public LinkedList <Features> FindSimilar(int featureID, int kResults)
{
float[] queryFeature = GetFeatures(featureID);
LinkedList <Features> results = new LinkedList <Features>();
reader.BaseStream.Seek(featureDataStartOffset, SeekOrigin.Begin);
for (int i = 0; i < FeatureCount; i++)
{
if (i % 10000 == 0)
{
Console.WriteLine("Checking feature ID: " + i);
}
byte[] bytes = reader.ReadBytes(FeatureDimension * sizeof(float));
float[] floats = new float[bytes.Length / sizeof(float)];
Buffer.BlockCopy(bytes, 0, floats, 0, bytes.Length);
double distance = Distance.L2(queryFeature, floats);
if (results.Count == 0)
{
results.AddFirst(new Features(floats, i, distance));
}
else if (results.Count < kResults || distance < results.Last.Value.distance)
{
LinkedListNode <Features> node = results.First;
while (node != null && node.Value.distance < distance)
{
node = node.Next;
}
if (node != null)
{
results.AddBefore(node, new Features(floats, i, distance));
}
else
{
results.AddLast(new Features(floats, i, distance));
}
if (results.Count > kResults)
{
results.RemoveLast();
}
}
}
return(results);
}
public LinkedList <Features>[][] FindSimilarsIgnoreNullRadius(int[] featureIDs, int kResults, int nRadiuses, float increment, float bias)
{
float[][] queryFeatures = new float[featureIDs.Length][];
for (int i = 0; i < queryFeatures.Length; i++)
{
//queryFeatures[i] = new float[4096];
queryFeatures[i] = GetFeatures(featureIDs[i]);
}
LinkedList <Features>[][] results = new LinkedList <Features> [nRadiuses][];
for (int i = 0; i < nRadiuses; i++)
{
results[i] = new LinkedList <Features> [featureIDs.Length];
for (int j = 0; j < featureIDs.Length; j++)
{
results[i][j] = new LinkedList <Features>();
}
}
reader.BaseStream.Seek(featureDataStartOffset, SeekOrigin.Begin);
for (int iFeature = 0; iFeature < FeatureCount; iFeature++)
{
if (iFeature % 1000 == 0)
{
Console.WriteLine("Checking feature ID: " + iFeature);
}
byte[] bytes = reader.ReadBytes(FeatureDimension * sizeof(float));
float[] floats = new float[FeatureDimension];
Buffer.BlockCopy(bytes, 0, floats, 0, bytes.Length);
double nullDistance = Distance.L2(new float[FeatureDimension], floats);
Parallel.For(0, featureIDs.Length, index =>
{
for (int iRadius = 0; iRadius < nRadiuses; iRadius++)
{
if (nullDistance < (iRadius * increment) + bias)
{
continue;
}
double distance = Distance.L2(queryFeatures[index], floats);
if (results[iRadius][index].Count == 0)
{
results[iRadius][index].AddFirst(new Features(floats, iFeature, distance));
}
else if (results[iRadius][index].Count < kResults || distance < results[iRadius][index].Last.Value.distance)
{
LinkedListNode <Features> node = results[iRadius][index].First;
while (node != null && node.Value.distance < distance)
{
node = node.Next;
}
if (node != null)
{
results[iRadius][index].AddBefore(node, new Features(floats, iFeature, distance));
}
else
{
results[iRadius][index].AddLast(new Features(floats, iFeature, distance));
}
if (results[iRadius][index].Count > kResults)
{
results[iRadius][index].RemoveLast();
}
}
}
});
}
return(results);
}
public LinkedList <Features>[] FindSimilars(int[] featureIDs, int kResults)
{
float[][] queryFeatures = new float[featureIDs.Length][];
for (int i = 0; i < queryFeatures.Length; i++)
{
//queryFeatures[i] = new float[featureDimension];
queryFeatures[i] = GetFeatures(featureIDs[i]);
}
LinkedList <Features>[] results = new LinkedList <Features> [featureIDs.Length];
for (int i = 0; i < featureIDs.Length; i++)
{
results[i] = new LinkedList <Features>();
}
reader.BaseStream.Seek(featureDataStartOffset, SeekOrigin.Begin);
for (int i = 0; i < FeatureCount; i++)
{
if (i % 10000 == 0)
{
Console.WriteLine("Checking feature ID: " + i);
}
byte[] bytes = reader.ReadBytes(FeatureDimension * sizeof(float));
float[] floats = new float[bytes.Length / sizeof(float)];
Buffer.BlockCopy(bytes, 0, floats, 0, bytes.Length);
double[] distances = new double[featureIDs.Length];
Parallel.For(0, featureIDs.Length, j =>
{
distances[j] = Distance.L2(queryFeatures[j], floats);
if (results[j].Count == 0)
{
results[j].AddFirst(new Features(floats, i, distances[j]));
}
else if (results[j].Count < kResults || distances[j] < results[j].Last.Value.distance)
{
LinkedListNode <Features> node = results[j].First;
while (node != null && node.Value.distance < distances[j])
{
node = node.Next;
}
if (node != null)
{
results[j].AddBefore(node, new Features(floats, i, distances[j]));
}
else
{
results[j].AddLast(new Features(floats, i, distances[j]));
}
if (results[j].Count > kResults)
{
results[j].RemoveLast();
}
}
});
}
return(results);
}