String key, String saliencyPattern, bool debug = false, int paletteSize=5)
{
//Now initialize a palette and start hill climbing
int trials = 5;
PaletteScoreCache cache = new PaletteScoreCache(1000000);
PaletteData swatches = GetPaletteSwatches(key);
List<CIELAB> shuffled = new List<CIELAB>();
foreach (CIELAB c in swatches.lab)
shuffled.Add(c);
Random random = new Random();
//weights
Dictionary<Features, double> weights = new Dictionary<Features, double>();
weights = LoadWeights(Path.Combine(weightsDir,"weights.csv"), Path.Combine(weightsDir,"featurenames.txt"));
PaletteData best = new PaletteData();
double bestScore = Double.NegativeInfinity;
SortedSet<Features> included = new SortedSet<Features>(weights.Keys);
Stopwatch watch = new Stopwatch();
watch.Start();
FeatureParams fparams = SetupFeatureParams(included, key, saliencyPattern, debug);
Log(Path.Combine(dir, "out", "convergelog.txt"), "Setup feature params " + watch.ElapsedMilliseconds);
//Generate all the random starts first
List<PaletteData> starts = new List<PaletteData>();
PaletteData[] allOptions = new PaletteData[trials];
double[] allScores = new double[trials];
for (int t = 0; t < trials; t++)
{
//setup
PaletteData option = new PaletteData();
//pick k random colors. First shuffle the colors and pick the top k
for (int j = shuffled.Count() - 1; j >= 0; j--)
{
int idx = random.Next(j + 1);
CIELAB temp = shuffled[j];
shuffled[j] = shuffled[idx];
shuffled[idx] = temp;
}
for (int i = 0; i < paletteSize; i++)
{
option.lab.Add(shuffled[i]);
option.colors.Add(Util.LABtoRGB(shuffled[i]));
}
starts.Add(option);
allOptions[t] = new PaletteData(option);
double optionScore = ScorePalette(weights, CalculateFeatures(option, fparams));
allScores[t] = optionScore;
cache.SetScore(option.lab, optionScore);
}
watch.Restart();
for (int t = 0; t < trials; t++)
{
//setup
PaletteData option = new PaletteData(starts[t]);
double optionScore = allScores[t];
//Now hill climb, for each swatch, consider replacing it with a better swatch
//Pick the best replacement, and continue until we reach the top of a hill
int changes = 1;
int iters = 0;
int reuse = 0;
watch.Restart();
while (changes > 0)
{
changes = 0;
for (int i = 0; i < option.lab.Count(); i++)
{
//find the best swatch replacement for this color
double bestTempScore = optionScore;
CIELAB bestRep = option.lab[i];
Color bestRGB = option.colors[i];
double[] scores = new double[swatches.lab.Count()];
for (int s = 0; s < swatches.lab.Count(); s++)
{
CIELAB r = swatches.lab[s];
PaletteData temp = new PaletteData(option);
if (!temp.lab.Contains(r))
{
temp.lab[i] = r;
temp.colors[i] = swatches.colors[s];
if (!cache.ContainsKey(temp.lab))
{
double tempScore = ScorePalette(weights, CalculateFeatures(temp, fparams));
scores[s] = tempScore;
cache.SetScore(temp.lab, tempScore);
}
else
{
scores[s] = cache.GetScore(temp.lab);
reuse++;
}
}
else
{
scores[s] = Double.NegativeInfinity;
}
}
//aggregate results
for (int s = 0; s < scores.Count(); s++)
{
if (scores[s] > bestTempScore)
{
bestTempScore = scores[s];
bestRep = swatches.lab[s];
bestRGB = swatches.colors[s];
}
}
if (!option.lab[i].Equals(bestRep))
{
option.lab[i] = bestRep;
option.colors[i] = bestRGB;
optionScore = bestTempScore;
changes++;
}
}
iters++;
}
if (optionScore > allScores[t])
{
allOptions[t] = option;
allScores[t] = optionScore;
}
Log(Path.Combine(dir, "out", "convergelog.txt"), "Trial " + t + " Key " + key + " BestScore: " + allScores[t] + " Steps: " + iters + " Time: " + watch.ElapsedMilliseconds);
Log(Path.Combine(dir, "out", "convergelog.txt"), "Reused " + reuse);
}
//aggregate scores
for (int i = 0; i < allScores.Count(); i++)
{
if (allScores[i] > bestScore)
{
bestScore = allScores[i];
best = allOptions[i];
}
}
//convert best lab to rgb
best.colors = new List<Color>();
foreach (CIELAB l in best.lab)
best.colors.Add(Util.LABtoRGB(l));
return best;
}
private List<PaletteData> GenerateRandomPalettes(int count, List<PaletteData> palettes, PaletteData swatches)
{
PaletteScoreCache cache = new PaletteScoreCache(1000000);
int k = 5;
List<PaletteData> data = new List<PaletteData>();
Random random = new Random();
List<int> shuffled = new List<int>();
for (int i = 0; i < swatches.lab.Count(); i++)
shuffled.Add(i);
//find the max scoring human palette
double maxScore = Double.NegativeInfinity;
foreach (PaletteData p in palettes)
{
double score = 1 - GetAvgDist(new List<PaletteData> { p }, palettes);
maxScore = Math.Max(maxScore, score);
}
//generate random palettes to find the min score
double minScore = Double.PositiveInfinity;
for (int i = 0; i < 10000; i++)
{
PaletteData result = new PaletteData();
result.id = -1;
//pick k random colors. First shuffle the colors and pick the top k
for (int j = shuffled.Count() - 1; j >= 0; j--)
{
int idx = random.Next(j + 1);
int temp = shuffled[j];
shuffled[j] = shuffled[idx];
shuffled[idx] = temp;
}
for (int c = 0; c < k; c++)
{
result.colors.Add(swatches.colors[shuffled[c]]);
result.lab.Add(swatches.lab[shuffled[c]]);
}
double score = 1 - GetAvgDist(new List<PaletteData>{result}, palettes);
cache.SetScore(result.lab, score);
minScore = Math.Min(minScore, score);
maxScore = Math.Max(maxScore, score);
}
int numbins = 10;
int[] counts = new int[numbins];
int totalCount = 0;
int thresh = count / numbins;
int tries = 0;
//generate random palettes, given swatches
while (totalCount < count)
{
if (tries % 1000 == 0)
{
String log = Path.Combine(trainOutDir, "randlog.txt");
Log(log, tries + "-" + totalCount + " binned ");
Log(log, " bins --- " + counts[0] + "," + counts[1] + "," + counts[2] + "," + counts[3] + "," + counts[4] + "," + counts[5] + "," + counts[6] + "," + counts[7] + "," + counts[8] + "," + counts[9]);
backgroundWorker.ReportProgress(-1,"bin counts " + String.Join(",",counts));
}
tries++;
PaletteData result = new PaletteData();
result.id = -1;
//pick k random colors. First shuffle the colors and pick the top k
for (int j = shuffled.Count() - 1; j >= 0; j--)
{
int idx = random.Next(j + 1);
int temp = shuffled[j];
shuffled[j] = shuffled[idx];
shuffled[idx] = temp;
}
for (int c = 0; c < k; c++)
{
result.colors.Add(swatches.colors[shuffled[c]]);
result.lab.Add(swatches.lab[shuffled[c]]);
}
double score = 0;
if (cache.ContainsKey(result.lab))
score = cache.GetScore(result.lab);
else
{
score = 1 - GetAvgDist(new List<PaletteData> { result }, palettes);
cache.SetScore(result.lab, score);
}
score = (score - minScore) / (maxScore - minScore);
int bin = (int)Math.Min(Math.Max(0, Math.Floor(score * numbins)), numbins - 1);
if (counts[bin] >= thresh)
continue;
totalCount++;
counts[bin]++;
data.Add(result);
}
return data;
}