public static AudioFeature FromBytesXML(byte[] buf)
{
String xmlData = StringUtils.GetString(buf);
XmlTextReader xmlTextReader = new XmlTextReader(new StringReader(xmlData));
MandelEllis mandelEllis = new MandelEllis();
mandelEllis.ReadXML(xmlTextReader);
return(mandelEllis);
}
/// <summary>Get Distance</summary>
/// <seealso cref="">comirva.audio.feature.AudioFeature#GetDistance(comirva.audio.feature.AudioFeature)</seealso>
public override double GetDistance(AudioFeature f)
{
if (!(f is MandelEllis))
{
new Exception("Can only handle AudioFeatures of type Mandel Ellis, not of: " + f);
return(-1);
}
MandelEllis other = (MandelEllis)f;
return(KullbackLeibler(this.gmmMe, other.gmmMe) + KullbackLeibler(other.gmmMe, this.gmmMe));
}
public static AudioFeature FromBytesCompressed(byte[] byteArray)
{
using (Stream stream = new MemoryStream(byteArray)) {
Matrix mean = Matrix.LoadBinary(stream);
Matrix covarMatrix = Matrix.LoadBinary(stream);
Matrix covarMatrixInv = Matrix.LoadBinary(stream);
stream.Flush();
MandelEllis.GmmMe gmmme = new MandelEllis.GmmMe(mean, covarMatrix, covarMatrixInv);
var mandelEllis = new MandelEllis(gmmme);
return(mandelEllis);
}
}
public AudioFeature Calculate(double[] input)
{
//pack the mfccs into a pointlist
double[][] mfccCoefficients = mfcc.Process(input);
//check if element 0 exists
if(mfccCoefficients.Length == 0)
throw new ArgumentException("The input stream is to short to process;");
//create mfcc matrix
Matrix mfccs = new Matrix(mfccCoefficients);
#if DEBUG
mfccs.WriteText("mfccdata-mandelellis.txt");
mfccs.DrawMatrixGraph("mfccdata-mandelellis.png");
#endif
// compute mean
//Matrix mean = mfccs.Mean(1).Transpose();
Matrix mean = mfccs.Mean(2);
#if DEBUG
mean.WriteText("mean-mandelellis.txt");
mean.DrawMatrixGraph("mean-mandelellis.png");
#endif
// create covariance matrix
Matrix covarMatrix = mfccs.Cov();
#if DEBUG
covarMatrix.WriteText("covariance-mandelellis.txt");
covarMatrix.DrawMatrixGraph("covariance-mandelellis.png");
#endif
// Inverse Covariance
Matrix covarMatrixInv;
try {
//covarMatrixInv = covarMatrix.Inverse();
covarMatrixInv = covarMatrix.InverseGausJordan();
} catch (Exception) {
Console.Error.WriteLine("Mandel Ellis Extraction Failed!");
return null;
}
#if DEBUG
covarMatrixInv.WriteText("inverse_covariance-mandelellis.txt");
covarMatrixInv.DrawMatrixGraph("inverse_covariance-mandelellis.png");
#endif
MandelEllis.GmmMe gmmMe = new MandelEllis.GmmMe(mean, covarMatrix, covarMatrixInv);
MandelEllis mandelEllis = new MandelEllis(gmmMe);
return mandelEllis;
}
/// <summary>Get Distance</summary>
/// <seealso cref="">comirva.audio.feature.AudioFeature#GetDistance(comirva.audio.feature.AudioFeature)</seealso>
public override double GetDistance(AudioFeature f, AudioFeature.DistanceType t)
{
if (!(f is MandelEllis))
{
new Exception("Can only handle AudioFeatures of type Mandel Ellis, not of: " + f);
return(-1);
}
MandelEllis other = (MandelEllis)f;
DistanceMeasure distanceMeasure = DistanceMeasure.Euclidean;
switch (t)
{
case AudioFeature.DistanceType.Dtw_Euclidean:
distanceMeasure = DistanceMeasure.Euclidean;
break;
case AudioFeature.DistanceType.Dtw_SquaredEuclidean:
distanceMeasure = DistanceMeasure.SquaredEuclidean;
break;
case AudioFeature.DistanceType.Dtw_Manhattan:
distanceMeasure = DistanceMeasure.Manhattan;
break;
case AudioFeature.DistanceType.Dtw_Maximum:
distanceMeasure = DistanceMeasure.Maximum;
break;
case AudioFeature.DistanceType.KullbackLeiblerDivergence:
default:
return(KullbackLeibler(this.gmmMe, other.gmmMe) + KullbackLeibler(other.gmmMe, this.gmmMe));
}
Dtw dtw = new Dtw(this.GetArray(), other.GetArray(), distanceMeasure, true, true, null, null, null);
return(dtw.GetCost());
}
/// <summary>
/// Find Similar Tracks to one or many audio files using their unique database id(s)
/// </summary>
/// <param name="id">an array of unique database ids for the audio files to search for similar matches</param>
/// <param name="exclude">an array of unique database ids to ignore (normally the same as the id array)</param>
/// <param name="db">database</param>
/// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param>
/// <param name="numToTake">max number of entries to return</param>
/// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param>
/// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param>
/// <returns>a list of query results</returns>
public static List<FindSimilar.QueryResult> SimilarTracksList(int[] id, int[] exclude, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence) {
AudioFeature[] seedAudioFeatures = null;
AudioFeature[] audioFeatures = null;
switch (analysisMethod) {
case Analyzer.AnalysisMethod.MandelEllis:
seedAudioFeatures = new MandelEllis[id.Length];
audioFeatures = new MandelEllis[100];
break;
case Analyzer.AnalysisMethod.SCMS:
seedAudioFeatures = new Scms[id.Length];
audioFeatures = new Scms[100];
break;
}
for (int i = 0; i < seedAudioFeatures.Length; i++) {
seedAudioFeatures[i] = db.GetTrack(id[i], analysisMethod);
}
// Get all tracks from the DB except the seedSongs
IDataReader r = db.GetTracks(exclude, seedAudioFeatures[0].Duration, percentage);
// store results in a query results list
List<FindSimilar.QueryResult> queryResultList = new List<FindSimilar.QueryResult>();
int[] mapping = new int[100];
int read = 1;
double d;
double dcur;
float count;
while (read > 0) {
read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod);
for (int i = 0; i < read; i++) {
d = 0;
count = 0;
for (int j = 0; j < seedAudioFeatures.Length; j++) {
dcur = seedAudioFeatures[j].GetDistance(audioFeatures[i], distanceType);
// convert to positive values
dcur = Math.Abs(dcur);
d += dcur;
count++;
}
if (d > 0) {
QueryResult queryResult = new QueryResult();
queryResult.Id = mapping[i];
queryResult.Path = audioFeatures[i].Name;
queryResult.Duration = audioFeatures[i].Duration;
queryResult.Similarity = d/count;
queryResultList.Add(queryResult);
}
}
}
var sortedList = (from row in queryResultList
orderby row.Similarity ascending
select new QueryResult {
Id = row.Id,
Path = row.Path,
Duration = row.Duration,
Similarity = row.Similarity
}).Take(numToTake).ToList();
return sortedList;
}
/// <summary>
/// Find Similar Tracks to one or many audio files using their unique database id(s)
/// </summary>
/// <param name="id">an array of unique database ids for the audio files to search for similar matches</param>
/// <param name="exclude">an array of unique database ids to ignore (normally the same as the id array)</param>
/// <param name="db">database</param>
/// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param>
/// <param name="numToTake">max number of entries to return</param>
/// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param>
/// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param>
/// <returns>a dictinary list of key value pairs (filepath and distance)</returns>
public static Dictionary<KeyValuePair<int, string>, double> SimilarTracks(int[] id, int[] exclude, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence)
{
DbgTimer t = new DbgTimer();
t.Start();
AudioFeature[] seedAudioFeatures = null;
AudioFeature[] audioFeatures = null;
switch (analysisMethod) {
case Analyzer.AnalysisMethod.MandelEllis:
seedAudioFeatures = new MandelEllis[id.Length];
audioFeatures = new MandelEllis[100];
break;
case Analyzer.AnalysisMethod.SCMS:
seedAudioFeatures = new Scms[id.Length];
audioFeatures = new Scms[100];
break;
}
for (int i = 0; i < seedAudioFeatures.Length; i++) {
seedAudioFeatures[i] = db.GetTrack(id[i], analysisMethod);
}
// Get all tracks from the DB except the seedSongs
IDataReader r = db.GetTracks(exclude, seedAudioFeatures[0].Duration, percentage);
// store results in a dictionary
var NameDictionary = new Dictionary<KeyValuePair<int, string>, double>();
int[] mapping = new int[100];
int read = 1;
double d;
double dcur;
float count;
while (read > 0) {
read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod);
for (int i = 0; i < read; i++) {
d = 0;
count = 0;
for (int j = 0; j < seedAudioFeatures.Length; j++) {
dcur = seedAudioFeatures[j].GetDistance(audioFeatures[i], distanceType);
// convert to positive values
dcur = Math.Abs(dcur);
d += dcur;
count++;
}
if (d > 0) {
NameDictionary.Add(new KeyValuePair<int,string>(mapping[i], audioFeatures[i].Name), d/count);
//NameDictionary.Add(new KeyValuePair<int,string>(mapping[i], String.Format("{0} ({1} ms)", audioFeatures[i].Name, audioFeatures[i].Duration)), d/count);
}
}
}
// sort by non unique values
var sortedDict = (from entry in NameDictionary orderby entry.Value ascending select entry)
.Take(numToTake)
.ToDictionary(pair => pair.Key, pair => pair.Value);
Console.Out.WriteLine(String.Format("Found Similar to ({0}) in {1} ms", String.Join(",", seedAudioFeatures.Select(p=>p.Name)), t.Stop().TotalMilliseconds));
return sortedDict;
}
/// <summary>
/// Find Similar Tracks to an audio file using its file path
/// </summary>
/// <param name="searchForPath">audio file path</param>
/// <param name="db">database</param>
/// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param>
/// <param name="numToTake">max number of entries to return</param>
/// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param>
/// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param>
/// <returns>a list of query results</returns>
public static List<FindSimilar.QueryResult> SimilarTracksList(string searchForPath, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence) {
FileInfo fi = new FileInfo(searchForPath);
AudioFeature seedAudioFeature = null;
AudioFeature[] audioFeatures = null;
switch (analysisMethod) {
case Analyzer.AnalysisMethod.MandelEllis:
seedAudioFeature = Analyzer.AnalyzeMandelEllis(fi);
audioFeatures = new MandelEllis[100];
break;
case Analyzer.AnalysisMethod.SCMS:
seedAudioFeature = Analyzer.AnalyzeScms(fi);
audioFeatures = new Scms[100];
break;
}
// Get all tracks from the DB except the seedSongs
IDataReader r = db.GetTracks(null, seedAudioFeature.Duration, percentage);
// store results in a query results list
List<FindSimilar.QueryResult> queryResultList = new List<FindSimilar.QueryResult>();
int[] mapping = new int[100];
int read = 1;
double dcur;
while (read > 0) {
read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod);
for (int i = 0; i < read; i++) {
dcur = seedAudioFeature.GetDistance(audioFeatures[i], distanceType);
// convert to positive values
dcur = Math.Abs(dcur);
QueryResult queryResult = new QueryResult();
queryResult.Id = mapping[i];
queryResult.Path = audioFeatures[i].Name;
queryResult.Duration = audioFeatures[i].Duration;
queryResult.Similarity = dcur;
queryResultList.Add(queryResult);
}
}
var sortedList = (from row in queryResultList
orderby row.Similarity ascending
select new QueryResult {
Id = row.Id,
Path = row.Path,
Duration = row.Duration,
Similarity = row.Similarity
}).Take(numToTake).ToList();
return sortedList;
}
/// <summary>
/// Find Similar Tracks to an audio file using its file path
/// </summary>
/// <param name="searchForPath">audio file path</param>
/// <param name="db">database</param>
/// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param>
/// <param name="numToTake">max number of entries to return</param>
/// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param>
/// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param>
/// <returns>a dictinary list of key value pairs (filepath and distance)</returns>
public static Dictionary<KeyValuePair<int, string>, double> SimilarTracks(string searchForPath, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence)
{
DbgTimer t = new DbgTimer();
t.Start();
FileInfo fi = new FileInfo(searchForPath);
AudioFeature seedAudioFeature = null;
AudioFeature[] audioFeatures = null;
switch (analysisMethod) {
case Analyzer.AnalysisMethod.MandelEllis:
seedAudioFeature = Analyzer.AnalyzeMandelEllis(fi);
audioFeatures = new MandelEllis[100];
break;
case Analyzer.AnalysisMethod.SCMS:
seedAudioFeature = Analyzer.AnalyzeScms(fi);
audioFeatures = new Scms[100];
break;
}
// Get all tracks from the DB except the seedSongs
IDataReader r = db.GetTracks(null, seedAudioFeature.Duration, percentage);
// store results in a dictionary
var NameDictionary = new Dictionary<KeyValuePair<int, string>, double>();
int[] mapping = new int[100];
int read = 1;
double dcur;
while (read > 0) {
read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod);
for (int i = 0; i < read; i++) {
dcur = seedAudioFeature.GetDistance(audioFeatures[i], distanceType);
// convert to positive values
dcur = Math.Abs(dcur);
NameDictionary.Add(new KeyValuePair<int,string>(mapping[i], audioFeatures[i].Name), dcur);
}
}
// sort by non unique values
var sortedDict = (from entry in NameDictionary orderby entry.Value ascending select entry)
.Take(numToTake)
.ToDictionary(pair => pair.Key, pair => pair.Value);
Console.Out.WriteLine(String.Format("Found Similar to ({0}) in {1} ms", seedAudioFeature.Name, t.Stop().TotalMilliseconds));
return sortedDict;
}
public static AudioFeature FromBytesXML(byte[] buf) {
String xmlData = StringUtils.GetString(buf);
XmlTextReader xmlTextReader = new XmlTextReader(new StringReader(xmlData));
MandelEllis mandelEllis = new MandelEllis();
mandelEllis.ReadXML(xmlTextReader);
return mandelEllis;
}
public static AudioFeature FromBytesCompressed(byte[] byteArray)
{
using (Stream stream = new MemoryStream(byteArray)) {
Matrix mean = Matrix.LoadBinary(stream);
Matrix covarMatrix = Matrix.LoadBinary(stream);
Matrix covarMatrixInv = Matrix.LoadBinary(stream);
stream.Flush();
MandelEllis.GmmMe gmmme = new MandelEllis.GmmMe(mean, covarMatrix, covarMatrixInv);
var mandelEllis = new MandelEllis(gmmme);
return mandelEllis;
}
}
