public DefaultQueryConfiguration()
{
ThresholdVotes = 5;
MaxTracksToReturn = 25;
Clusters = Enumerable.Empty<string>();
FingerprintConfiguration = new DefaultFingerprintConfiguration();
}
public void CreateFingerprintsTest()
{
float[] samples = TestUtilities.GenerateRandomFloatArray(5512 * 10);
var configuration = new DefaultFingerprintConfiguration();
float[][] logarithmizedSpectrum = new[]
{
TestUtilities.GenerateRandomFloatArray(2048),
TestUtilities.GenerateRandomFloatArray(2048),
TestUtilities.GenerateRandomFloatArray(2048)
};
List<float[][]> dividedLogSpectrum = new List<float[][]>
{
new[] { TestUtilities.GenerateRandomFloatArray(2048) },
new[] { TestUtilities.GenerateRandomFloatArray(2048) },
new[] { TestUtilities.GenerateRandomFloatArray(2048) }
};
spectrumService.Setup(service => service.CreateLogSpectrogram(samples, configuration)).Returns(logarithmizedSpectrum);
spectrumService.Setup(service => service.CutLogarithmizedSpectrum(logarithmizedSpectrum, configuration.Stride, configuration.FingerprintLength, configuration.Overlap))
.Returns(dividedLogSpectrum);
waveletDecomposition.Setup(service => service.DecomposeImagesInPlace(dividedLogSpectrum));
fingerprintDescriptor.Setup(descriptor => descriptor.ExtractTopWavelets(It.IsAny<float[][]>(), configuration.TopWavelets)).Returns(GenericFingerprint);
List<bool[]> rawFingerprints = fingerprintService.CreateFingerprints(samples, configuration);
Assert.AreEqual(3, rawFingerprints.Count);
foreach (bool[] fingerprint in rawFingerprints)
{
Assert.AreEqual(GenericFingerprint, fingerprint);
}
}
public DefaultQueryConfiguration()
{
ThresholdVotes = 5;
MaxTracksToReturn = 25;
Clusters = Enumerable.Empty <string>();
FingerprintConfiguration = new DefaultFingerprintConfiguration();
}
public void QueryCommandIsBuiltWithCustomFingerprintConfigCorrectly()
{
var customConfig = new DefaultFingerprintConfiguration();
var command = queryCommandBuilder.BuildQueryCommand()
.From("path-to-file", 10, 0)
.WithFingerprintConfig(customConfig)
.UsingServices(modelService.Object, audioService.Object);
Assert.AreSame(command.FingerprintConfiguration, customConfig);
}
public DefaultQueryConfiguration()
{
ThresholdVotes = Configs.Threshold.Default;
MaxTracksToReturn = 25;
Clusters = Enumerable.Empty <string>();
AllowMultipleMatchesOfTheSameTrackInQuery = false;
FingerprintConfiguration = new DefaultFingerprintConfiguration
{
Stride = Configs.QueryStrides.DefaultStride,
FrequencyRange = Configs.FrequencyRanges.Default
};
}
public void CreateLogSpectrogramFromSamplesLessThanFourierTransformWindowLength()
{
var configuration = new DefaultFingerprintConfiguration();
float[] samples = TestUtilities.GenerateRandomFloatArray(configuration.WdftSize - 1);
logUtility.Setup(utility => utility.GenerateLogFrequenciesRanges(configuration)).Returns(new int[33]);
float[][] result = spectrumService.CreateLogSpectrogram(samples, configuration);
logUtility.Verify(utility => utility.GenerateLogFrequenciesRanges(configuration), Times.Once());
Assert.AreEqual(0, result.Length); // 128
}
public DefaultQueryConfiguration()
{
ThresholdVotes = Configs.Threshold.Default;
MaxTracksToReturn = 25;
PermittedGap = 2d;
AllowMultipleMatchesOfTheSameTrackInQuery = false;
FingerprintConfiguration = new DefaultFingerprintConfiguration
{
Stride = Configs.QueryStrides.DefaultStride,
FrequencyRange = Configs.FrequencyRanges.Default
};
MetaFieldsFilter = new Dictionary <string, string>();
QueryMediaType = MediaType.Audio;
}
public void CorrectFingerprintConfigurationIsUsedWithInstanceConfigTest()
{
const string PathToAudioFile = "path-to-audio-file";
var configuration = new DefaultFingerprintConfiguration { SpectrogramConfig = new DefaultSpectrogramConfig { ImageLength = 1234 } };
var fingerprintCommand = fingerprintCommandBuilder.BuildFingerprintCommand()
.From(PathToAudioFile)
.WithFingerprintConfig(configuration)
.UsingServices(audioService.Object);
Assert.AreSame(configuration, fingerprintCommand.FingerprintConfiguration);
Assert.AreEqual(configuration.SpectrogramConfig.ImageLength, fingerprintCommand.FingerprintConfiguration.SpectrogramConfig.ImageLength);
}
public void AudioSamplesAreNormalized()
{
const int TenSeconds = 5512 * 10;
var samples = TestUtilities.GenerateRandomAudioSamples(TenSeconds);
var fingerprintConfig = new DefaultFingerprintConfiguration { NormalizeSignal = true };
var dividedLogSpectrum = GetDividedLogSpectrum();
spectrumService.Setup(service => service.CreateLogSpectrogram(samples, It.IsAny<DefaultSpectrogramConfig>())).Returns(dividedLogSpectrum);
waveletDecomposition.Setup(service => service.DecomposeImageInPlace(It.IsAny<float[][]>()));
fingerprintDescriptor.Setup(descriptor => descriptor.ExtractTopWavelets(It.IsAny<float[][]>(), fingerprintConfig.TopWavelets))
.Returns(GenericFingerprint);
audioSamplesNormalizer.Setup(normalizer => normalizer.NormalizeInPlace(samples.Samples));
fingerprintService.CreateFingerprints(samples, fingerprintConfig);
}
public void CutLogarithmizedSpectrumOfJustOneFingerprintTest()
{
DefaultFingerprintConfiguration config = new DefaultFingerprintConfiguration();
int logSpectrumLength = config.FingerprintLength; // 128
var stride = new StaticStride(0, 0);
var logSpectrum = new float[logSpectrumLength][];
for (int i = 0; i < logSpectrumLength; i++)
{
logSpectrum[i] = new float[32];
}
var cutLogarithmizedSpectrum = spectrumService.CutLogarithmizedSpectrum(logSpectrum, stride, config.FingerprintLength, config.Overlap);
Assert.AreEqual(1, cutLogarithmizedSpectrum.Count);
}
public void FingerprintConfigurationInheritsDefaultValues()
{
var customConfiguration = new CustomFingerprintConfiguration();
var defaultConfiguration = new DefaultFingerprintConfiguration();
Assert.AreEqual(defaultConfiguration.FingerprintLength, customConfiguration.FingerprintLength);
Assert.AreEqual(defaultConfiguration.LogBase, customConfiguration.LogBase);
Assert.AreEqual(defaultConfiguration.LogBins, customConfiguration.LogBins);
Assert.AreEqual(defaultConfiguration.MaxFrequency, customConfiguration.MaxFrequency);
Assert.AreEqual(defaultConfiguration.MinFrequency, customConfiguration.MinFrequency);
Assert.AreEqual(defaultConfiguration.NormalizeSignal, customConfiguration.NormalizeSignal);
Assert.AreEqual(defaultConfiguration.NumberOfLSHTables, customConfiguration.NumberOfLSHTables);
Assert.AreEqual(defaultConfiguration.NumberOfMinHashesPerTable, customConfiguration.NumberOfMinHashesPerTable);
Assert.AreEqual(defaultConfiguration.Overlap, customConfiguration.Overlap);
Assert.AreEqual(defaultConfiguration.SampleRate, customConfiguration.SampleRate);
Assert.AreEqual(defaultConfiguration.SamplesPerFingerprint, customConfiguration.SamplesPerFingerprint);
Assert.IsTrue(defaultConfiguration.Stride.GetType() == customConfiguration.Stride.GetType());
Assert.AreEqual(defaultConfiguration.TopWavelets, customConfiguration.TopWavelets);
Assert.AreEqual(defaultConfiguration.UseDynamicLogBase, customConfiguration.UseDynamicLogBase);
Assert.AreEqual(defaultConfiguration.WdftSize, customConfiguration.WdftSize);
}
public void CreateFingerprints()
{
const int TenSeconds = 5512 * 10;
var samples = TestUtilities.GenerateRandomAudioSamples(TenSeconds);
var configuration = SpectrogramConfig.Default;
var fingerprintConfig = new DefaultFingerprintConfiguration();
var dividedLogSpectrum = GetDividedLogSpectrum();
spectrumService.Setup(service => service.CreateLogSpectrogram(samples, configuration)).Returns(dividedLogSpectrum);
waveletDecomposition.Setup(service => service.DecomposeImageInPlace(It.IsAny<float[][]>()));
fingerprintDescriptor.Setup(descriptor => descriptor.ExtractTopWavelets(It.IsAny<float[][]>(), fingerprintConfig.TopWavelets))
.Returns(GenericFingerprint);
var fingerprints = fingerprintService.CreateFingerprints(samples, fingerprintConfig);
Assert.AreEqual(dividedLogSpectrum.Count, fingerprints.Count);
for (int index = 0; index < fingerprints.Count; index++)
{
Assert.AreEqual(GenericFingerprint, fingerprints[index].Signature);
Assert.AreEqual(dividedLogSpectrum[index].Timestamp, fingerprints[index].Timestamp, Epsilon);
}
}
private void BtnStartClick(object sender, EventArgs e)
{
DefaultFingerprintConfiguration configuration = new DefaultFingerprintConfiguration();
switch (hashAlgorithm)
{
case HashAlgorithm.LSH:
if (!fileList.Any())
{
MessageBox.Show(Resources.SelectFolderWithSongs, Resources.Songs, MessageBoxButtons.OK, MessageBoxIcon.Information);
break;
}
WinQueryResults winQueryResults = new WinQueryResults(
_numSecondsToAnalyze.Enabled ? (int)_numSecondsToAnalyze.Value : 0,
_numStartAtSecond.Enabled ? (int)_numStartAtSecond.Value : 0,
(int)_nudHashtables.Value,
(int)_nudKeys.Value,
Convert.ToInt32(_nudThreshold.Value),
WinUtils.GetStride((StrideType)_cmbStrideType.SelectedIndex, (int)_nudQueryStrideMax.Value, (int)_nudQueryStrideMin.Value, configuration.SamplesPerFingerprint),
tagService,
modelService,
audioService,
queryCommandBuilder);
winQueryResults.Show();
winQueryResults.Refresh();
winQueryResults.ExtractCandidatesWithMinHashAlgorithm(fileList);
break;
case HashAlgorithm.NeuralHasher:
throw new NotImplementedException();
case HashAlgorithm.None:
throw new NotImplementedException();
}
}
private void BtnQueryFromMicrophoneClick(object sender, EventArgs e)
{
DefaultFingerprintConfiguration configuration = new DefaultFingerprintConfiguration();
int secondsToRecord = (int)_nudSecondsToRecord.Value;
int sampleRate = (int)_nudSampleRate.Value;
string pathToFile = "mic_" + DateTime.Now.Ticks + ".wav";
_gbQueryMicrophoneBox.Enabled = false;
Task<float[]>.Factory.StartNew(() => audioService.ReadMonoSamplesFromMicrophone(sampleRate, secondsToRecord)).ContinueWith(
task =>
{
var samples = task.Result;
audioService.WriteSamplesToWaveFile(pathToFile, samples, sampleRate);
_gbQueryMicrophoneBox.Enabled = true;
WinQueryResults winQueryResults = new WinQueryResults(
secondsToRecord,
0,
(int)_nudHashtables.Value,
(int)_nudKeys.Value,
(int)_nudThreshold.Value,
WinUtils.GetStride((StrideType)_cmbStrideType.SelectedIndex, (int)_nudQueryStrideMax.Value, (int)_nudQueryStrideMin.Value, configuration.SamplesPerFingerprint),
tagService,
modelService,
audioService,
queryCommandBuilder);
winQueryResults.Show();
winQueryResults.Refresh();
winQueryResults.ExtractCandidatesUsingSamples(task.Result);
},
TaskScheduler.FromCurrentSynchronizationContext());
}
public void CreateFingerprintFromSamplesWhichAreExactlyEqualToMinimumLength()
{
DefaultFingerprintConfiguration config = new DefaultFingerprintConfiguration();
AudioSamples samples = GenerateRandomAudioSamples(config.SamplesPerFingerprint + config.SpectrogramConfig.WdftSize);
var hash = fingerprintCommandBuilder.BuildFingerprintCommand()
.From(samples)
.UsingServices(bassAudioService)
.Hash()
.Result;
Assert.AreEqual(1, hash.Count);
}
public void CreateFingerprintFromSamplesWhichAreExactlyEqualToMinimumLength()
{
DefaultFingerprintConfiguration config = new DefaultFingerprintConfiguration();
float[] samples = TestUtilities.GenerateRandomFloatArray(config.SamplesPerFingerprint + config.WdftSize);
var hash = fingerprintCommandBuilder.BuildFingerprintCommand()
.From(samples)
.WithDefaultFingerprintConfig()
.UsingServices(bassAudioService)
.Hash()
.Result;
Assert.AreEqual(1, hash.Count);
}
public void CutLogarithmizedSpectrumWithAnIncrementalStaticStride()
{
DefaultFingerprintConfiguration config = new DefaultFingerprintConfiguration();
int logSpectrumLength = (config.FingerprintLength * 24) + config.Overlap;
var stride = new IncrementalStaticStride(config.SamplesPerFingerprint / 2, config.SamplesPerFingerprint, 0);
var logSpectrum = new float[logSpectrumLength][];
for (int i = 0; i < logSpectrumLength; i++)
{
logSpectrum[i] = new float[32];
}
var cutLogarithmizedSpectrum = spectrumService.CutLogarithmizedSpectrum(logSpectrum, stride, config.FingerprintLength, config.Overlap);
Assert.AreEqual(48, cutLogarithmizedSpectrum.Count);
}
internal FingerprintCommand(IFingerprintService fingerprintService, ILocalitySensitiveHashingAlgorithm lshAlgorithm)
{
this.fingerprintService = fingerprintService;
this.lshAlgorithm = lshAlgorithm;
FingerprintConfiguration = new DefaultFingerprintConfiguration();
}
public void SilenceIsNotFingerprinted()
{
var samples = TestUtilities.GenerateRandomAudioSamples(5512 * 10);
var configuration = new DefaultFingerprintConfiguration();
var dividedLogSpectrum = GetDividedLogSpectrum();
spectrumService.Setup(service => service.CreateLogSpectrogram(samples, It.IsAny<DefaultSpectrogramConfig>())).Returns(dividedLogSpectrum);
waveletDecomposition.Setup(decomposition => decomposition.DecomposeImageInPlace(It.IsAny<float[][]>()));
fingerprintDescriptor.Setup(descriptor => descriptor.ExtractTopWavelets(It.IsAny<float[][]>(), configuration.TopWavelets)).Returns(
new[] { false, false, false, false, false, false, false, false });
var rawFingerprints = fingerprintService.CreateFingerprints(samples, configuration);
Assert.IsTrue(rawFingerprints.Count == 0);
}
private void BtnStartClick(object sender, EventArgs e)
{
DefaultFingerprintConfiguration configuration = new DefaultFingerprintConfiguration();
switch (hashAlgorithm)
{
case HashAlgorithm.LSH:
if (!fileList.Any())
{
MessageBox.Show(Resources.SelectFolderWithSongs, Resources.Songs, MessageBoxButtons.OK, MessageBoxIcon.Information);
break;
}
WinQueryResults winQueryResults = new WinQueryResults(10, 20, 25, 4, 5,
WinUtils.GetStride(StrideType.IncrementalRandom, 512, 256, configuration.SamplesPerFingerprint),
tagService,
modelService,
audioService,
queryCommandBuilder);
winQueryResults.Show();
winQueryResults.Refresh();
winQueryResults.ExtractCandidatesWithMinHashAlgorithm(fileList);
break;
case HashAlgorithm.NeuralHasher:
throw new NotImplementedException();
case HashAlgorithm.None:
throw new NotImplementedException();
}
}