Пример #1
0
        private void Form1_Load(object sender, EventArgs e)
        {
            ctx = new PrimaryContext();
            ctx.SetCurrent();

            modPRelu   = ctx.LoadModulePTX("PRelu.ptx");
            modDeBayer = ctx.LoadModulePTX("DeBayer.ptx");
            modColor   = ctx.LoadModulePTX("ImageColorProcessing.ptx");

            createBayerKernel       = new CreateBayerWithNoiseKernel(ctx, modDeBayer);
            deBayerGreenKernel      = new DeBayerGreenKernel(modDeBayer, ctx);
            deBayerRedBlueKernel    = new DeBayerRedBlueKernel(modDeBayer, ctx);
            setupCurandKernel       = new SetupCurandKernel(ctx, modDeBayer);
            highlightRecoveryKernel = new HighlightRecoveryKernel(modColor, ctx);
            camToXYZKernel          = new ConvertCamToXYZKernel(modColor, ctx);
            convertRGBTosRGBKernel  = new ConvertRGBTosRGBKernel(modColor, ctx);

            //constant variable is set for the entire module!
            createBayerKernel.BayerPattern = new BayerColor[] { BayerColor.Red, BayerColor.Green, BayerColor.Green, BayerColor.Blue };

            //If you do not have CUDNN, set the last parameter to false (use NPP instead)
            denoiseAndDemoisaic = new DenoiseAndDemoisaic(TileSize, ctx, modPRelu, true);
            CuRandStates        = new CudaDeviceVariable <byte>(TileSize * TileSize * 48); //one state has the size of 48 bytes
            setupCurandKernel.RunSafe(CuRandStates, TileSize * TileSize);
            tile = new NPPImage_32fC3(TileSize, TileSize);
            cmb_IsoValue.SelectedIndex = 0;
        }
Пример #2
0
        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();
        }