public static LabeledTomogram ReadMRCFile(string mrcFilePath, int frameNumber)
{
MRCFile file = MRCParser.Parse(mrcFilePath);
MRCFrame frame = file.Frames[frameNumber];
LabeledTomogram ret = new LabeledTomogram();
ret.Labels = null;
ret.Data = frame.Data;
ret.Width = frame.Width;
ret.Height = frame.Height;
return(ret);
}
public static Bitmap MRCFrame2Bitmap(MRCFile file, int frameNumber)
{
MRCFrame frame = file.Frames[frameNumber];
float minFloat = file.MinPixelValue;
float maxfloat = file.MaxPixelValue;
float delta = maxfloat - minFloat;
float scaler = 255 / delta;
Bitmap bmp = new Bitmap(frame.Width, frame.Height);
for (int y = 0, i = 0; y < frame.Height; y++)
{
for (int x = 0; x < frame.Width; x++, i++)
{
byte b = (byte)((frame.Data[i] + Math.Abs(minFloat)) * scaler);
bmp.SetPixel(x, y, System.Drawing.Color.FromArgb(b, b, b));
}
}
return(bmp);
}
public static List <float> Sample(string annotatedBitmap, string correspondingMRCFileName, int correspondingMRCFrameNumber)
{
MRCFrame file = MRCParser.Parse(correspondingMRCFileName).Frames[correspondingMRCFrameNumber];
List <float> ret = new List <float>();
using (Bitmap bmp = (Bitmap)Image.FromFile(annotatedBitmap))
{
for (int y = 0, i = 0; y < bmp.Height; y++)
{
for (int x = 0; x < bmp.Width; x++, i++)
{
Color c = bmp.GetPixel(x, y);
if (c.R != c.B)
{
ret.Add(file.Data[i]);
}
}
}
}
return(ret);
}
static void Main(string[] args)
{
//Convolution.DoIt();
//EdgeTracer.DoIt();
//LabeledEdgeFinder.DoIt();
const string TomogramDirectory = @"c:/users/ben/downloads/";
Console.WriteLine("Loading main file..");
MRCFile file = MRCParser.Parse(@"D:\tomograms\tomography2_fullsirtcliptrim.mrc");
//MRCFrame frame = file.Frames[145];
//float[] data =
//for (int y = 264; y < 363; y++)
//{
// for (int x = 501; x < 600; x++)
// {
// }
//}
float scaler = 255 / (file.MaxPixelValue - file.MinPixelValue);
//Console.WriteLine("Loading label files...");
//List<MRCFile> labelFiles = new List<MRCFile>();
//labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels.mrc")));
//labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels2.mrc")));
//labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels3.mrc")));
//labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels4.mrc")));
//labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels5.mrc")));
//labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels7.mrc")));
//Color[] colors = new Color[]
//{
// Color.Red, Color.Green, Color.Pink, Color.Orange, Color.Yellow, Color.Violet
//};
//
float skipLength = 1.0f;
//int vertexCount = 0;
//using (StreamWriter sw = new StreamWriter(Path.Combine(TomogramDirectory, "pointCloudEnding.ply")))
//{
for (int z = 0; z < file.Frames.Count; z++)
{
Console.WriteLine($"File {z}/{file.Frames.Count}");
MRCFrame frame = file.Frames[z];
using (Bitmap bmp = new Bitmap(frame.Width / (int)skipLength, frame.Height / (int)skipLength))
{
for (int y = 0; y < frame.Height; y += (int)skipLength)
{
for (int x = 0; x < frame.Width; x += (int)skipLength)
{
try
{
int i = y * frame.Width + x;
bool labeled = false;
int colorIndex = 0;
//foreach (MRCFile label in labelFiles)
//{
// if (label.Frames[z].Data[i] > 0)
// {
// byte b = (byte)(frame.Data[i] * scaler);
// bmp.SetPixel((int)(x / skipLength), (int)(y / skipLength), colors[colorIndex]);
// sw.WriteLine("{0} {1} {2} {3} {4} {5}",
// x / skipLength,
// y / skipLength,
// z / skipLength,
// colors[colorIndex].R, colors[colorIndex].G, colors[colorIndex].B);
// //vertices.Add(new PLYVertex { X = x, Y = y, Z = z, Color = colors[colorIndex] });
// labeled = true;
// vertexCount++;
// }
// colorIndex++;
//}
//if (!labeled)
{
float v = frame.Data[i] + Math.Abs(file.MinPixelValue);
byte b = (byte)(v * scaler);
bmp.SetPixel((int)(x / skipLength), (int)(y / skipLength), Color.FromArgb(b, b, b));
//vertices.Add(new PLYVertex { X = x, Y = y, Z = z, Color = Color.FromArgb(b, b, b) });
}
}
catch
{
//sw.WriteLine("{0} {1} {2} {3} {4} {5}", x, y, z, 0, 0, 0);
//vertexCount++;
//vertices.Add(new PLYVertex { X = x, Y = y, Z = z, Color = Color.FromArgb(0, 0, 0) });
}
}
}
bmp.Save(Path.Combine("C:/users/brush/desktop/samples/", $"{z}.png"), ImageFormat.Png);
}
}
//}
//using (StreamWriter sw = new StreamWriter(Path.Combine(TomogramDirectory, "pointCloud.ply")))
//{
// sw.WriteLine("ply");
// sw.WriteLine("format ascii 1.0");
// sw.WriteLine("element vertex " + vertexCount.ToString());
// sw.WriteLine("property float x");
// sw.WriteLine("property float y");
// sw.WriteLine("property float z");
// sw.WriteLine("property uchar red");
// sw.WriteLine("property uchar green");
// sw.WriteLine("property uchar blue");
// sw.WriteLine("element face " + 0.ToString());
// sw.WriteLine("property list uchar uint vertex_indices");
// sw.WriteLine("end_header");
// using (StreamReader sr = new StreamReader(Path.Combine(TomogramDirectory, "pointCloudEnding.ply")))
// {
// string l = null;
// while ((l = sr.ReadLine()) != null)
// {
// sw.WriteLine(l);
// }
// }
//}
//using (StreamWriter sw = new StreamWriter(Path.Combine(TomogramDirectory, "pointCloud.json")))
//{
// using (StreamReader sr = new StreamReader(Path.Combine(TomogramDirectory, "pointCloudEnding.ply")))
// {
// sw.WriteLine("{ \"data\": [");
// string l = null;
// while ((l = sr.ReadLine()) != null)
// {
// string[] bits = l.Split(' ');
// sw.WriteLine($"\"{bits[0]} {bits[1]} {bits[2]}\",");
// sw.WriteLine($"\"{bits[3]} {bits[4]} {bits[5]}\",");
// }
// sw.WriteLine($"\"0 0 0\",");
// sw.WriteLine($"\"0 0 0\"");
// sw.WriteLine("]}");
// }
//}
//File.Delete(Path.Combine(TomogramDirectory, "pointCloudEnding.ply"));
}
public static void DoIt()
{
const string TomogramDirectory = @"C:\Users\Ben\Desktop\tomograms";
Console.WriteLine("Loading main file..");
MRCFile file = MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.mrc"));
Console.WriteLine("Loading label files...");
List <MRCFile> labelFiles = new List <MRCFile>();
labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels.mrc")));
labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels2.mrc")));
labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels3.mrc")));
labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels4.mrc")));
labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels5.mrc")));
labelFiles.Add(MRCParser.Parse(Path.Combine(TomogramDirectory, "tomography2_fullsirtcliptrim.labels7.mrc")));
float scaler = 255 / (file.MaxPixelValue - file.MinPixelValue);
Color[] colors = new Color[]
{
Color.Red, Color.Green, Color.Pink, Color.Orange, Color.Yellow, Color.Violet
};
for (int z = 0; z < file.Frames.Count; z++)
{
Console.WriteLine($"File {z}/{file.Frames.Count}");
MRCFrame frame = file.Frames[z];
using (Bitmap bmp = new Bitmap(frame.Width, frame.Height))
{
for (int y = 1; y < frame.Height - 1; y++)
{
for (int x = 1; x < frame.Width - 1; x++)
{
//if(x == 196 && y == 123 && z == 58)
//{
// Console.WriteLine(".");
//}
try
{
int i = y * frame.Width + x;
bool labeled = false;
int colorIndex = 0;
//foreach (MRCFile label in labelFiles)
//{
// if (label.Frames[z].Data[i] > 0)
// {
// bool isEdge = false;
// for (int y1 = y - 1; y1 <= y + 1; y1++)
// {
// for (int x1 = x - 1; x1 <= x + 1; x1++)
// {
// int offsetIndex = y1 * frame.Width + x1;
// if (label.Frames[z].Data[offsetIndex] == 0)
// {
// isEdge = true;
// break;
// }
// }
// }
// if (isEdge)
// {
// byte b = (byte)(frame.Data[i] * scaler);
// bmp.SetPixel((int)(x), (int)(y), colors[colorIndex]);
// labeled = true;
// }
// }
// colorIndex++;
//}
if (!labeled)
{
float v = frame.Data[i] + Math.Abs(file.MinPixelValue);
byte b = (byte)(v * scaler);
bmp.SetPixel((int)(x), (int)(y), Color.FromArgb(b, b, b));
}
}
catch
{
}
}
}
bmp.Save(Path.Combine(TomogramDirectory, $"{z}.png"), ImageFormat.Png);
}
}
}
static void Test()
{
BinaryFormatter bf = new BinaryFormatter();
using (FileStream fs = File.OpenRead("serialized.dat"))
{
DecisionTreeNode node = bf.Deserialize(fs) as DecisionTreeNode;
DecisionTreeOptions options = new DecisionTreeOptions
{
// TODO: Fill in
MaximumNumberOfRecursionLevels = 25,
NumberOfFeatures = 300,
NumberOfThresholds = 35,
OffsetXMax = 40,
OffsetXMin = -40,
OffsetYMax = 40,
OffsetYMin = -40,
OutOfRangeValue = 1000000,
SplittingThresholdMax = .2f,
SufficientGainLevel = 0,
PercentageOfPixelsToUse = .9f,
//DistanceThreshold = .1f,
};
MRCFile file = MRCParser.Parse(Path.Combine("/home/brush/tomography2_fullsirtcliptrim.mrc"));
MRCFrame frame = file.Frames[145];
LabeledTomogram tom = new LabeledTomogram();
tom.Width = frame.Width;
tom.Height = frame.Height;
tom.Data = new float[frame.Width * frame.Height];
for (int i = 0; i < frame.Data.Length; i++)
{
tom.Data[i] = frame.Data[i];
}
//for (int y = 264, i = 0; y < 364; y++)
//{
// for (int x = 501; x < 601; x++, i++)
// {
// tom.Data[i] = frame.Data[y * frame.Width + x];
// }
//}
float[] labels = DecisionTreeBuilder.Predict(tom, node, options);
//Bitmap bmp = DataManipulator.Tomogram2Bitmap(tom);
Bitmap bmp = Drawing.TomogramDrawing.PaintClassifiedPixelsOnTomogram(tom, labels);
bmp.Save("/var/www/html/static/labeled_real.png", System.Drawing.Imaging.ImageFormat.Png);
LabeledTomogram tom2 = DataReader.ReadDatFile("/home/brush/tom4/0.dat");
labels = DecisionTreeBuilder.Predict(tom2, node, options);
//Bitmap bmp = DataManipulator.Tomogram2Bitmap(tom);
bmp = Drawing.TomogramDrawing.PaintClassifiedPixelsOnTomogram(tom2, labels);
bmp.Save("/var/www/html/static/labeled_simulated.png", System.Drawing.Imaging.ImageFormat.Png);
}
}
private static void FinalizeFrame(Tomogram tom, Random rand, MRCFile file,
string serializedSamplerPath)
{
float minValue = file.MinPixelValue;
float maxValue = file.MaxPixelValue;
tom.MRCScaler = 255.0f / (maxValue - minValue);
tom.MinimumTomogramValue = minValue;
int[] classes = tom.DataClasses.Where(n => n != -1).Distinct().ToArray();
Dictionary <int, float> classValues = new Dictionary <int, float>();
for (int c = 0; c < classes.Length; c++)
{
MRCFrame frame = file.Frames[145];// rand.Next(0, file.Frames.Count - 1)];
int randomX = rand.Next(511, 611);
int randomY = rand.Next(292, 392);
int randomIndex = randomY * frame.Width + randomX;
float value = frame.Data[randomIndex];
classValues.Add(classes[c], value);
}
for (int y = 0, i = 0; y < tom.Height; y++)
{
for (int x = 0; x < tom.Width; x++, i++)
{
int classNumber = tom.DataClasses[i];
if (classNumber >= 0)
{
tom.Data[i] = classValues[classNumber];
}
}
}
List <float> distribution = null;
BinaryFormatter bf = new BinaryFormatter();
using (FileStream fin = File.OpenRead(serializedSamplerPath))
{
distribution = bf.Deserialize(fin) as List <float>;
}
int[] mask = new int[tom.Width * tom.Height];
for (int y = 0, i = 0; y < tom.Height; y++)
{
for (int x = 0; x < tom.Width; x++, i++)
{
int classNumber = tom.DataClasses[i];
if (classNumber == -1)
{
tom.Data[i] = distribution[rand.Next(0, distribution.Count - 1)];
mask[i] = 0;
}
else
{
mask[i] = 1;
}
}
}
// tom.Data = blur.BlurData(tom.Data, tom.Width, tom.Height);
GaussianBlur blur = GaussianBlur.BuildBlur(.65f, tom.BlurRadius);
tom.Data = blur.SelectivelyBlurData(tom.Data, mask, tom.Width, tom.Height, 1f, rand);
float[] finalData = new float[tom.FinalHeight * tom.FinalWidth];
int[] finalDataClasses = new int[tom.FinalHeight * tom.FinalWidth];
for (int y = 0, dstIndex = 0; y < tom.FinalHeight; y++)
{
for (int x = 0; x < tom.FinalHeight; x++, dstIndex++)
{
int srcIndex = (y + tom.BlurRadius) * tom.Width + (x + tom.BlurRadius);
finalData[dstIndex] = tom.Data[srcIndex];
finalDataClasses[dstIndex] = tom.DataClasses[srcIndex];
}
}
// hack. clean this up.
tom.Data = finalData;
tom.DataClasses = finalDataClasses;
tom.Width = tom.FinalWidth;
tom.Height = tom.FinalHeight;
}
