//public int spawnModifer = 10;
// Use this for initialization
void Start()
{
sampleRate = audioSource.clip.frequency;
onset = FindObjectOfType <OnsetDetector>();
amplitude = FindObjectOfType <AmplitudeDetector>();
spawner = FindObjectOfType <EnemySpawner>();
}
// Use this for initialization
void Start()
{
onset = FindObjectOfType <OnsetDetector>();
audio = gameObject.AddComponent <AudioSource>();
audio.clip = Resources.Load("sfx_aura") as AudioClip;
audio.loop = true;
audio.spatialBlend = 1.0f;
audio.Play();
}
public AudioFeatures(DetectorOptions options, string csvDirectory, float correction, IProgress <string> progress = null)
{
//force garbage collection
GC.Collect(2, GCCollectionMode.Forced, true);
_csvDirectory = csvDirectory;
_outerProgressReporter = progress ?? new Progress <string>();
_correction = correction;
_innerProgressReporter = new Progress <string>(status =>
{
_outerProgressReporter.Report(_currentTask + ":" + status);
});
_onsetDetector = new OnsetDetector(options, _innerProgressReporter);
}
static void Main(string[] args)
{
double[][] inputs = { };
int[] outputs = { };
if (LearningModel.doTraining)
{
for (int i = 1; i <= Training.LearningModel.noteCount; i++)
{
string training_file = "C:\\UCLA\\MrChorder-master\\MrChorder\\Training\\LearningModelData\\piano" + i.ToString() + ".wav";
OnsetDetector onsetDetector = new OnsetDetector(training_file, null);
double[][] FAData = onsetDetector.GenerateTrainingFAData();
inputs = ConcatVector(inputs, FAData);
int[] arr = new int[FAData.Length];
for (int j = 0; j < arr.Length; j++)
{
arr[j] = i - 1;
}
outputs = ConcatElement(outputs, arr);
Console.WriteLine("Training FA Data generated.");
}
}
LearningModel svm = new LearningModel(inputs, outputs);
Console.WriteLine("Testing.");
string testFile = "C:\\UCLA\\MrChorder-master\\MrChorder\\Training\\LearningModelData\\test3.wav";
OnsetDetector testDetector = new OnsetDetector(testFile, svm);
double[][] notes = testDetector.GenerateNotes();
double[][] labels = { };
foreach (string line in File.ReadLines("C:\\UCLA\\MrChorder-master\\MrChorder\\Training\\LearningModelData\\label3", Encoding.UTF8))
{
double[][] t = new double[1][];
t[0] = new double[2];
string[] s = line.Split(' ');
t[0][0] = Double.Parse(s[0]);
t[0][1] = Double.Parse(s[1]);
labels = ConcatVector(labels, t);
}
double[] acc = GetAccuracy(notes, labels);
Console.WriteLine("End");
}
public void SendFile()
{
// Process file.
string resultFilePath = System.IO.Path.Combine(Server.MapPath("~\\Generate\\"), System.IO.Path.GetFileName("AnalyseResult.pdf"));
while (!System.IO.File.Exists(resultFilePath))
{
// TODO(allenxie): Fancy work on filename processing.
double[][] inputs = { };
int[] outputs = { };
LearningModel svm = new LearningModel(inputs, outputs); // Pre-trained
OnsetDetector od = new OnsetDetector(filename, svm);
double[][] music = od.GenerateNotes();
for (int i = 0; i < music.Length; i++)
{
music[i][0] = music[i][0] + 1; // Sync Training module and ToPDF module
}
ToPDF PDFGenerator = new ToPDF(resultFilePath, music, music.Length, musicname);
}
Response.Write("Return file successfully!");
Response.End();
}
public List <Note> Detection()
{
List <Note> noteList = new List <Note>();
//Console.WriteLine("Press any key to convert to .WAV file...");
//Console.ReadLine();
int i;
//Open MP3 file and convert to WAV file.
WaveOutEvent waveOut = new WaveOutEvent();
Mp3FileReader mp3Reader = new Mp3FileReader(@"C:\Users\Fazle\source\repos\Practice\Media\twinkle.mp3");
toWAV(mp3Reader);
//Console.WriteLine(".WAV file created! Press any key to continue...");
//Console.ReadLine();
StereoToMono(@"C:\Users\Fazle\source\repos\Practice\Media\current.wav");
int sampleRate;
double[] data = null, R = null;
ReadWavFile(out sampleRate);
openWav(@"C:\Users\Fazle\source\repos\Practice\Media\currentMono.wav", out data, out R);
//Console.WriteLine(data.Length);
Progress <string> progress = new Progress <string>();
OnsetDetector detector = new OnsetDetector(DetectorOptions.Default, progress);
List <Onset> list = detector.Detect(@"C:\Users\Fazle\source\repos\Practice\Media\currentMono.wav");
/*Console.WriteLine("Time Amp");
* for (i = 0; i < list.Count; i++)
* {
* Console.Write(list[i].OnsetTime);
* Console.Write(" ");
* Console.Write(list[i].OnsetAmplitude);
* Console.Write(" ");
* Console.WriteLine();
* }
* Console.WriteLine();*/
int startPos = 0, stopPos = 0, flag = 0;
double freq = 0, duration = 0;
double[] temp;
double[] result;
CSCore.Utils.Complex[] complex;
for (i = 0; i < list.Count - 1; i++)
{
startPos = (int)Math.Ceiling(list[i].OnsetTime * sampleRate);
stopPos = (int)Math.Floor(list[i + 1].OnsetTime * sampleRate);
temp = new double[stopPos - startPos];
result = new double[stopPos - startPos];
complex = new CSCore.Utils.Complex[stopPos - startPos];
Array.ConstrainedCopy(data, startPos, temp, 0, temp.Length);
for (int j = 0; j < complex.Length; j++)
{
complex[j] = new Complex((float)temp[j]);
//Console.WriteLine(complex[j]);
}
//Console.ReadLine();
Note note = new Note();
note.Frequency = CalculateFFT(result, complex, flag);
note.Name = UtilMethods.FreqToNote(note.Frequency);
note.Duration = list[i + 1].OnsetTime - list[i].OnsetTime;
noteList.Add(note);
}
//Last Note
startPos = (int)Math.Floor(list[i].OnsetTime * sampleRate);
stopPos = data.Length - 1;
temp = new double[stopPos - startPos];
result = new double[stopPos - startPos];
complex = new CSCore.Utils.Complex[stopPos - startPos];
Array.ConstrainedCopy(data, startPos, temp, 0, temp.Length);
for (int j = 0; j < complex.Length; j++)
{
complex[j] = new Complex((float)temp[j]);
}
flag = 1;
Note lastNote = new Note();
lastNote.Frequency = CalculateFFT(result, complex, flag);
lastNote.Name = UtilMethods.FreqToNote(lastNote.Frequency);
lastNote.Duration = (data.Length / sampleRate) - list[i].OnsetTime;
noteList.Add(lastNote);
//Console.WriteLine("Press any key to terminate.");
//Console.ReadLine();
mp3Reader.Dispose();
return(noteList);
}
