private int DenoiseLoop()
{
int dt = 0;
curImage = CImageProvider.GetImage(out dt);
curImage = DenoiseMaster.Process(curImage);
return(dt);
}
public void Initialize(StructMainFormParams Params)
{
CImageProvider.InitImageProvider(Params);
curImage = GetSampleImage(Params.PathToLoadFolder).Convert <Gray, Byte>();
MaskingMaster.SetMethod(Params.MaskingModes[Params.CurMaskingMode]);
DenoiseMaster.SetMethod(Params.DenoiseModes[Params.CurDenoiseMode], curImage);
NeuronProvider.PrepareExport(Params);
CurrentParams = Params;
}
private void CleanFilesLoop()
{
//int dt = 0;
//curImage = CImageProvider.GetImage(out dt);
curImage = CImageProvider.GetImage();
if (curImage == null)
{
; //поднять ивент о бяде или конце работы
}
curImage = DenoiseMaster.Process(curImage);
Intenisites = ImageParser.ApplyMask(curImage); // получаем словарь с данными интенсивностей нейронов
//NeuronProvider.AddValues(Intenisites, dt);
//NeuronProvider.AddValues(Intenisites);
}
public void StartProcessing()
{
int N = CImageProvider.TotalNumberOfImages;
curImage = CImageProvider.GetImage(0);
maskImage = MaskingMaster.Process(curImage);
ImageParser.PrepareImageParsingMethod(maskImage);
/*
* if (CurrentParams.doUseDenoiseOnly)
* {
* int time = 0;
* for (int i = 0; i < N; i++)
* {
* time = DenoiseLoop();
* curImage.Save(CurrentParams.PathToSaveFolder + "\\" + i.ToString() + "_" + time.ToString() + ".Png");
* }
* return;
* }
*
* if (CurrentParams.doUseCleanFiles)
* for (int i = 0; i < N; i++)
* {
* CleanFilesLoop();
* onNewImage(curImage);
* curImage.Save(@"" + i.ToString() + ".png");
* } */
Image <Gray, Byte> medianImage = new Image <Gray, byte>(@"C:\Users\Admin\Desktop\Антон\59 vanb\72\MED_Debug_2nd experiment work 72.png");
for (int i = 0; i < N; i++)
{
Loop(medianImage);
//curImage.Save(CurrentParams.PathToSaveFolder + i.ToString() + ".Png");
onNewImage(curImage);
}
MaskingMaster.GetMaskImage().Save(CurrentParams.PathToSaveFolder + "\\MaskImage.png");
List <NeuronBodyMask> NBML = MaskingMaster.GetListOfNeuronBodyMasks();
for (int i = 0; i < NBML.Count; i++)
{
NBML[i].BodyMask.Save(CurrentParams.PathToSaveFolder + "\\mask_" + i.ToString() + ".Png");
}
NeuronProvider.FinishSaving();
}
private void Loop(Image <Gray, Byte> backgroundImage)
{
int dt = 0;
curImage = CImageProvider.GetImage(out dt);
if (curImage == null)
{
return; //поднять ивент о бяде или конце работы
}
if (!CurrentParams.doUseCleanFiles)
{
curImage = DenoiseMaster.Process(curImage);
}
curImage = curImage - backgroundImage;
Intenisites = ImageParser.ApplyMask(curImage); // получаем словарь с данными интенсивностей нейронов
NeuronProvider.AddValues(Intenisites, dt);
//NeuronProvider.AddValues(Intenisites);
}
// Переделать чтобы считывалось через ImageProvider
public Image <Bgr, Byte> GetSampleImage(string path)
{
if (CImageProvider.TotalNumberOfImages != 0)
{
return(CImageProvider.GetSampleImage());
}
string[] files = Directory.GetFiles(path);
if (files.Length == 0)
{
throw new Exception("GetSampleImage: input_path некорректен либо в папке не содержится файлов");
}
Image <Bgr, Byte> tmp = new Image <Bgr, byte>(1, 1, new Bgr(0, 0, 0));
try
{
tmp = new Image <Bgr, byte>(files[0]);
curImage = tmp.Convert <Gray, Byte>();
}
catch (Exception) { return(null); }
return(tmp);
}
