public Fingerprinter(FingerprinterConfiguration config, IFFTService fftService)
{
m_image = new Image(12);
if (config == null)
{
config = new FingerprinterConfigurationTest1();
}
m_image_builder = new ImageBuilder(m_image);
m_chroma_normalizer = new ChromaNormalizer(m_image_builder);
m_chroma_filter = new ChromaFilter(config.FilterCoefficients, m_chroma_normalizer);
m_chroma = new Chroma(MIN_FREQ, MAX_FREQ, FRAME_SIZE, SAMPLE_RATE, m_chroma_filter);
//m_chroma.set_interpolate(true);
// TODO: inject IFFTService
m_fft = new FFT(FRAME_SIZE, OVERLAP, m_chroma, fftService);
if (config.RemoveSilence)
{
m_silence_remover = new SilenceRemover(m_fft);
m_silence_remover.Threshold = config.SilenceThreshold;
m_audio_processor = new AudioProcessor(SAMPLE_RATE, m_silence_remover);
}
else
{
m_silence_remover = null;
m_audio_processor = new AudioProcessor(SAMPLE_RATE, m_fft);
}
m_fingerprint_calculator = new FingerprintCalculator(config.Classifiers);
m_config = config;
}
public Fingerprinter(FingerprinterConfiguration config, IFFTService fftService)
{
m_image = new Image(12);
if (config == null)
{
config = new FingerprinterConfigurationTest1();
}
m_image_builder = new ImageBuilder(m_image);
m_chroma_normalizer = new ChromaNormalizer(m_image_builder);
m_chroma_filter = new ChromaFilter(config.FilterCoefficients, m_chroma_normalizer);
m_chroma = new Chroma(MIN_FREQ, MAX_FREQ, FRAME_SIZE, SAMPLE_RATE, m_chroma_filter);
//m_chroma.set_interpolate(true);
// TODO: inject IFFTService
m_fft = new FFT(FRAME_SIZE, OVERLAP, m_chroma, fftService);
if (config.RemoveSilence)
{
m_silence_remover = new SilenceRemover(m_fft);
m_silence_remover.Threshold = config.SilenceThreshold;
m_audio_processor = new AudioProcessor(SAMPLE_RATE, m_silence_remover);
}
else
{
m_silence_remover = null;
m_audio_processor = new AudioProcessor(SAMPLE_RATE, m_fft);
}
m_fingerprint_calculator = new FingerprintCalculator(config.Classifiers);
m_config = config;
}
public void TestCalculateSubfingerprint()
{
Image image = new Image(2, 2);
image[0, 0] = 0.0;
image[0, 1] = 1.0;
image[1, 0] = 2.0;
image[1, 1] = 3.0;
Classifier[] classifiers = {
new Classifier(new Filter(0, 0, 1, 1), new Quantizer(0.01, 1.01, 1.5)),
};
FingerprintCalculator calculator = new FingerprintCalculator(classifiers);
IntegralImage integral_image = new IntegralImage(image);
Assert.AreEqual(TestsHelper.GrayCode(0), calculator.CalculateSubfingerprint(integral_image, 0));
Assert.AreEqual(TestsHelper.GrayCode(2), calculator.CalculateSubfingerprint(integral_image, 1));
}
public void TestCalculate()
{
Image image = new Image(2, 3);
image[0, 0] = 0.0;
image[0, 1] = 1.0;
image[1, 0] = 2.0;
image[1, 1] = 3.0;
image[2, 0] = 4.0;
image[2, 1] = 5.0;
Classifier[] classifiers = {
new Classifier(new Filter(0, 0, 1, 1), new Quantizer(0.01, 1.01, 1.5)),
};
FingerprintCalculator calculator = new FingerprintCalculator(classifiers);
int[] fp = calculator.Calculate(image);
Assert.AreEqual(3, fp.Length);
Assert.AreEqual(TestsHelper.GrayCode(0), fp[0]);
Assert.AreEqual(TestsHelper.GrayCode(2), fp[1]);
Assert.AreEqual(TestsHelper.GrayCode(3), fp[2]);
}
