public void SaveSegmentationAs(SegmenterImageStackSaveDescription segmenterImageStackSaveDescription)
{
CommitSegmentation();
var colorMapDataStream =
new DataStream(
Interop.VolumeDescription.NumVoxelsX * Interop.VolumeDescription.NumVoxelsY * Interop.VolumeDescription.NumVoxelsZ * NUM_BYTES_PER_COLOR_MAP_PIXEL,
true,
true);
var idMapDataStream =
new DataStream(
Interop.VolumeDescription.NumVoxelsX * Interop.VolumeDescription.NumVoxelsY * Interop.VolumeDescription.NumVoxelsZ * NUM_BYTES_PER_COLOR_MAP_PIXEL,
true,
true);
var volumeDescriptions = new Dictionary <VolumeDescription>
{
{
"ColorMap", new VolumeDescription
{
DxgiFormat = Format.R8G8B8A8_UNorm,
DataStream = colorMapDataStream,
Data = colorMapDataStream.DataPointer,
NumBytesPerVoxel = NUM_BYTES_PER_COLOR_MAP_PIXEL,
NumVoxelsX = Interop.VolumeDescription.NumVoxelsX,
NumVoxelsY = Interop.VolumeDescription.NumVoxelsY,
NumVoxelsZ = Interop.VolumeDescription.NumVoxelsZ,
IsSigned = false
}
},
{
"IdMap", new VolumeDescription
{
DxgiFormat = Format.R32_UInt,
DataStream = idMapDataStream,
Data = idMapDataStream.DataPointer,
NumBytesPerVoxel = NUM_BYTES_PER_ID_MAP_PIXEL,
NumVoxelsX = Interop.VolumeDescription.NumVoxelsX,
NumVoxelsY = Interop.VolumeDescription.NumVoxelsY,
NumVoxelsZ = Interop.VolumeDescription.NumVoxelsZ,
IsSigned = false
}
},
};
Interop.SaveSegmentationAs(volumeDescriptions);
segmenterImageStackSaveDescription.VolumeDescriptions = volumeDescriptions;
SegmenterImageStackLoader.SaveSegmentation(segmenterImageStackSaveDescription);
}
public void LoadDataset(SegmenterImageStackLoadDescription segmenterImageStackLoadDescription)
{
var volumeDescriptions = SegmenterImageStackLoader.LoadDataset(segmenterImageStackLoadDescription);
var neuralProcessDescriptions = new ObservableDictionary <int, NeuralProcessDescription>
{
{ Constants.DEFAULT_NEURAL_PROCESS.Id, Constants.DEFAULT_NEURAL_PROCESS }
};
var datasetDescription = new DatasetDescription
{
NeuralProcessDescriptions = neuralProcessDescriptions,
VolumeDescriptions = volumeDescriptions
};
LoadDataset(datasetDescription);
}
public void LoadDataset(SegmenterImageStackLoadDescription segmenterImageStackLoadDescription, BreadcrumbXmlLoadDescription breadcrumbXmlLoadDescription)
{
var volumeDescriptions = SegmenterImageStackLoader.LoadDataset(segmenterImageStackLoadDescription);
var breadcrumbXmlLoader = new BreadcrumbXmlLoader();
var neuralProcessDescriptions = breadcrumbXmlLoader.LoadDataset(breadcrumbXmlLoadDescription);
neuralProcessDescriptions.Add(Constants.DEFAULT_NEURAL_PROCESS.Id, Constants.DEFAULT_NEURAL_PROCESS);
var datasetDescription = new DatasetDescription
{
NeuralProcessDescriptions = neuralProcessDescriptions,
VolumeDescriptions = volumeDescriptions
};
LoadDataset(datasetDescription);
}
public void LoadSegmentation(SegmenterImageStackLoadDescription segmenterImageStackLoadDescription)
{
UnloadSegmentation();
var volumeDescriptions = SegmenterImageStackLoader.LoadSegmentation(segmenterImageStackLoadDescription);
Interop.LoadSegmentation(volumeDescriptions);
Interop.VisualUpdate();
Interop.VisualUpdateColorMap();
volumeDescriptions.Get("ColorMap").DataStream.Seek(0, SeekOrigin.Begin);
volumeDescriptions.Get("IdMap").DataStream.Seek(0, SeekOrigin.Begin);
var uniqueIds = new Dictionary <int, Rgb>();
for (var z = 0; z < volumeDescriptions.Get("IdMap").NumVoxelsZ; z++)
{
for (var y = 0; y < volumeDescriptions.Get("IdMap").NumVoxelsY; y++)
{
for (var x = 0; x < volumeDescriptions.Get("IdMap").NumVoxelsX; x++)
{
var id = volumeDescriptions.Get("IdMap").DataStream.Read <int>();
var colorMapValue = volumeDescriptions.Get("ColorMap").DataStream.Read <int>();
var r = (colorMapValue & (0x0000ff << 0)) >> 0;
var g = (colorMapValue & (0x0000ff << 8)) >> 8;
var b = (colorMapValue & (0x0000ff << 16)) >> 16;
if (id == 0)
{
if (!(r == 0 && g == 0 && b == 0))
{
Console.WriteLine("WARNING: x = {0}, y = {1}, z = {2}, id = {3}, color = {4}", x, y, z, id, new Rgb(r, g, b).ToString());
}
}
if (uniqueIds.ContainsKey(id))
{
if (!uniqueIds[id].Equals(new Rgb(r, g, b)))
{
Console.WriteLine("WARNING: x = {0}, y = {1}, z = {2}, id = {3}, existing color = {4}, new color = {5}", x, y, z, id, uniqueIds[id].ToString(), new Rgb(r, g, b).ToString());
}
}
if (!uniqueIds.ContainsKey(id))
{
uniqueIds[id] = new Rgb(r, g, b);
}
}
}
}
uniqueIds.Remove(Constants.NULL_NEURAL_PROCESS.Id);
uniqueIds.ToList().ForEach(keyValuePair =>
DatasetDescription.NeuralProcessDescriptions.Add(keyValuePair.Key,
new NeuralProcessDescription(keyValuePair.Key)
{
Name = "Autogenerated Neural Process (ID " + keyValuePair.Key + ") " + keyValuePair.Value,
Color =
new Vector3((float)keyValuePair.Value.Red,
(float)keyValuePair.Value.Green,
(float)keyValuePair.Value.Blue),
BreadcrumbDescriptions = new List <BreadcrumbDescription>()
}));
CurrentNeuralProcess = null;
MergeSourceNeuralProcess = null;
MergeDestinationNeuralProcess = null;
SplitNeuralProcess = null;
CommittedSegmentationEqualsUndoBuffer = false;
CommittedSegmentationEqualsRedoBuffer = false;
SegmentationLoaded = true;
}
