private void DumpImage(NPPImage_32fC1 img, string filename)
{
float[] f = new float[img.Width * img.Height];
img.CopyToHost(f);
FileStream fs = File.OpenWrite(filename);
BinaryWriter bw = new BinaryWriter(fs);
bw.Write(img.Width);
bw.Write(img.Height);
for (int i = 0; i < f.Length; i++)
{
bw.Write(f[i]);
}
bw.Close();
fs.Close();
bw.Dispose();
fs.Dispose();
}
static void Main(string[] args)
{
CudaContext ctx = null;
DeBayersSubSampleKernel kernelDeBayersSubSample = null;
DeBayersSubSampleDNGKernel kernelDeBayersSubSampleDNG = null;
SetupCurandKernel kernelSetupCurand = null;
CreateBayerWithNoiseKernel kernelCreateBayerWithNoise = null;
CudaDeviceVariable <ushort> rawImg;
string outputPathOwn = @"C:\Users\kunz_\Desktop\TrainingDataNN\FromOwnDataset\";
string outputPath5k = @"C:\Users\kunz_\Desktop\TrainingDataNN\From5kDataset\";
const int patchSize = 66;
//These are the noise levels I measured for each ISO of my camera:
double[] noiseLevels = new double[] { 6.66667E-05, 0.0001, 0.000192308, 0.000357143, 0.000714286, 0.001388889, 0.0025 };
string[] noiseLevelsFolders = new string[] { "ISO100", "ISO200", "ISO400", "ISO800", "ISO1600", "ISO3200", "ISO6400" };
//Process files from my own dataset:
string[] files = File.ReadAllLines("FileListOwnImages.txt");
if (ctx == null)
{
ctx = new PrimaryContext();
ctx.SetCurrent();
CUmodule mod = ctx.LoadModulePTX("DeBayer.ptx");
kernelDeBayersSubSample = new DeBayersSubSampleKernel(ctx, mod);
kernelDeBayersSubSampleDNG = new DeBayersSubSampleDNGKernel(ctx, mod);
kernelSetupCurand = new SetupCurandKernel(ctx, mod);
kernelCreateBayerWithNoise = new CreateBayerWithNoiseKernel(ctx, mod);
}
FileStream fs = new FileStream("ImagesCompleted.txt", FileMode.Append, FileAccess.Write);
StreamWriter sw = new StreamWriter(fs);
PEFFile pef = new PEFFile(files[0]);
BayerColor[] bayerPattern = new BayerColor[pef.BayerPattern.Length];
for (int i = 0; i < pef.BayerPattern.Length; i++)
{
bayerPattern[i] = (BayerColor)pef.BayerPattern[i];
}
kernelDeBayersSubSample.BayerPattern = bayerPattern;
rawImg = new CudaDeviceVariable <ushort>(pef.RawWidth * pef.RawHeight);
NPPImage_32fC3 img = new NPPImage_32fC3(pef.RawWidth / 2, pef.RawHeight / 2);
NPPImage_32fC3 imgsmall = new NPPImage_32fC3(pef.RawWidth / 8, pef.RawHeight / 8);
NPPImage_32fC3 patch = new NPPImage_32fC3(patchSize, patchSize);
NPPImage_32fC1 patchBayerWithNoise = new NPPImage_32fC1(patchSize, patchSize);
//NPPImage_8uC3 img8u = new NPPImage_8uC3(patchSize, patchSize);
//Bitmap bmp = new Bitmap(patchSize, patchSize, System.Drawing.Imaging.PixelFormat.Format24bppRgb);
CudaDeviceVariable <byte> states = new CudaDeviceVariable <byte>(patchSize * patchSize * 48); //one state has the size of 48 bytes
kernelSetupCurand.RunSafe(states, patchSize * patchSize);
NppiRect maxRoi = new NppiRect(10, 10, pef.RawWidth / 8 - 10, pef.RawHeight / 8 - 10);
List <NppiRect> ROIs = GetROIs(maxRoi, patchSize);
float3[] imgGroundTruth = new float3[patchSize * patchSize];
float[] noisyPatchBayer = new float[patchSize * patchSize];
int counter = 0;
int fileCounter = 0;
FileStream fsWB1 = new FileStream("WhiteBalancesOwn.txt", FileMode.Create, FileAccess.Write);
StreamWriter swWB1 = new StreamWriter(fsWB1);
foreach (var file in files)
{
pef = new PEFFile(file);
float whiteLevelAll = pef.WhiteLevel.Value;
float3 whitePoint = new float3(whiteLevelAll, whiteLevelAll, whiteLevelAll);
float3 blackPoint = new float3(pef.BlackPoint.Value[0], pef.BlackPoint.Value[1], pef.BlackPoint.Value[3]);
whitePoint -= blackPoint;
float scale = pef.Scaling.Value;
float3 scaling = new float3(pef.WhitePoint.Value[0] / scale, pef.WhitePoint.Value[1] / scale, pef.WhitePoint.Value[3] / scale);
int RoiCounter = 0;
foreach (var roi in ROIs)
{
swWB1.WriteLine((counter + RoiCounter).ToString("0000000") + "\t" + scaling.x.ToString(CultureInfo.InvariantCulture) + "\t" + scaling.y.ToString(CultureInfo.InvariantCulture) + "\t" + scaling.z.ToString(CultureInfo.InvariantCulture));
RoiCounter++;
}
fileCounter++;
Console.WriteLine("Done " + fileCounter + " of " + files.Length);
rawImg.CopyToDevice(pef.RawImage);
kernelDeBayersSubSample.RunSafe(rawImg, img, (float)Math.Pow(2.0, pef.BitDepth));
imgsmall.ResetRoi();
img.ResizeSqrPixel(imgsmall, 0.25, 0.25, 0, 0, InterpolationMode.SuperSampling);
RoiCounter = 0;
foreach (var roi in ROIs)
{
imgsmall.SetRoi(roi);
imgsmall.Copy(patch);
patch.CopyToHost(imgGroundTruth);
WriteRAWFile(outputPathOwn + @"GroundTruth\img_" + (counter + RoiCounter).ToString("0000000") + ".bin", imgGroundTruth, patchSize, patchSize);
RoiCounter++;
}
RoiCounter = 0;
foreach (var roi in ROIs)
{
imgsmall.SetRoi(roi);
for (int i = 0; i < 7; i++)
{
imgsmall.Copy(patch);
kernelCreateBayerWithNoise.RunSafe(states, patch, patchBayerWithNoise, (float)noiseLevels[i], 0);
patchBayerWithNoise.CopyToHost(noisyPatchBayer);
WriteRAWFile(outputPathOwn + noiseLevelsFolders[i] + @"\img_" + (counter + RoiCounter).ToString("0000000") + ".bin", noisyPatchBayer, patchSize, patchSize);
}
RoiCounter++;
}
fileCounter++;
counter += ROIs.Count;
Console.WriteLine("Done " + fileCounter + " of " + files.Length);
sw.WriteLine(file);
sw.Flush();
}
sw.Close();
sw.Dispose();
swWB1.Flush();
swWB1.Close();
rawImg.Dispose();
img.Dispose();
imgsmall.Dispose();
patch.Dispose();
patchBayerWithNoise.Dispose();
//Move on to DNG images from 5k dataset:
files = File.ReadAllLines("FileListe5KKomplett.txt");
fs = new FileStream("ImagesCompleted5k.txt", FileMode.Append, FileAccess.Write);
sw = new StreamWriter(fs);
DNGFile dng = new DNGFile(files[0]);
int maxWidth = 7000;
int maxHeight = 5000;
rawImg = new CudaDeviceVariable <ushort>(maxWidth * maxHeight);
img = new NPPImage_32fC3(maxWidth, maxHeight); // /2
imgsmall = new NPPImage_32fC3(maxWidth, maxHeight); // /8
patch = new NPPImage_32fC3(patchSize, patchSize);
patchBayerWithNoise = new NPPImage_32fC1(patchSize, patchSize);
imgGroundTruth = new float3[patchSize * patchSize];
noisyPatchBayer = new float[patchSize * patchSize];
counter = 0;
fileCounter = 0;
int roiCount = 0;
FileStream fsWB2 = new FileStream("WhiteBalances5k.txt", FileMode.Create, FileAccess.Write);
StreamWriter swWB2 = new StreamWriter(fsWB2);
foreach (var file in files)
{
dng = new DNGFile(file);
bayerPattern = new BayerColor[dng.BayerPattern.Length];
for (int i = 0; i < dng.BayerPattern.Length; i++)
{
bayerPattern[i] = (BayerColor)dng.BayerPattern[i];
}
kernelDeBayersSubSampleDNG.BayerPattern = bayerPattern;
maxRoi = new NppiRect(10, 10, dng.RawWidth / 8 - 10, dng.RawHeight / 8 - 10);
ROIs = GetROIs(maxRoi, patchSize);
roiCount += ROIs.Count;
float[] wb = dng.AsShotNeutral;
int RoiCounter = 0;
foreach (var roi in ROIs)
{
swWB2.WriteLine((counter + RoiCounter).ToString("0000000") + "\t" + (1.0f / wb[0]).ToString(CultureInfo.InvariantCulture) + "\t" + (1.0f / wb[1]).ToString(CultureInfo.InvariantCulture) + "\t" + (1.0f / wb[2]).ToString(CultureInfo.InvariantCulture));
RoiCounter++;
}
fileCounter++;
Console.WriteLine("Done " + fileCounter + " of " + files.Length);
Console.WriteLine("RoiCoint: " + ROIs.Count);
unsafe
{
fixed(ushort *ptr = dng.RawImage)
{
rawImg.CopyToDevice((IntPtr)ptr, 0, 0, dng.RawWidth * dng.RawHeight * 2);
}
}
NppiRect rect = new NppiRect(0, 0, dng.RawWidth / 2, dng.RawHeight / 2);
img.SetRoi(rect);
kernelDeBayersSubSampleDNG.RunSafe(rawImg, img, dng.MaxVal, dng.MinVal);
rect = new NppiRect(0, 0, dng.RawWidth / 8, dng.RawHeight / 8);
imgsmall.SetRoi(rect);
img.ResizeSqrPixel(imgsmall, 0.25, 0.25, 0, 0, InterpolationMode.SuperSampling);
RoiCounter = 0;
foreach (var roi in ROIs)
{
imgsmall.SetRoi(roi);
imgsmall.Copy(patch);
patch.CopyToHost(imgGroundTruth);
WriteRAWFile(outputPath5k + @"GroundTruth\img_" + (counter + RoiCounter).ToString("0000000") + ".bin", imgGroundTruth, patchSize, patchSize);
RoiCounter++;
}
RoiCounter = 0;
foreach (var roi in ROIs)
{
imgsmall.SetRoi(roi);
for (int i = 0; i < 7; i++)
{
imgsmall.Copy(patch);
kernelCreateBayerWithNoise.RunSafe(states, patch, patchBayerWithNoise, (float)noiseLevels[i], 0);
patchBayerWithNoise.CopyToHost(noisyPatchBayer);
WriteRAWFile(outputPath5k + noiseLevelsFolders[i] + @"\img_" + (counter + RoiCounter).ToString("0000000") + ".bin", noisyPatchBayer, patchSize, patchSize);
}
RoiCounter++;
}
fileCounter++;
counter += ROIs.Count;
Console.WriteLine("Done " + fileCounter + " of " + files.Length);
sw.WriteLine(file);
sw.Flush();
}
sw.Close();
sw.Dispose();
swWB2.Flush();
swWB2.Close();
Console.WriteLine("Total cropped ROIs: " + roiCount);
rawImg.Dispose();
img.Dispose();
imgsmall.Dispose();
patch.Dispose();
patchBayerWithNoise.Dispose();
states.Dispose();
ctx.Dispose();
}