public void HammingSimilarityIsSummedUpAccrossAllSubFingerprintsTest()
{
long[] buckets = new long[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
var queryHash = new HashData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 11 }, buckets);
const int DefaultThreshold = 5;
const int FirstTrackId = 20;
const int FirstSubFingerprintId = 10;
const int SecondSubFingerprintId = 11;
var firstTrackReference = new ModelReference <int>(FirstTrackId);
SubFingerprintData firstResult = new SubFingerprintData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 }, new ModelReference <int>(FirstSubFingerprintId), firstTrackReference);
SubFingerprintData secondResult = new SubFingerprintData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 10, 12 }, new ModelReference <int>(SecondSubFingerprintId), firstTrackReference);
modelService.Setup(service => service.ReadSubFingerprintDataByHashBucketsWithThreshold(buckets, DefaultThreshold))
.Returns(new List <SubFingerprintData> {
firstResult, secondResult
});
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference))
.Returns(new TrackData {
ISRC = "isrc", TrackReference = firstTrackReference
});
var queryResult = queryFingerprintService.Query(new List <HashData> {
queryHash
}, new DefaultQueryConfiguration());
Assert.IsTrue(queryResult.IsSuccessful);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(9 + 8, queryResult.BestMatch.Similarity);
Assert.AreEqual(1, queryResult.AnalyzedCandidatesCount);
Assert.AreEqual(1, queryResult.ResultEntries.Count);
}
protected MetaCompilation Compile(string filePath, bool assertEmptyDiagnostics = true, bool compileMetaModelCore = false)
{
MetaDescriptor.Initialize();
string text = File.ReadAllText(filePath);
var st = MetaSyntaxTree.ParseText(text);
BinderFlags binderFlags = BinderFlags.IgnoreAccessibility;
if (compileMetaModelCore)
{
BinderFlags binderFlags2 = BinderFlags.IgnoreMetaLibraryDuplicatedTypes;
binderFlags = binderFlags.UnionWith(binderFlags2);
}
MetaCompilationOptions options = new MetaCompilationOptions(MetaLanguage.Instance, OutputKind.NetModule, deterministic: true, concurrentBuild: false,
topLevelBinderFlags: binderFlags);
var compilation = MetaCompilation.
Create("MetaModelCompilation").
AddSyntaxTrees(st).
AddReferences(
ModelReference.CreateFromModel(MetaInstance.MModel)
).
WithOptions(options);
compilation.ForceComplete();
if (assertEmptyDiagnostics)
{
AssertEmptyDiagnostics(compilation);
}
return(compilation);
}
public void OnlyTracksWithGroupIdAreConsideredAsPotentialCandidatesTest()
{
long[] buckets = new long[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
var queryHash = new HashData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 11 }, buckets);
const int DefaultThreshold = 5;
const int FirstTrackId = 20;
const int FirstSubFingerprintId = 10;
var firstTrackReference = new ModelReference <int>(FirstTrackId);
SubFingerprintData firstResult = new SubFingerprintData(
new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 },
new ModelReference <int>(FirstSubFingerprintId),
firstTrackReference);
modelService.Setup(
service =>
service.ReadSubFingerprintDataByHashBucketsThresholdWithGroupId(buckets, DefaultThreshold, "group-id"))
.Returns(new List <SubFingerprintData> {
firstResult
});
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference)).Returns(
new TrackData {
ISRC = "isrc", TrackReference = firstTrackReference
});
var queryResult = queryFingerprintService.Query(
new List <HashData> {
queryHash
}, new CustomQueryConfiguration {
TrackGroupId = "group-id"
});
Assert.IsTrue(queryResult.IsSuccessful);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
}
public IModelReference AddTrack(TrackData track)
{
var trackReference = new ModelReference <int>(Interlocked.Increment(ref trackReferenceCounter));
Tracks[trackReference.Id] = track;
return(track.TrackReference = trackReference);
}
public void HammingSimilarityIsSummedUpAcrossAllSubFingerprintsTest()
{
var queryHash = new HashedFingerprint(GenericHashBuckets(), 0, 0, Array.Empty <byte>());
const int firstTrackId = 20;
const int firstSubFingerprintId = 10;
const int secondSubFingerprintId = 11;
var firstTrackReference = new ModelReference <int>(firstTrackId);
var firstResult = new SubFingerprintData(GenericHashBuckets(), 1, 0, new ModelReference <int>(firstSubFingerprintId), firstTrackReference);
var secondResult = new SubFingerprintData(GenericHashBuckets(), 2, 0.928f, new ModelReference <int>(secondSubFingerprintId), firstTrackReference);
var defaultQueryConfiguration = new DefaultQueryConfiguration();
modelService.Setup(service => service.Query(
It.IsAny <Hashes>(),
It.IsAny <QueryConfiguration>())).Returns(new[] { firstResult, secondResult });
modelService.Setup(service => service.ReadTracksByReferences(new[] { firstTrackReference })).Returns(
new List <TrackData>
{
new TrackData("id", string.Empty, string.Empty, 0d, firstTrackReference)
});
var hashes = new Hashes(new List <HashedFingerprint> {
queryHash
}, 1.48f, DateTime.Now, Enumerable.Empty <string>());
var queryResult = queryFingerprintService.Query(hashes, defaultQueryConfiguration, modelService.Object);
Assert.IsTrue(queryResult.ContainsMatches);
Assert.AreEqual("id", queryResult.BestMatch.Track.Id);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(200, queryResult.BestMatch.Score);
Assert.AreEqual(1, queryResult.ResultEntries.Count());
}
public void ShouldAccumulateHammingDistanceSumForMultipleTracks()
{
const int CandidatesCount = 10000;
var trackReference0 = new ModelReference<int>(0);
var subFingerprints0 = GetSubFingerprintsForTrack(trackReference0, CandidatesCount);
var trackReference1 = new ModelReference<int>(1);
var subFingerprints1 = GetSubFingerprintsForTrack(trackReference1, CandidatesCount);
var trackReference2 = new ModelReference<int>(2);
var subFingerprints2 = GetSubFingerprintsForTrack(trackReference2, CandidatesCount);
var allSubs = subFingerprints0.Concat(subFingerprints1).Concat(subFingerprints2);
var acumulator = new ConcurrentDictionary<IModelReference, ResultEntryAccumulator>();
Parallel.ForEach(
allSubs,
new ParallelOptions { MaxDegreeOfParallelism = 10 },
sub =>
similarityUtility.AccumulateHammingSimilarity(
new List<SubFingerprintData> { sub },
new HashedFingerprint(GenericSignature(), GenericHashBuckets(), 1, 0d, Enumerable.Empty<string>()),
acumulator));
int expectedHammingSimilarity = (GenericSignature().Length * CandidatesCount) - CandidatesCount + 1;
Assert.AreEqual(expectedHammingSimilarity, acumulator[trackReference0].HammingSimilaritySum);
Assert.AreEqual(expectedHammingSimilarity, acumulator[trackReference1].HammingSimilaritySum);
Assert.AreEqual(expectedHammingSimilarity, acumulator[trackReference2].HammingSimilaritySum);
Assert.AreEqual(CandidatesCount, acumulator[trackReference0].BestMatch.SubFingerprint.SubFingerprintReference.Id);
Assert.AreEqual(CandidatesCount, acumulator[trackReference1].BestMatch.SubFingerprint.SubFingerprintReference.Id);
Assert.AreEqual(CandidatesCount, acumulator[trackReference2].BestMatch.SubFingerprint.SubFingerprintReference.Id);
}
public void HammingSimilarityIsSummedUpAccrossAllSubFingerprintsTest()
{
var queryHash = new HashedFingerprint(GenericHashBuckets(), 0, 0, Enumerable.Empty <string>());
const int FirstTrackId = 20;
const int FirstSubFingerprintId = 10;
const int SecondSubFingerprintId = 11;
var firstTrackReference = new ModelReference <int>(FirstTrackId);
var firstResult = new SubFingerprintData(GenericHashBuckets(), 1, 0, new ModelReference <int>(FirstSubFingerprintId), firstTrackReference);
var secondResult = new SubFingerprintData(GenericHashBuckets(), 2, 0.928f, new ModelReference <int>(SecondSubFingerprintId), firstTrackReference);
var defaultQueryConfiguration = new DefaultQueryConfiguration();
modelService.Setup(service => service.SupportsBatchedSubFingerprintQuery).Returns(false);
modelService.Setup(service => service.ReadSubFingerprints(It.IsAny <int[]>(), defaultQueryConfiguration))
.Returns(new List <SubFingerprintData> {
firstResult, secondResult
});
modelService.Setup(service => service.ReadTracksByReferences(new [] { firstTrackReference }))
.Returns(new List <TrackData> {
new TrackData {
ISRC = "isrc", TrackReference = firstTrackReference
}
});
var queryResult = queryFingerprintService.Query(new List <HashedFingerprint> {
queryHash
}, defaultQueryConfiguration, modelService.Object);
Assert.IsTrue(queryResult.ContainsMatches);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(200, queryResult.BestMatch.HammingSimilaritySum);
Assert.AreEqual(1, queryResult.ResultEntries.Count());
}
/// <inheritdoc />
public override BigQueryModel PatchModel(ModelReference modelReference, Model resource, PatchModelOptions options = null)
{
var request = CreatePatchModelRequest(modelReference, resource, options);
var model = request.Execute();
return(new BigQueryModel(this, model));
}
public void Compile()
{
if (_compilation == null)
{
ImmutableModel coreModel = MetaInstance.MModel;
string text = File.ReadAllText(_inputFilePath);
var tree = MetaSyntaxTree.ParseText(text, path: _inputFilePath);
BinderFlags binderFlags = BinderFlags.IgnoreAccessibility;
if (_compileMetaModelCore)
{
BinderFlags binderFlags2 = BinderFlags.IgnoreMetaLibraryDuplicatedTypes;
binderFlags = binderFlags.UnionWith(binderFlags2);
}
MetaCompilationOptions options = new MetaCompilationOptions(MetaLanguage.Instance, OutputKind.NetModule, deterministic: true, concurrentBuild: true,
topLevelBinderFlags: binderFlags);
//MetaCompilationOptions options = new MetaCompilationOptions(MetaLanguage.Instance, OutputKind.NetModule, deterministic: true, concurrentBuild: false);
var compilation = MetaCompilation.
Create("MetaModelCompilation").
AddSyntaxTrees(tree).
AddReferences(
ModelReference.CreateFromModel(coreModel)
).
WithOptions(options);
Interlocked.CompareExchange(ref _compilation, compilation, null);
}
_compilation.ForceComplete();
}
public IModelReference InsertTrack(TrackData track)
{
var trackReference = new ModelReference <int>(Interlocked.Increment(ref counter));
storage.Tracks[trackReference] = track;
return(track.TrackReference = trackReference);
}
/// <inheritdoc />
public override BigQueryModel GetModel(ModelReference modelReference, GetModelOptions options = null)
{
var request = CreateGetModelRequest(modelReference, options);
var resource = request.Execute();
return(new BigQueryModel(this, resource));
}
public void ShouldInsertEntriesInThreadSafeManner()
{
var storage = new RAMStorage(50);
var hashConverter = new HashConverter();
var hashes = Enumerable.Range(0, 100).Select(b => (byte)b).ToArray();
var longs = hashConverter.ToInts(hashes, 25);
int tracksCount = 520;
int subFingerprintsPerTrack = 33;
float one = 8192f / 5512;
Parallel.For(0, tracksCount, i =>
{
var trackReference = new ModelReference <int>(i);
for (int j = 0; j < subFingerprintsPerTrack; ++j)
{
var hashed = new HashedFingerprint(longs, (uint)j, j * one, Array.Empty <byte>());
storage.AddHashedFingerprint(hashed, trackReference);
}
});
for (int i = 0; i < 25; ++i)
{
var subFingerprints = storage.GetSubFingerprintsByHashTableAndHash(i, longs[i]);
Assert.AreEqual(tracksCount * subFingerprintsPerTrack, subFingerprints.Count);
}
}
public void HammingSimilarityIsSummedUpAccrossAllSubFingerprintsTest()
{
long[] buckets = new long[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
var queryHash = new HashData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 11 }, buckets);
const int DefaultThreshold = 5;
const int FirstTrackId = 20;
const int FirstSubFingerprintId = 10;
const int SecondSubFingerprintId = 11;
var firstTrackReference = new ModelReference<int>(FirstTrackId);
SubFingerprintData firstResult = new SubFingerprintData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 }, new ModelReference<int>(FirstSubFingerprintId), firstTrackReference);
SubFingerprintData secondResult = new SubFingerprintData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 10, 12 }, new ModelReference<int>(SecondSubFingerprintId), firstTrackReference);
modelService.Setup(service => service.ReadSubFingerprintDataByHashBucketsWithThreshold(buckets, DefaultThreshold))
.Returns(new List<SubFingerprintData> { firstResult, secondResult });
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference))
.Returns(new TrackData { ISRC = "isrc", TrackReference = firstTrackReference });
var queryResult = queryFingerprintService.Query(modelService.Object, new List<HashData> { queryHash }, new DefaultQueryConfiguration());
Assert.IsTrue(queryResult.IsSuccessful);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(9 + 8, queryResult.BestMatch.Similarity);
Assert.AreEqual(1, queryResult.AnalyzedCandidatesCount);
Assert.AreEqual(1, queryResult.ResultEntries.Count);
}
public void SameQueryHashGeneratesMultipleTrackMatches()
{
var groupedQueryResults = new GroupedQueryResults(10d, DateTime.Now);
var random = new Random(1);
int runs = 100;
int[] counts = new int[runs];
var trackRef = new ModelReference <uint>(1);
int k = 0;
Parallel.For(0, runs, i =>
{
counts[i] = random.Next(5, 10);
var queryPoint = new HashedFingerprint(new int[25], (uint)i, i * 1.48f, Array.Empty <byte>());
for (int j = 0; j < counts[i]; ++j)
{
var dbPoint = new SubFingerprintData(new int[25], (uint)k, k * 0.01f, new ModelReference <uint>((uint)Interlocked.Increment(ref k)), trackRef);
groupedQueryResults.Add(queryPoint, dbPoint, i);
}
});
var allMatches = groupedQueryResults.GetMatchesForTrack(trackRef).ToList();
Assert.AreEqual(counts.Sum(), allMatches.Count);
Assert.AreEqual(runs, allMatches.Select(m => m.QuerySequenceNumber).Distinct().Count());
}
public void DistributionOfHashesHasToBeUniform()
{
var lshAlgorithm = LocalitySensitiveHashingAlgorithm.Instance;
var random = new Random();
var storage = new RAMStorage(25);
float one = 8192f / 5512;
var config = new DefaultHashingConfig {
NumberOfLSHTables = 25, NumberOfMinHashesPerTable = 4, HashBuckets = 0
};
var track = new ModelReference <int>(1);
int l = 100000;
for (int i = 0; i < l; ++i)
{
var schema = TestUtilities.GenerateRandomFingerprint(random, 200, 128, 32);
var hash = lshAlgorithm.Hash(new Fingerprint(schema, i * one, (uint)i, Array.Empty <byte>()), config);
var subFingerprint = new SubFingerprintData(hash.HashBins, hash.SequenceNumber, hash.StartsAt, new ModelReference <uint>((uint)i), track);
storage.AddSubFingerprint(subFingerprint);
}
var distribution = storage.HashCountsPerTable;
foreach (var hashPerTable in distribution)
{
double collisions = (double)(l - hashPerTable) / l;
Assert.IsTrue(collisions <= 0.01d, $"Less than 1% of collisions across 100K hashes: {collisions}");
}
}
public void HammingSimilarityIsSummedUpAccrossAllSubFingerprintsTest()
{
var queryHash = new HashedFingerprint(GenericSignature(), GenericHashBuckets(), 0, 0, Enumerable.Empty<string>());
const int FirstTrackId = 20;
const int FirstSubFingerprintId = 10;
const int SecondSubFingerprintId = 11;
var firstTrackReference = new ModelReference<int>(FirstTrackId);
var firstResult = new SubFingerprintData(GenericHashBuckets(), 1, 0, new ModelReference<int>(FirstSubFingerprintId), firstTrackReference);
var secondResult = new SubFingerprintData(GenericHashBuckets(), 2, 0.928, new ModelReference<int>(SecondSubFingerprintId), firstTrackReference);
var defaultQueryConfiguration = new DefaultQueryConfiguration();
modelService.Setup(service => service.SupportsBatchedSubFingerprintQuery).Returns(false);
modelService.Setup(service => service.ReadSubFingerprints(It.IsAny<long[]>(), defaultQueryConfiguration))
.Returns(new List<SubFingerprintData> { firstResult, secondResult });
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference))
.Returns(new TrackData { ISRC = "isrc", TrackReference = firstTrackReference });
var queryResult = queryFingerprintService.Query(new List<HashedFingerprint> { queryHash }, defaultQueryConfiguration, modelService.Object);
Assert.IsTrue(queryResult.ContainsMatches);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(GenericSignature().Length * 2, queryResult.BestMatch.HammingSimilaritySum);
Assert.AreEqual(1, queryResult.ResultEntries.Count());
}
public void FingerprintsCantMatchUniformlyAtRandom()
{
var lshAlgorithm = LocalitySensitiveHashingAlgorithm.Instance;
var random = new Random();
var storage = new RAMStorage(25);
float one = 8192f / 5512;
var config = new DefaultHashingConfig {
NumberOfLSHTables = 25, NumberOfMinHashesPerTable = 4, HashBuckets = 0
};
var track = new ModelReference <int>(1);
for (int i = 0; i < 100; ++i)
{
var schema = TestUtilities.GenerateRandomFingerprint(random, 200, 128, 32);
var hash = lshAlgorithm.Hash(new Fingerprint(schema, i * one, (uint)i, Array.Empty <byte>()), config);
var subFingerprint = new SubFingerprintData(hash.HashBins, hash.SequenceNumber, hash.StartsAt, new ModelReference <uint>((uint)i), track);
storage.AddSubFingerprint(subFingerprint);
}
for (int i = 0; i < 10; ++i)
{
var schema = TestUtilities.GenerateRandomFingerprint(random, 200, 128, 32);
var hash = lshAlgorithm.Hash(new Fingerprint(schema, i * one, (uint)i, Array.Empty <byte>()), config);
for (int j = 0; j < 25; ++j)
{
var ids = storage.GetSubFingerprintsByHashTableAndHash(j, hash.HashBins[j]);
Assert.IsFalse(ids.Any());
}
}
}
/// <inheritdoc />
public override async Task <BigQueryModel> PatchModelAsync(ModelReference modelReference, Model resource, PatchModelOptions options = null, CancellationToken cancellationToken = default)
{
var request = CreatePatchModelRequest(modelReference, resource, options);
var model = await request.ExecuteAsync().ConfigureAwait(false);
return(new BigQueryModel(this, model));
}
public void ShouldSerializeSpectralImages()
{
var spectrumService = new SpectrumService(new LomontFFT(), new LogUtility());
var spectrums = spectrumService.CreateLogSpectrogram(GetAudioSamples(), new DefaultSpectrogramConfig())
.Select(spectrum => spectrum.ImageRowCols)
.ToList();
var modelService = new InMemoryModelService();
var trackReference = new ModelReference <int>(10);
modelService.InsertSpectralImages(spectrums, trackReference);
var tempFile = Path.GetTempFileName();
modelService.Snapshot(tempFile);
var fromFileService = new InMemoryModelService(tempFile);
File.Delete(tempFile);
var allSpectrums = fromFileService.GetSpectralImagesByTrackReference(trackReference).ToList();
Assert.AreEqual(spectrums.Count, allSpectrums.Count);
}
private static void SetModel(Entity entity, ModelReference model)
{
entity.MetaData.Set(ModelMetaKey, model);
entity.MetaData.Set(ModelNameMetaKey, GetModelName(entity));
entity.MetaData.Set(ModelBoundingBoxMetaKey, model.Model.GetBoundingBox());
entity.UpdateBoundingBox();
}
/// <summary>
/// Stores the fingerprints of the given file into the ModelService.
/// Uses HighPrecisionFingerprintConfiguration.
/// </summary>
/// <param name="waveFile"></param>
private void StoreNewAudioFileData(IAudioFile waveFile)
{
TrackData track = new TrackData(
isrc: "TD100INPROG", // International Standart Recording Code.
artist: "The TD's",
title: waveFile.FilePath.NameWithoutExtension,
album: waveFile.FilePath.DirectoryPath,
releaseYear: DateTime.Today.Year,
length: waveFile.DurationInSeconds);
// Stores track metadata in the datasource.
//TRack trackReference = new TrackReference<int>(mModelService.InsertTrack(track).Id);
IModelReference trackReference = mModelService.InsertTrack(track);
ModelReference <int> trackReference2 = trackReference as ModelReference <int>;
// Creates hashed fingerprints.
List <HashedFingerprint> hashedFingerprints = FingerprintCommandBuilder.Instance
.BuildFingerprintCommand()
.From(waveFile.FilePath.FileFullPath)
.WithFingerprintConfig(new DefaultFingerprintConfiguration())
.UsingServices(mAudioService)
.Hash()
.Result;
// Stores hashes in the database.
//SaveFingerPrintsInMemory(hashedFingerprints, trackReference2, waveFile.FilePath.NameWithoutExtension); // Currenntly not using fp.
mModelService.InsertHashDataForTrack(hashedFingerprints, trackReference);
mLogger.WriteLine($"Stored {hashedFingerprints.Count} hashed fingerprints from {waveFile.FilePath.Name}");
}
public void ShouldReturnEmptySinceNoSpectralImagesArePresentForTrack()
{
var trackReference = new ModelReference<int>(10);
var results = spectralImageDao.GetSpectralImagesByTrackReference(trackReference);
Assert.IsEmpty(results);
}
private DeleteRequest CreateDeleteModelRequest(ModelReference modelReference, DeleteModelOptions options)
{
GaxPreconditions.CheckNotNull(modelReference, nameof(modelReference));
var request = Service.Models.Delete(modelReference.ProjectId, modelReference.DatasetId, modelReference.ModelId);
options?.ModifyRequest(request);
return(request);
}
public void ShouldReturnEmptySinceNoSpectralImagesArePresentForTrack()
{
var trackReference = new ModelReference <int>(10);
var results = spectralImageDao.GetSpectralImagesByTrackReference(trackReference);
Assert.IsEmpty(results);
}
public void MaximumNumberOfReturnedTracksIsLessThanAnalyzedCandidatesResultsTest()
{
long[] buckets = new long[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
var queryHash = new HashData(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 11 }, buckets);
const int DefaultThreshold = 5;
const int FirstTrackId = 20;
const int SecondTrackId = 21;
const int ThirdTrackId = 22;
const int FirstSubFingerprintId = 10;
const int SecondSubFingerprintId = 11;
var firstTrackReference = new ModelReference <int>(FirstTrackId);
var thirdTrackReference = new ModelReference <int>(ThirdTrackId);
SubFingerprintData firstResult = new SubFingerprintData(
new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 },
new ModelReference <int>(FirstSubFingerprintId),
firstTrackReference);
SubFingerprintData secondResult = new SubFingerprintData(
new byte[] { 11, 2, 13, 4, 15, 6, 7, 8, 10, 12 },
new ModelReference <int>(SecondSubFingerprintId),
new ModelReference <int>(SecondTrackId));
SubFingerprintData thirdResult = new SubFingerprintData(
new byte[] { 1, 2, 3, 4, 5, 15, 7, 8, 10, 12 },
new ModelReference <int>(SecondSubFingerprintId),
new ModelReference <int>(ThirdTrackId));
modelService.Setup(
service => service.ReadSubFingerprintDataByHashBucketsWithThreshold(buckets, DefaultThreshold)).Returns(
new List <SubFingerprintData> {
firstResult, secondResult, thirdResult
});
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference)).Returns(
new TrackData {
ISRC = "isrc", TrackReference = firstTrackReference
});
modelService.Setup(service => service.ReadTrackByReference(thirdTrackReference)).Returns(
new TrackData {
ISRC = "isrc_2", TrackReference = thirdTrackReference
});
var queryResult = queryFingerprintService.Query(
modelService.Object,
new List <HashData> {
queryHash
},
new CustomQueryConfiguration
{
MaximumNumberOfTracksToReturnAsResult = 2, ThresholdVotes = DefaultThreshold
});
Assert.IsTrue(queryResult.IsSuccessful);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(9, queryResult.BestMatch.Similarity);
Assert.AreEqual(3, queryResult.AnalyzedCandidatesCount);
Assert.AreEqual(2, queryResult.ResultEntries.Count);
Assert.AreEqual(firstTrackReference, queryResult.ResultEntries[0].Track.TrackReference);
Assert.AreEqual(thirdTrackReference, queryResult.ResultEntries[1].Track.TrackReference);
}
public void LevelChanged(MsdLevelChangeType ChangeType, Level TheLevel, ModelReference TheModel)
{
if (MsdLevelChangeType.AfterCreate == ChangeType ||
MsdLevelChangeType.AfterDelete == ChangeType ||
MsdLevelChangeType.ChangeName == ChangeType)
{
PopulateLevelList();
}
}
public void MaximumNumberOfReturnedTracksIsLessThanAnalyzedCandidatesResultsTest()
{
long[] buckets = new long[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
var queryHash = new HashedFingerprint(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 11 }, buckets, 1, 0);
const int DefaultThreshold = 5;
const int FirstTrackId = 20;
const int SecondTrackId = 21;
const int ThirdTrackId = 22;
const int FirstSubFingerprintId = 10;
const int SecondSubFingerprintId = 11;
var firstTrackReference = new ModelReference<int>(FirstTrackId);
var thirdTrackReference = new ModelReference<int>(ThirdTrackId);
var firstResult = new SubFingerprintData(
new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 },
1,
0,
new ModelReference<int>(FirstSubFingerprintId),
firstTrackReference);
SubFingerprintData secondResult = new SubFingerprintData(
new byte[] { 11, 2, 13, 4, 15, 6, 7, 8, 10, 12 },
2,
0.928,
new ModelReference<int>(SecondSubFingerprintId),
new ModelReference<int>(SecondTrackId));
SubFingerprintData thirdResult = new SubFingerprintData(
new byte[] { 1, 2, 3, 4, 5, 15, 7, 8, 10, 12 },
3,
0.928 * 2,
new ModelReference<int>(SecondSubFingerprintId),
new ModelReference<int>(ThirdTrackId));
modelService.Setup(
service => service.ReadSubFingerprintDataByHashBucketsWithThreshold(buckets, DefaultThreshold)).Returns(
new List<SubFingerprintData> { firstResult, secondResult, thirdResult });
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference)).Returns(
new TrackData { ISRC = "isrc", TrackReference = firstTrackReference });
modelService.Setup(service => service.ReadTrackByReference(thirdTrackReference)).Returns(
new TrackData { ISRC = "isrc_2", TrackReference = thirdTrackReference });
var queryResult = queryFingerprintService.Query(
modelService.Object,
new List<HashedFingerprint> { queryHash },
new CustomQueryConfiguration
{
MaximumNumberOfTracksToReturnAsResult = 2, ThresholdVotes = DefaultThreshold
});
Assert.IsTrue(queryResult.IsSuccessful);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(9, queryResult.BestMatch.Similarity);
Assert.AreEqual(3, queryResult.AnalyzedCandidatesCount);
Assert.AreEqual(2, queryResult.ResultEntries.Count);
Assert.AreEqual(firstTrackReference, queryResult.ResultEntries[0].Track.TrackReference);
Assert.AreEqual(thirdTrackReference, queryResult.ResultEntries[1].Track.TrackReference);
}
private PatchRequest CreatePatchModelRequest(ModelReference modelReference, Model resource, PatchModelOptions options)
{
GaxPreconditions.CheckNotNull(modelReference, nameof(modelReference));
GaxPreconditions.CheckNotNull(resource, nameof(resource));
var request = Service.Models.Patch(resource, modelReference.ProjectId, modelReference.DatasetId, modelReference.ModelId);
options?.ModifyRequest(request);
RetryIfETagPresent(request, resource);
return(request);
}
private GetRequest CreateGetModelRequest(ModelReference modelReference, GetModelOptions options)
{
GaxPreconditions.CheckNotNull(modelReference, nameof(modelReference));
var request = Service.Models.Get(modelReference.ProjectId, modelReference.DatasetId, modelReference.ModelId);
options?.ModifyRequest(request);
RetryHandler.MarkAsRetriable(request);
return(request);
}
public static String GenererReference(String element)
{
ModelReference model = SearchModelReference(element);
if ((model != null) ? model.Id > 0 : false)
{
return(ReferenceElement(model));
}
Messages.ShowErreur("Cet élément n'a pas de modele de reference!");
return("");
}
/// <summary>
/// Finds a model reference (0x14) with the given name
/// </summary>
/// <param name="modelName">The model actor name</param>
/// <param name="modelReference">The out reference parameter</param>
/// <returns>Whether or not we have found the model</returns>
private bool FindModelReference(string modelName, out ModelReference modelReference)
{
if (!_fragmentNameDictionary.ContainsKey(modelName))
{
modelReference = null;
return(false);
}
modelReference = _fragmentNameDictionary[modelName] as ModelReference;
return(true);
}
public void DeleteOneTrackTest()
{
var trackReference = new ModelReference <int>(101);
var track = GetTrack(trackReference);
trackDao.InsertTrack(track);
trackDao.DeleteTrack(trackReference);
Assert.IsEmpty(trackDao.ReadTracksByReferences(new [] { trackReference }));
}
public void ReadTrackByIdTest()
{
var trackReference = new ModelReference <int>(101);
var expectedTrack = GetTrack(trackReference, 10);
trackDao.InsertTrack(expectedTrack);
TrackData actualTrack = trackDao.ReadTrackById(expectedTrack.Id);
AssertTracksAreEqual(expectedTrack, actualTrack);
}
public int Insert(TrackData track)
{
int id = PrepareStoredProcedure(SpInsertTrack)
.WithParametersFromModel(track)
.Execute()
.AsScalar <int>();
var trackReference = new ModelReference <int>(id);
track.TrackReference = trackReference;
return(id);
}
public IModelReference InsertSubFingerprint(byte[] signature, int sequenceNumber, double sequenceAt, IModelReference trackReference)
{
var subFingerprintReference = new ModelReference<long>(Interlocked.Increment(ref counter));
storage.SubFingerprints[subFingerprintReference] = new SubFingerprintData(signature, sequenceNumber, sequenceAt, subFingerprintReference, trackReference);
if (!storage.TracksHashes.ContainsKey(trackReference))
{
storage.TracksHashes[trackReference] = new ConcurrentDictionary<IModelReference, HashedFingerprint>();
}
storage.TracksHashes[trackReference][subFingerprintReference] = new HashedFingerprint(signature, null, sequenceNumber, sequenceAt);
return subFingerprintReference;
}
public void ShouldSerializeModelReference()
{
var @ref = new ModelReference <int>(42);
using var stream = new MemoryStream();
Serializer.SerializeWithLengthPrefix <IModelReference>(stream, @ref, PrefixStyle.Fixed32);
byte[] serialized = stream.ToArray();
using var deserializedStream = new MemoryStream(serialized);
var reference = Serializer.DeserializeWithLengthPrefix <IModelReference>(deserializedStream, PrefixStyle.Fixed32);
Assert.NotNull(reference);
}
public IModelReference InsertSubFingerprint(byte[] signature, IModelReference trackReference)
{
var subFingerprintReference = new ModelReference<long>(Interlocked.Increment(ref counter));
storage.SubFingerprints[subFingerprintReference] = new SubFingerprintData(signature, subFingerprintReference, trackReference);
if (!storage.TracksHashes.ContainsKey(trackReference))
{
storage.TracksHashes[trackReference] = new ConcurrentDictionary<IModelReference, HashData>();
}
storage.TracksHashes[trackReference][subFingerprintReference] = new HashData { SubFingerprint = signature };
return subFingerprintReference;
}
public void MaximumNumberOfReturnedTracksIsLessThanAnalyzedCandidatesResultsTest()
{
var queryHash = new HashedFingerprint(GenericSignature(), GenericHashBuckets(), 1, 0, Enumerable.Empty<string>());
const int DefaultThreshold = 5;
const int FirstTrackId = 20;
const int SecondTrackId = 21;
const int ThirdTrackId = 22;
const int FirstSubFingerprintId = 10;
const int SecondSubFingerprintId = 11;
var firstTrackReference = new ModelReference<int>(FirstTrackId);
var secondTrackReference = new ModelReference<int>(SecondTrackId);
var firstResult = new SubFingerprintData(
GenericHashBuckets(),
1,
0,
new ModelReference<int>(FirstSubFingerprintId),
firstTrackReference);
var secondResult = new SubFingerprintData(
GenericHashBuckets(),
2,
0.928,
new ModelReference<int>(SecondSubFingerprintId),
secondTrackReference);
var thirdResult = new SubFingerprintData(
GenericHashBuckets(),
3,
0.928 * 2,
new ModelReference<int>(SecondSubFingerprintId),
new ModelReference<int>(ThirdTrackId));
var customQueryConfiguration = new DefaultQueryConfiguration { MaxTracksToReturn = 2, ThresholdVotes = DefaultThreshold };
modelService.Setup(service => service.SupportsBatchedSubFingerprintQuery).Returns(false);
modelService.Setup(
service => service.ReadSubFingerprints(It.IsAny<long[]>(), customQueryConfiguration)).Returns(
new List<SubFingerprintData> { firstResult, secondResult, thirdResult });
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference)).Returns(
new TrackData { ISRC = "isrc", TrackReference = firstTrackReference });
modelService.Setup(service => service.ReadTrackByReference(secondTrackReference)).Returns(
new TrackData { ISRC = "isrc_1", TrackReference = secondTrackReference });
var queryResult = queryFingerprintService.Query(new List<HashedFingerprint> { queryHash }, customQueryConfiguration, modelService.Object);
Assert.IsTrue(queryResult.ContainsMatches);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
Assert.AreEqual(50, queryResult.BestMatch.HammingSimilaritySum);
Assert.AreEqual(2, queryResult.ResultEntries.Count());
var results = queryResult.ResultEntries.ToList();
Assert.AreEqual(firstTrackReference, results[0].Track.TrackReference);
Assert.AreEqual(secondTrackReference, results[1].Track.TrackReference);
}
public void ShouldAccumulateHammingDistanceSum()
{
const int CandidatesCount = 5;
var trackReference = new ModelReference<int>(0);
var subFingerprints = GetSubFingerprintsForTrack(trackReference, CandidatesCount);
var acumulator = new ConcurrentDictionary<IModelReference, ResultEntryAccumulator>();
similarityUtility.AccumulateHammingSimilarity(subFingerprints, new HashedFingerprint(GenericSignature(), GenericHashBuckets(), 1, 0d, Enumerable.Empty<string>()), acumulator);
int expectedHammingSimilaritySum = (GenericSignature().Length * CandidatesCount) - CandidatesCount + 1;
Assert.AreEqual(expectedHammingSimilaritySum, acumulator[trackReference].HammingSimilaritySum);
Assert.AreEqual(CandidatesCount, acumulator[trackReference].BestMatch.SubFingerprint.SubFingerprintReference.Id);
}
public void ShouldInsertSpectralImages()
{
var images = new List<float[]>() { new float[0], new float[0], new float[0] };
var trackReference = new ModelReference<int>(10);
spectralImageDao.InsertSpectralImages(images, trackReference);
Assert.AreEqual(3, spectralImageDao.GetSpectralImagesByTrackReference(trackReference).Count());
var ids =
spectralImageDao.GetSpectralImagesByTrackReference(trackReference)
.Select(dto => (int)dto.SpectralImageReference.Id)
.ToList();
CollectionAssert.AreEqual(Enumerable.Range(1, 3), ids);
}
public void ShouldGetBestCandidatesByHammingDistance()
{
var modelService = new Mock<IModelService>(MockBehavior.Strict);
var trackReference = new ModelReference<int>(3);
modelService.Setup(s => s.ReadTrackByReference(trackReference)).Returns(
new TrackData { ISRC = "isrc-1234-1234" });
var queryConfiguration = new DefaultQueryConfiguration { MaxTracksToReturn = 1 };
var query = new List<HashedFingerprint>
{
new HashedFingerprint(null, null, 1, 0d, Enumerable.Empty<string>()),
new HashedFingerprint(null, null, 1, 4d, Enumerable.Empty<string>()),
new HashedFingerprint(null, null, 1, 8d, Enumerable.Empty<string>())
};
var first = new ResultEntryAccumulator(query[0], new SubFingerprintData(null, 1, 0d, null, null), 100);
var second = new ResultEntryAccumulator(query[1], new SubFingerprintData(null, 1, 4d, null, null), 99);
var third = new ResultEntryAccumulator(query[2], new SubFingerprintData(null, 1, 8d, null, null), 101);
var hammingSimilarties = new Dictionary<IModelReference, ResultEntryAccumulator>
{
{ new ModelReference<int>(1), first },
{ new ModelReference<int>(2), second },
{ new ModelReference<int>(3), third },
};
var best = queryMath.GetBestCandidates(
query,
hammingSimilarties,
queryConfiguration.MaxTracksToReturn,
modelService.Object,
queryConfiguration.FingerprintConfiguration);
Assert.AreEqual(1, best.Count);
Assert.AreEqual("isrc-1234-1234", best[0].Track.ISRC);
Assert.AreEqual(9.48d, best[0].QueryLength, 0.01);
Assert.AreEqual(0d, best[0].TrackStartsAt);
modelService.VerifyAll();
}
public void ShouldSortMatchesProperly()
{
List<SubFingerprintData> subFingerprints = new List<SubFingerprintData>();
var trackReference = new ModelReference<int>(0);
const double OneFingerprintLength = 1.0d;
const int CandidatesCount = 20;
for (int i = 0; i < CandidatesCount; ++i)
{
var sub = new SubFingerprintData(GenericHashBuckets(), i, OneFingerprintLength * (CandidatesCount - i), new ModelReference<int>(i), trackReference);
subFingerprints.Add(sub);
}
var acumulator = new ConcurrentDictionary<IModelReference, ResultEntryAccumulator>();
similarityUtility.AccumulateHammingSimilarity(subFingerprints, new HashedFingerprint(GenericSignature(), GenericHashBuckets(), 1, 0d, Enumerable.Empty<string>()), acumulator);
var expected = Enumerable.Range(1, 20);
var actual = acumulator[trackReference].Matches.Select(m => m.SubFingerprint.SequenceAt).ToList();
CollectionAssert.AreEqual(expected, actual);
}
public void RenderModel(WLD modelWld,ModelReference model,int textureNumber=0,int headNumber=0,int face=0)
{
var wld = modelWld;
TrackAnimationBuilder animation = null;
List<MeshReference> meshrefs = new List<MeshReference>();
foreach (var refs in model.References)
{
var meshref = wld.MeshReferences.Where(x => x.FragmentNumber == refs).FirstOrDefault();
if (meshref != null)
{
meshrefs.Add(meshref);
continue;
}
var skel = wld.SkeletonTrackReferences.Where(x => x.FragmentNumber == refs).FirstOrDefault();
if (skel != null)
{
var skelset = wld.SkeletonTrackSet.Where(x => x.FragmentNumber == skel.SkeletonTrackSetReference).FirstOrDefault();
if (skelset != null)
{
animation = new TrackAnimationBuilder(skelset, wld);
foreach (var ms in skelset.MeshReferences)
{
var m = wld.MeshReferences.Where(x => x.FragmentNumber == ms).FirstOrDefault();
if (m != null) meshrefs.Add(m);
}
}
}
}
List<Mesh> meshes = new List<Mesh>();
foreach (var m in meshrefs)
{
var mesh = wld.ZoneMeshes.FirstOrDefault(x => x.FragmentNumber == m.FragmentReference);
if (headNumber > 0)
{
//see if it's a head mesh
int pos = mesh.FragmentName.IndexOf("HE00");
if (pos > 0)
{
string hNum = String.Format("HE{0:d2}", headNumber);
string hMeshName = mesh.FragmentName.Substring(0, pos) + hNum + mesh.FragmentName.Substring(pos + hNum.Length);
var hMesh = wld.ZoneMeshes.FirstOrDefault(x => x.FragmentName == hMeshName);
if (hMesh != null) mesh = hMesh;
}
}
if (mesh != null) meshes.Add(mesh);
}
if (meshes.Count > 0)
{
RenderMesh(wld,meshes, animation, textureNumber,face);
}
}
public static WLD Load(Stream stream,string name="default.wld")
{
WLD wld = new WLD();
wld.Name = name;
int size = Marshal.SizeOf(typeof(WLDHeader));
var barray = new byte[size];
stream.Read(barray, 0, size);
var header = Functions.ByteArrayToStructure<WLDHeader>(barray);
if (header.Magic != 0x54503d02)
{
throw new Exception("Invalid file format");
}
if (header.Version == 0x00015500)
{
wld._format = Format.Old;
}
else if (header.Version == 0x1000C800)
{
wld._format = Format.New;
}
else
{
throw new Exception("Unknown file version");
}
//var shash = stream.Position;
barray = new byte[header.StringHashSize];
stream.Read(barray, 0, (int)header.StringHashSize);
wld._sHash = WLD.DecodeFileName(barray);
wld._strings = wld._sHash.Split('\0');
var fragCount = header.FragmentCount;
stream.Seek(size + header.StringHashSize, SeekOrigin.Begin);
int fragSize = Marshal.SizeOf(typeof(BasicWLDFragment));
for (int i = 0; i < header.FragmentCount; i++)
{
barray = new byte[fragSize];
stream.Read(barray, 0, fragSize);
var fragment = Functions.ByteArrayToStructure<BasicWLDFragment>(barray);
int nameRef = (int)fragment.NameRef;
var position = stream.Position;
switch (fragment.Id)
{
case 0x03:
var bmpname = new BitmapName(i, nameRef);
bmpname.Handler(stream);
wld._fragments.Add(bmpname);
break;
case 0x04:
var binfo = new BitmapInfo(i, nameRef);
binfo.Handler(stream);
wld._fragments.Add(binfo);
break;
case 0x05:
var bitmapInfoRef = new BitmapInfoReference(i, nameRef);
bitmapInfoRef.Handler(stream);
wld._fragments.Add(bitmapInfoRef);
break;
case 0x09:
break;
case 0x10:
var skelset = new SkeletonTrackSet(i, nameRef);
skelset.Handler(stream);
skelset.FragmentName = wld.GetStringAtHashIndex(0-skelset.FragmentNameRef);
wld._fragments.Add(skelset);
break;
case 0x11:
var skeltrackRef = new SkeletonTrackReference(i, nameRef);
skeltrackRef.Handler(stream);
wld._fragments.Add(skeltrackRef);
break;
case 0x12:
var skelpiece = new SkeletonPieceTrack(i, nameRef);
skelpiece.Handler(stream);
wld._fragments.Add(skelpiece);
break;
case 0x13:
var skelpref = new SkeletonPieceTrackReference(i, nameRef);
skelpref.Handler(stream);
//skelpref.FragmentName = wld.GetStringAtHashIndex(0 - skelpref.FragmentNameRef);
wld._fragments.Add(skelpref);
break;
case 0x14:
var modelref = new ModelReference(i, nameRef);
modelref.Handler(stream);
modelref.FragmentName = wld.GetStringAtHashIndex(0 - modelref.FragmentNameRef);
wld._fragments.Add(modelref);
modelref.MagicString = wld.GetStringAtHashIndex(modelref.MagicStringRef);
break;
case 0x15:
var objlocation = new ObjectLocation(i, nameRef);
objlocation.Handler(stream);
wld._fragments.Add(objlocation);
break;
case 0x22:
//num_0x22++;
break;
case 0x2d:
var meshref = new MeshReference(i, nameRef);
meshref.Handler(stream);
wld._fragments.Add(meshref);
break;
case 0x31:
var tlist = new TextureList(i, nameRef);
tlist.Handler(stream);
wld._fragments.Add(tlist);
break;
case 0x30:
var texture = new Texture(i, nameRef);
texture.Handler(stream);
wld._fragments.Add(texture);
break;
// Grab the number of vertices and polygons
case 0x36:
var mesh = new Mesh(i, nameRef);
mesh.Handler(stream);
wld._fragments.Add(mesh);
break;
}
stream.Seek(position + fragment.Size - 4, SeekOrigin.Begin);
}
return wld;
}
public void OnlyTracksWithGroupIdAreConsideredAsPotentialCandidatesTest()
{
long[] buckets = new long[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
var queryHash = new HashedFingerprint(new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 11 }, buckets, 0, 0);
const int DefaultThreshold = 5;
const int FirstTrackId = 20;
const int FirstSubFingerprintId = 10;
var firstTrackReference = new ModelReference<int>(FirstTrackId);
SubFingerprintData firstResult = new SubFingerprintData(
new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 },
1,
0.928,
new ModelReference<int>(FirstSubFingerprintId),
firstTrackReference);
modelService.Setup(
service =>
service.ReadSubFingerprintDataByHashBucketsThresholdWithGroupId(buckets, DefaultThreshold, "group-id"))
.Returns(new List<SubFingerprintData> { firstResult });
modelService.Setup(service => service.ReadTrackByReference(firstTrackReference)).Returns(
new TrackData { ISRC = "isrc", TrackReference = firstTrackReference });
var queryResult = queryFingerprintService.Query(
modelService.Object,
new List<HashedFingerprint> { queryHash },
new CustomQueryConfiguration { TrackGroupId = "group-id" });
Assert.IsTrue(queryResult.IsSuccessful);
Assert.AreEqual("isrc", queryResult.BestMatch.Track.ISRC);
Assert.AreEqual(firstTrackReference, queryResult.BestMatch.Track.TrackReference);
}
private void InsertSubFingerprint(HashedFingerprint hashedFingerprint, IModelReference trackReference)
{
var subFingerprintReference = new ModelReference<long>(Interlocked.Increment(ref counter));
storage.SubFingerprints[subFingerprintReference] = new SubFingerprintData(
hashedFingerprint.HashBins,
hashedFingerprint.SequenceNumber,
hashedFingerprint.StartsAt,
subFingerprintReference,
trackReference) {
Clusters = hashedFingerprint.Clusters
};
if (!storage.TracksHashes.ContainsKey(trackReference))
{
storage.TracksHashes[trackReference] = new ConcurrentDictionary<IModelReference, HashedFingerprint>();
}
storage.TracksHashes[trackReference][subFingerprintReference] = hashedFingerprint;
this.InsertHashes(hashedFingerprint.HashBins, subFingerprintReference);
}
private IEnumerable<SubFingerprintData> GetSubFingerprintsForTrack(ModelReference<int> trackReference, int candidatesCount)
{
List<SubFingerprintData> subFingerprints = new List<SubFingerprintData>();
const double OneFingerprintLength = 0.256;
for (int i = 0; i < candidatesCount - 1; ++i)
{
var sub = new SubFingerprintData(GenericHashBuckets(), i, OneFingerprintLength * i, new ModelReference<int>(i), trackReference);
sub.Hashes[0] = 0;
subFingerprints.Add(sub);
}
subFingerprints.Add(new SubFingerprintData(GenericHashBuckets(), candidatesCount - 1, OneFingerprintLength * candidatesCount, new ModelReference<int>(candidatesCount), trackReference));
return subFingerprints;
}
public IModelReference InsertTrack(TrackData track)
{
var trackReference = new ModelReference<int>(Interlocked.Increment(ref counter));
storage.Tracks[trackReference] = track;
return track.TrackReference = trackReference;
}
public void RenderModel(ModelReference model,int textureNumber,int headNumber=0)
{
if (model == null) return;
_display3d.RenderModel(model, textureNumber, headNumber);
}
