public DefaultFingerprintConfiguration()
{
SpectrogramConfig = new DefaultSpectrogramConfig();
HashingConfig = new DefaultHashingConfig();
TopWavelets = 200;
SampleRate = 5512;
HaarWaveletNorm = Math.Sqrt(2);
FingerprintLengthInSeconds = (double)SamplesPerFingerprint / SampleRate;
OriginalPointSaveTransform = (_ => Array.Empty <byte>());
GaussianBlurConfiguration = GaussianBlurConfiguration.None;
FrameNormalizationTransform = new LogSpectrumNormalization();
}
public void ShouldGenerateLogSpectrumFromAudioSamples()
{
int Fs = 5512;
int seconds = 10;
float[] samples = new float[Fs * seconds];
float f1 = 410;
float f2 = 1400;
for (int t = 0; t < samples.Length; ++t)
{
samples[t] = (float)System.Math.Sin(2 * System.Math.PI * f1 / Fs * t) + (float)System.Math.Sin(2 * System.Math.PI * f2 / Fs * t);
}
var audio = new AudioSamples(samples, "410Hz", 5512);
var config = new DefaultSpectrogramConfig
{
Stride = new IncrementalStaticStride(5512)
};
var logNormalize = new LogSpectrumNormalization();
var spectralImages = logNormalize.Normalize(spectrumService.CreateLogSpectrogram(audio, config)).ToList();
Assert.AreEqual((seconds * Fs - config.WdftSize) / Fs, spectralImages.Count);
// check with logspace(log10(318), log10(2000), 33), 410Hz are located in 4th bin, 1400Hz at 25th (0 indexed)
int tf1 = 4;
int tf2 = 25;
foreach (var image in spectralImages)
{
float[] spectrum = image.ImageRowCols;
for (int row = 0; row < image.Rows; ++row)
{
for (int col = 0; col < image.Cols; ++col)
{
int index = row * image.Cols + col;
if (col == tf1 || col == tf2)
{
Assert.AreEqual(col == tf1 ? 1 : 0.78, spectrum[index], 0.01);
}
else
{
Assert.AreEqual(0, spectrum[index], 0.001);
}
}
}
}
}
