| public static Assert ( bool condition ) : void | ||
| condition | bool | |
| Результат | void | |
private static void LoadOpticalFlowBackwardFiles <TEmguImageStructure, TSize>(SegmenterImageStackLoadDescription segmenterImageStackLoadDescription, string opticalFlowVolumeName, string sourceVolumeName, ref Dictionary <VolumeDescription> volumeDescriptions)
where TEmguImageStructure : struct, IColor
where TSize : new()
{
//
// load in each source image (using SlimDX just because this is the easiest way to access the raw bytes) and copy to client buffer
//
var sourceImageDirectory = segmenterImageStackLoadDescription.Directories.Get(sourceVolumeName);
var sourceImageFileNames = from fileInfo in new DirectoryInfo(sourceImageDirectory).GetFiles("*.*") where !fileInfo.Name.Equals("Thumbs.db") select fileInfo.Name;
var sourceImageFilePaths = from sourceImageFileName in sourceImageFileNames select Path.Combine(sourceImageDirectory, sourceImageFileName);
if (sourceImageFilePaths.Count() > 1)
{
int width, height, depth;
using (var image = new Image <TEmguImageStructure, TSize>(sourceImageFilePaths.First()))
{
width = image.Width;
height = image.Height;
depth = sourceImageFilePaths.Count() - 1;
}
var volumeDataStream = new DataStream(width * height * depth * NUM_BYTES_PER_OPTICAL_FLOW_VOXEL, true, true);
var fromFileStems = from sourceImageFileName in sourceImageFileNames.Skip(1)
select new string( sourceImageFileName.Remove(sourceImageFileName.LastIndexOf(".")).ToCharArray());
var toFileStems = from sourceImageFileName in sourceImageFileNames.Take(sourceImageFileNames.Count() - 1)
select new string( sourceImageFileName.Remove(sourceImageFileName.LastIndexOf(".")).ToCharArray());
var opticalFlowFileNames = fromFileStems.Select((fromFileStem, i) => fromFileStem + "-to-" + toFileStems.ElementAt(i) + ".raw");
var opticalFlowFilePaths = from opticalFlowFileName in opticalFlowFileNames
select
Path.Combine(segmenterImageStackLoadDescription.Directories.Get(opticalFlowVolumeName),
opticalFlowFileName);
foreach (var opticalFlowFilePath in opticalFlowFilePaths)
{
Release.Assert(File.Exists(opticalFlowFilePath));
using (var opticalFlowFileStream = new FileStream(opticalFlowFilePath, FileMode.Open))
{
opticalFlowFileStream.CopyTo(volumeDataStream);
}
}
volumeDescriptions.Set(opticalFlowVolumeName,
new VolumeDescription
{
DxgiFormat = Format.R32G32_Float,
DataStream = volumeDataStream,
Data = volumeDataStream.DataPointer,
NumBytesPerVoxel = NUM_BYTES_PER_OPTICAL_FLOW_VOXEL,
NumVoxelsX = width,
NumVoxelsY = height,
NumVoxelsZ = depth,
IsSigned = true
});
}
}
public void Scribble(int x, int y, ConstraintType constraintType, int brushWidth)
{
if (CurrentNeuralProcess != null)
{
Interop.ConvergenceGap = Constants.Parameters.GetFloat("MAX_CONVERGENCE_GAP");
Interop.ConvergenceGapDelta = Constants.Parameters.GetFloat("MAX_CONVERGENCE_GAP_DELTA");
switch (constraintType)
{
case ConstraintType.Foreground:
Interop.AddForegroundHardConstraint(
new Vector3(x, y, CurrentSlice),
new Vector3(mMousePreviousX, mMousePreviousY, CurrentSlice),
brushWidth,
HardConstraintMode.Scribble);
break;
case ConstraintType.Background:
Interop.AddBackgroundHardConstraint(
new Vector3(x, y, CurrentSlice),
new Vector3(mMousePreviousX, mMousePreviousY, CurrentSlice),
brushWidth,
HardConstraintMode.Scribble);
break;
default:
Release.Assert(false);
break;
}
mMousePreviousX = x;
mMousePreviousY = y;
}
}
public static Effect CompileEffect(Device device, string effectFile)
{
Effect effect = null;
var compilationSucceeded = false;
while (!compilationSucceeded)
{
try
{
Release.Assert(File.Exists(effectFile));
using (var shaderBytecode = ShaderBytecode.CompileFromFile(effectFile,
"fx_5_0",
ShaderFlags.None,
EffectFlags.None))
{
effect = new Effect(device, shaderBytecode);
compilationSucceeded = true;
}
}
catch (Exception e)
{
compilationSucceeded = false;
Release.Assert(false, e.Message);
}
}
return(effect);
}
private static void LoadImages <TEmguImageStructure, TSize>(SegmenterImageStackLoadDescription segmenterImageStackLoadDescription, string volumeName, ref Dictionary <VolumeDescription> volumeDescriptions)
where TEmguImageStructure : struct, IColor
where TSize : new()
{
//
// load in each source image and copy to client buffer
//
var imageDirectory = segmenterImageStackLoadDescription.Directories.Get(volumeName);
var imageFileNames = from fileInfo in new DirectoryInfo(imageDirectory).GetFiles("*.*") where !fileInfo.Name.Equals("Thumbs.db") select fileInfo.Name;
var imageFilePaths = from imageFileName in imageFileNames select Path.Combine(imageDirectory, imageFileName);
Release.Assert(imageFilePaths.Count() > 0);
int width, height, depth;
using (var image = new Image <TEmguImageStructure, TSize>(imageFilePaths.First()))
{
width = image.Width;
height = image.Height;
depth = imageFilePaths.Count();
}
var volumeDataStream = new DataStream(width * height * depth * segmenterImageStackLoadDescription.NumBytesPerVoxel, true, true);
foreach (var imageFilePath in imageFilePaths)
{
using (var image = new Image <TEmguImageStructure, TSize>(imageFilePath))
{
volumeDataStream.Write(image.Bytes, 0, image.Bytes.Length);
Release.Assert(width == image.Width);
Release.Assert(height == image.Height);
}
}
volumeDescriptions.Set(volumeName,
new VolumeDescription
{
DxgiFormat = segmenterImageStackLoadDescription.DxgiFormat,
DataStream = volumeDataStream,
Data = volumeDataStream.DataPointer,
NumBytesPerVoxel = segmenterImageStackLoadDescription.NumBytesPerVoxel,
NumVoxelsX = width,
NumVoxelsY = height,
NumVoxelsZ = depth,
IsSigned = segmenterImageStackLoadDescription.IsSigned
});
}
public static TXml ReadFromFile <TXml, TXmlSerializer>(string fileName) where TXmlSerializer : XmlSerializer, new()
{
try
{
var xmlSerializer = new TXmlSerializer();
// A FileStream is needed to read the XML document.
using (var fileStream = new FileStream(fileName, FileMode.Open))
{
System.Xml.XmlReader xmlTextReader = new XmlTextReader(fileStream);
// Declare an object variable of the type to be deserialized.
return((TXml)xmlSerializer.Deserialize(xmlTextReader));
}
}
catch (Exception)
{
Release.Assert(false);
}
return(default(TXml));
}
public void InitializeConstraintMapAndSegmentationFromBreadcrumbs()
{
if (DatasetDescription.NeuralProcessDescriptions.Count > 0)
{
Release.Assert(CurrentNeuralProcess != null);
var backgroundBreadcrumbs = from neuralProcessDescription in DatasetDescription.NeuralProcessDescriptions.Values
from breadcrumb in neuralProcessDescription.BreadcrumbDescriptions
where !neuralProcessDescription.Color.Equals(CurrentNeuralProcess.Color)
select breadcrumb;
backgroundBreadcrumbs.ToList().ForEach(
breadcrumb => Interop.AddBackgroundHardConstraint(breadcrumb.Position,
Constants.MIN_BRUSH_WIDTH,
HardConstraintMode.Breadcrumb));
CurrentNeuralProcess.BreadcrumbDescriptions.ToList().ForEach(
breadcrumb => Interop.AddForegroundHardConstraint(breadcrumb.Position,
Constants.MIN_BRUSH_WIDTH,
HardConstraintMode.Breadcrumb));
}
}
public void SelectNeuralProcess(int id)
{
switch (CurrentSegmenterToolMode)
{
case SegmenterToolMode.Adjust:
SaveOldNeuralProcess();
CurrentNeuralProcess = DatasetDescription.NeuralProcessDescriptions[id];
InitializeNewNeuralProcess();
break;
case SegmenterToolMode.Merge:
Release.Assert(false);
break;
case SegmenterToolMode.Split:
CurrentNeuralProcess = DatasetDescription.NeuralProcessDescriptions[id];
break;
default:
Release.Assert(false);
break;
}
}
private static void LoadIdMapImages(SegmenterImageStackLoadDescription segmenterImageStackLoadDescription, string volumeName, ref Dictionary <VolumeDescription> volumeDescriptions)
{
//
// load in each source image and copy to client buffer
//
var imageDirectory = segmenterImageStackLoadDescription.Directories.Get(volumeName);
var imageFileNames = from fileInfo in new DirectoryInfo(imageDirectory).GetFiles("*.*") where !fileInfo.Name.Equals("Thumbs.db") select fileInfo.Name;
var imageFilePaths = from imageFileName in imageFileNames select Path.Combine(imageDirectory, imageFileName);
Release.Assert(imageFilePaths.Count() > 0);
int width, height, depth;
using (var image = new Image <Gray, UInt16>(imageFilePaths.First()))
{
width = image.Width;
height = image.Height;
depth = imageFilePaths.Count();
}
var volumeDataStream = new DataStream(width * height * depth * segmenterImageStackLoadDescription.NumBytesPerVoxel, true, true);
foreach (var imageFilePath in imageFilePaths)
{
var tmpImagePointer = CvInvoke.cvLoadImage(imageFilePath, LOAD_IMAGE_TYPE.CV_LOAD_IMAGE_UNCHANGED);
using (var tmpImage = new Image <Gray, UInt16>(width, height))
{
Release.Assert(width == tmpImage.Width);
Release.Assert(height == tmpImage.Height);
CvInvoke.cvCopy(tmpImagePointer, tmpImage, IntPtr.Zero);
for (var y = 0; y < height; y++)
{
for (var x = 0; x < width; x++)
{
var idMapValue = tmpImage[y, x];
volumeDataStream.Write((int)idMapValue.Intensity);
}
}
}
CvInvoke.cvReleaseImage(ref tmpImagePointer);
}
volumeDescriptions.Set(volumeName,
new VolumeDescription
{
DxgiFormat = segmenterImageStackLoadDescription.DxgiFormat,
DataStream = volumeDataStream,
Data = volumeDataStream.DataPointer,
NumBytesPerVoxel = segmenterImageStackLoadDescription.NumBytesPerVoxel,
NumVoxelsX = width,
NumVoxelsY = height,
NumVoxelsZ = depth,
IsSigned = segmenterImageStackLoadDescription.IsSigned
});
}
// ReSharper restore InconsistentNaming
public void LoadDataset(DatasetDescription datasetDescription)
{
Release.Assert(false);
//datasetDescription.NeuralProcessDescriptions.Get( "Trail 1" ).BreadcrumbDescriptions.Add(
// datasetDescription.NeuralProcessDescriptions.Get( "Trail 2" ).BreadcrumbDescriptions.First() );
//datasetDescription.NeuralProcessDescriptions.Get( "Trail 1" ).BreadcrumbDescriptions.Add(
// datasetDescription.NeuralProcessDescriptions.Get( "Trail 3" ).BreadcrumbDescriptions.First() );
//datasetDescription.NeuralProcessDescriptions.Get( "Trail 1" ).BreadcrumbDescriptions.Add(
// datasetDescription.NeuralProcessDescriptions.Get( "Trail 4" ).BreadcrumbDescriptions.First() );
//datasetDescription.NeuralProcessDescriptions.Get( "Trail 1" ).BreadcrumbDescriptions.Add(
// datasetDescription.NeuralProcessDescriptions.Get( "Trail 5" ).BreadcrumbDescriptions.First() );
//datasetDescription.NeuralProcessDescriptions.Get( "Trail 1" ).BreadcrumbDescriptions.Add(
// datasetDescription.NeuralProcessDescriptions.Get( "Trail 6" ).BreadcrumbDescriptions.First() );
//datasetDescription.NeuralProcessDescriptions.Get( "Trail 1" ).BreadcrumbDescriptions.Add(
// datasetDescription.NeuralProcessDescriptions.Get( "Trail 7" ).BreadcrumbDescriptions.First() );
//datasetDescription.NeuralProcessDescriptions.Get( "Trail 1" ).Branches =
// new List<Edge>
// {
// new Edge
// {
// P1 = datasetDescription.NeuralProcessDescriptions.Get( "Trail 2" ).BreadcrumbDescriptions.First().Position,
// P2 = datasetDescription.NeuralProcessDescriptions.Get( "Trail 3" ).BreadcrumbDescriptions.First().Position
// },
// new Edge
// {
// P1 = datasetDescription.NeuralProcessDescriptions.Get( "Trail 4" ).BreadcrumbDescriptions.First().Position,
// P2 = datasetDescription.NeuralProcessDescriptions.Get( "Trail 5" ).BreadcrumbDescriptions.First().Position
// },
// new Edge
// {
// P1 = datasetDescription.NeuralProcessDescriptions.Get( "Trail 6" ).BreadcrumbDescriptions.First().Position,
// P2 = datasetDescription.NeuralProcessDescriptions.Get( "Trail 7" ).BreadcrumbDescriptions.First().Position
// }
// };
//datasetDescription.NeuralProcessDescriptions.Internal =
// new ObservableDictionary< string, NeuralProcessDescription >(
// ( from neuralProcessDescription in
// datasetDescription.NeuralProcessDescriptions.Internal
// where neuralProcessDescription.Key == "Trail 1"
// select neuralProcessDescription ).ToDictionary( b => b.Key,
// b => b.Value ) );
//Interop.LoadDataset( datasetDescription );
//VolumeDescription = datasetDescription.VolumeDescriptions.Get( "SourceMap" );
//var textureDesc3D = new Texture3DDescription
// {
// Width = VolumeDescription.NumVoxelsX,
// Height = VolumeDescription.NumVoxelsY,
// Depth = VolumeDescription.NumVoxelsZ,
// MipLevels = 1,
// Usage = ResourceUsage.Default,
// BindFlags = BindFlags.ShaderResource,
// Format = VolumeDescription.DxgiFormat
// };
//var shaderResourceViewDesc = new ShaderResourceViewDescription
// {
// Format = VolumeDescription.DxgiFormat,
// Dimension = ShaderResourceViewDimension.Texture3D,
// MipLevels = -1
// };
//mSourceTexture = new Texture3D( mD3D11Device, textureDesc3D );
//VolumeDescription.DataStream.Seek( 0, SeekOrigin.Begin );
//mD3D11DeviceContext.UpdateSubresource(
// new DataBox(
// VolumeDescription.NumVoxelsX *
// VolumeDescription.NumBytesPerVoxel,
// VolumeDescription.NumVoxelsY *
// VolumeDescription.NumVoxelsX *
// VolumeDescription.NumBytesPerVoxel,
// VolumeDescription.DataStream ),
// mSourceTexture,
// 0 );
//SourceTexture = new ShaderResourceView( mD3D11Device, mSourceTexture, shaderResourceViewDesc );
//AnisotropyFactor = 10f;
//NormalizedVolumeExtent =
// new Vector3( 1f,
// (float)VolumeDescription.NumVoxelsY / VolumeDescription.NumVoxelsX,
// ( VolumeDescription.NumVoxelsZ * AnisotropyFactor ) / VolumeDescription.NumVoxelsX );
//VolumeIndexToNormalizedVolumeCoordinates =
// Matrix.Scaling( NormalizedVolumeExtent.X / VolumeDescription.NumVoxelsX,
// NormalizedVolumeExtent.Y / VolumeDescription.NumVoxelsY,
// NormalizedVolumeExtent.Z / VolumeDescription.NumVoxelsZ );
//NormalizedVolumeCoordinatesToWorldCoordinates =
// Matrix.Reflection( new Plane( Vector3.Zero, Vector3.UnitY ) ) *
// Matrix.Translation( 0f, NormalizedVolumeExtent.Y, 0f );
//NormalizedVolumeCoordinatesToTextureCoordinates =
// Matrix.Scaling( 1f / NormalizedVolumeExtent.X,
// 1f / NormalizedVolumeExtent.Y,
// 1f / NormalizedVolumeExtent.Z );
//Camera = new Camera( NormalizedVolumeExtent * 4f,
// NormalizedVolumeExtent / 2f,
// new Vector3( 0f, 1f, 0f ),
// Matrix.PerspectiveFovLH( (float)Math.PI / 4, 1f, 0.1f, 100f ) );
//NeuralProcessDescriptions = datasetDescription.NeuralProcessDescriptions;
//AugmentedDelaunyEdges = AugmentDelaunyEdges( datasetDescription.NeuralProcessDescriptions, Interop.DelaunyEdges, VolumeIndexToNormalizedVolumeCoordinates );
//ShortestPathDescriptions = ComputeShortestPaths( datasetDescription.NeuralProcessDescriptions, AugmentedDelaunyEdges, VolumeIndexToNormalizedVolumeCoordinates );
}
public ObservableDictionary <int, NeuralProcessDescription> LoadDataset(BreadcrumbXmlLoadDescription breadcrumbXmlLoadDescription)
{
var breadcrumbTrailCollectionDirectory = breadcrumbXmlLoadDescription.BreadcrumbTrailCollectionDirectory;
var breadcrumbCollections = from fileInfo in new DirectoryInfo(breadcrumbTrailCollectionDirectory).GetFiles("*.*")
select new
{
SectionId = int.Parse(fileInfo.Name.Trim(TRIM_CHARS)),
BreadcrumbCollection =
XmlReader.ReadFromFile <contours, contoursSerializer>(
Path.Combine(breadcrumbTrailCollectionDirectory, fileInfo.Name))
};
Release.Assert(breadcrumbCollections.Count() > 0);
Release.Assert(breadcrumbCollections.All(breadcrumbCollection => breadcrumbCollection.BreadcrumbCollection.contour.All(breadcrumb => [email protected]("PointContour"))));
var distinctNeuralProcessNames = (from breadcrumbCollection in breadcrumbCollections
from breadcrumb in breadcrumbCollection.BreadcrumbCollection.contour
select breadcrumb.name).Distinct();
var distinctNeuralProcessIds = Enumerable.Range(1, distinctNeuralProcessNames.Count() + 1);
var distinctNeuralProcesses = distinctNeuralProcessIds.Zip(distinctNeuralProcessNames, (id, name) => new { Id = id, Name = name });
var tmpBreadcrumbDescriptions = from breadcrumbCollection in breadcrumbCollections
from breadcrumb in breadcrumbCollection.BreadcrumbCollection.contour
select new
{
Name = breadcrumb.name,
Color = new Vector3(
int.Parse(breadcrumb.color.Substring(1, 2), NumberStyles.HexNumber),
int.Parse(breadcrumb.color.Substring(3, 2), NumberStyles.HexNumber),
int.Parse(breadcrumb.color.Substring(5, 2), NumberStyles.HexNumber)),
BreadcrumbDescription = new BreadcrumbDescription
{
Position = new Vector3(
breadcrumb.value.point.x - breadcrumbXmlLoadDescription.BreadcrumbTrailCoordinateOffset.X,
breadcrumb.value.point.y - breadcrumbXmlLoadDescription.BreadcrumbTrailCoordinateOffset.Y,
breadcrumbCollection.SectionId - breadcrumbXmlLoadDescription.BreadcrumbTrailCoordinateOffset.Z)
}
};
var neuralProcesssToRemove = Constants.REMOVE_BAD_PROCESSES ? Constants.BadProcesses : new List <string>();
var neuralProcessDescriptions = new ObservableDictionary <int, NeuralProcessDescription>(
(from distinctNeuralProcess in distinctNeuralProcesses
join breadcrumbDescription in tmpBreadcrumbDescriptions
on distinctNeuralProcess.Name equals breadcrumbDescription.Name
into breadcrumbDescriptionsWithTheSameName
where !neuralProcesssToRemove.Contains(distinctNeuralProcess.Name)
select new NeuralProcessDescription(distinctNeuralProcess.Id)
{
Name = distinctNeuralProcess.Name,
Color = breadcrumbDescriptionsWithTheSameName.First().Color,
BreadcrumbDescriptions =
(from breadcrumbDescription in breadcrumbDescriptionsWithTheSameName
select breadcrumbDescription.BreadcrumbDescription).ToList()
}).ToDictionary(
neuralProcessDescription => neuralProcessDescription.Id,
neuralProcessDescription => neuralProcessDescription));
return(neuralProcessDescriptions);
}
