Added variable-size 2D correlation output (651267f2) · Commits · Elphel / imagej-elphel

src/main/java/com/elphel/imagej/cameras/CLTParameters.java

+11 −0

Original line number	Diff line number	Diff line
		@@ -772,6 +772,7 @@ public class CLTParameters {
		public double gpu_sigma_b = 1.1;
		public double gpu_sigma_g = 0.7;
		public double gpu_sigma_m = 0.7;
		public double gpu_sigma_rb_corr = 0.5; // apply LPF after accumulating R and B correlation before G,
		public double gpu_sigma_corr = 0.9;
		public double gpu_sigma_corr_m = 0.15;
		public double gpu_fatz = 30.0;
		@@ -837,6 +838,9 @@ public class CLTParameters {
		return monochrome ? gpu_sigma_corr_m : gpu_sigma_corr;
		}

		public double getGpuCorrRBSigma(boolean monochrome) {
		return monochrome ? 1.0 : gpu_sigma_rb_corr;
		}

		public double getScaleStrength(boolean aux) {
		return aux ? scale_strength_aux : scale_strength_main;
		@@ -1540,6 +1544,7 @@ public class CLTParameters {
		properties.setProperty(prefix+"gpu_sigma_b", this.gpu_sigma_b +"");
		properties.setProperty(prefix+"gpu_sigma_g", this.gpu_sigma_g +"");
		properties.setProperty(prefix+"gpu_sigma_m", this.gpu_sigma_m +"");
		properties.setProperty(prefix+"gpu_sigma_rb_corr", this.gpu_sigma_rb_corr +"");
		properties.setProperty(prefix+"gpu_sigma_corr", this.gpu_sigma_corr +"");
		properties.setProperty(prefix+"gpu_sigma_corr_m", this.gpu_sigma_corr_m +"");
		properties.setProperty(prefix+"gpu_fatz", this.gpu_fatz +"");
		@@ -2305,6 +2310,7 @@ public class CLTParameters {
		if (properties.getProperty(prefix+"gpu_sigma_b")!=null) this.gpu_sigma_b=Double.parseDouble(properties.getProperty(prefix+"gpu_sigma_b"));
		if (properties.getProperty(prefix+"gpu_sigma_g")!=null) this.gpu_sigma_g=Double.parseDouble(properties.getProperty(prefix+"gpu_sigma_g"));
		if (properties.getProperty(prefix+"gpu_sigma_m")!=null) this.gpu_sigma_m=Double.parseDouble(properties.getProperty(prefix+"gpu_sigma_m"));
		if (properties.getProperty(prefix+"gpu_sigma_rb_corr")!=null) this.gpu_sigma_rb_corr=Double.parseDouble(properties.getProperty(prefix+"gpu_sigma_rb_corr"));
		if (properties.getProperty(prefix+"gpu_sigma_corr")!=null) this.gpu_sigma_corr=Double.parseDouble(properties.getProperty(prefix+"gpu_sigma_corr"));
		if (properties.getProperty(prefix+"gpu_sigma_corr_m")!=null) this.gpu_sigma_corr_m=Double.parseDouble(properties.getProperty(prefix+"gpu_sigma_corr_m"));
		if (properties.getProperty(prefix+"gpu_fatz")!=null) this.gpu_fatz=Double.parseDouble(properties.getProperty(prefix+"gpu_fatz"));
		@@ -3211,6 +3217,7 @@ public class CLTParameters {
		"Weight of R for composite 2D correlation (green weight is 1.0 -gpu_weight_r - gpu_weight_b");
		gd.addNumericField("Correlation weight B", this.gpu_weight_b, 4, 6,"",
		"Weight of R for composite 2D correlation (green weight is 1.0 -gpu_weight_r - gpu_weight_b");
		gd.addMessage ("--- LPF sigmas used for images/textures ---");
		gd.addNumericField("Color LPF sigma R", this.gpu_sigma_r, 4, 6,"pix",
		"LPF sigma to process color components during aberration correction");
		gd.addNumericField("Color LPF sigma B", this.gpu_sigma_b, 4, 6,"pix",
		@@ -3219,6 +3226,9 @@ public class CLTParameters {
		"LPF sigma to process color components during aberration correction");
		gd.addNumericField("Monochrome LPF sigma", this.gpu_sigma_m, 4, 6,"pix",
		"LPF sigma to process monochrome (e.g.LWIR) during aberration correction");
		gd.addMessage ("--- LPF sigmas used for 2D phase correlation ---");
		gd.addNumericField("LPF sigma Red/Blue (extra)", this.gpu_sigma_rb_corr, 4, 6,"pix",
		"LPF sigma to apply to the composite R+B 2D correlation before adding G (next LPF will be applied to R+B+G correlation");
		gd.addNumericField("LPF sigma for correlation, color", this.gpu_sigma_corr, 4, 6,"pix",
		"LPF sigma to apply to the composite 2D correlation for RGB images");
		gd.addNumericField("LPF sigma for correlation, mono", this.gpu_sigma_corr_m, 4, 6,"pix",
		@@ -3964,6 +3974,7 @@ public class CLTParameters {
		this.gpu_sigma_b = gd.getNextNumber();
		this.gpu_sigma_g = gd.getNextNumber();
		this.gpu_sigma_m = gd.getNextNumber();
		this.gpu_sigma_rb_corr = gd.getNextNumber();
		this.gpu_sigma_corr = gd.getNextNumber();
		this.gpu_sigma_corr_m = gd.getNextNumber();
		this.gpu_fatz = gd.getNextNumber();

src/main/java/com/elphel/imagej/gpu/GPUTileProcessor.java

+10 −8

Original line number	Diff line number	Diff line
		@@ -765,7 +765,8 @@ public class GPUTileProcessor {

		public void execCorr2D(
		double [] scales,
		double fat_zero) {
		double fat_zero,
		int corr_radius) {
		if (GPU_CORRELATE2D_kernel == null)
		{
		IJ.showMessage("Error", "No GPU kernel: GPU_CORRELATE2D_kernel");
		@@ -788,6 +789,7 @@ public class GPUTileProcessor {
		Pointer.to(new int[] { num_corr_tiles }), // lpf_mask
		Pointer.to(gpu_corr_indices),
		Pointer.to(new int[] { corr_stride }),
		Pointer.to(new int[] { corr_radius }),
		Pointer.to(gpu_corrs) // lpf_mask
		);
		cuCtxSynchronize();
		@@ -800,9 +802,9 @@ public class GPUTileProcessor {
		cuCtxSynchronize();
		}

		public float [][] getCorr2D(){
		float [] cpu_corrs = new float [ num_corr_tiles * CORR_SIZE];

		public float [][] getCorr2D(int corr_rad){
		int corr_size = (2 * corr_rad + 1) * (2 * corr_rad + 1);
		float [] cpu_corrs = new float [ num_corr_tiles * corr_size];
		CUDA_MEMCPY2D copyD2H = new CUDA_MEMCPY2D();
		copyD2H.srcMemoryType = CUmemorytype.CU_MEMORYTYPE_DEVICE;
		copyD2H.srcDevice = gpu_corrs;
		@@ -810,16 +812,16 @@ public class GPUTileProcessor {

		copyD2H.dstMemoryType = CUmemorytype.CU_MEMORYTYPE_HOST;
		copyD2H.dstHost = Pointer.to(cpu_corrs);
		copyD2H.dstPitch = CORR_SIZE * Sizeof.FLOAT;
		copyD2H.dstPitch = corr_size * Sizeof.FLOAT;

		copyD2H.WidthInBytes = CORR_SIZE * Sizeof.FLOAT;
		copyD2H.WidthInBytes = corr_size * Sizeof.FLOAT;
		copyD2H.Height = num_corr_tiles;

		cuMemcpy2D(copyD2H); // run copy

		float [][] corrs = new float [num_corr_tiles][ CORR_SIZE];
		float [][] corrs = new float [num_corr_tiles][ corr_size];
		for (int ncorr = 0; ncorr < num_corr_tiles; ncorr++) {
		System.arraycopy(cpu_corrs, ncorr*CORR_SIZE, corrs[ncorr], 0, CORR_SIZE);
		System.arraycopy(cpu_corrs, ncorr*corr_size, corrs[ncorr], 0, corr_size);
		}
		return corrs;
		}

src/main/java/com/elphel/imagej/tileprocessor/ImageDtt.java

+33 −0

Original line number	Diff line number	Diff line
		@@ -9113,11 +9113,15 @@ public class ImageDtt {
		final int transform_len = transform_size*transform_size;
		final double afat_zero2 = clt_parameters.getGpuFatZero(is_mono); // ? clt_parameters.gpu_fatz_m : clt_parameters.gpu_fatz;
		final double sigma_corr = clt_parameters.getGpuCorrSigma(is_mono); // ? clt_parameters.gpu_sigma_corr_m : clt_parameters.gpu_sigma_corr;
		final double sigma_rb_corr = clt_parameters.getGpuCorrRBSigma(is_mono);
		final int corr_radius = clt_parameters.gpu_corr_rad;
		// final double[] lpf = getLpf(sigma_corr);

		final double[] lpf_fd = doubleGetCltLpfFd(
		sigma_corr);
		final double[] lpf_rb_fd = doubleGetCltLpfFd(
		sigma_rb_corr);

		for (int ithread = 0; ithread < threads.length; ithread++) {
		threads[ithread] = new Thread() {
		@Override
		@@ -9199,6 +9203,35 @@ public class ImageDtt {
		}
		}
		}
		//c
		if (c == 1) { // after red and blue, color only
		if (lpf_rb_fd != null) {
		for (int n = 0; n<4; n++) {
		for (int i = 0; i < transform_len; i++) {
		tcorr[n][i] *= lpf_rb_fd[i];
		}
		}
		if (debug_gpu && debug_tile) {
		System.out.println("=== LPF-RB for CORRELATION ===");
		for (int i = 0; i < transform_size; i++) {
		for (int j = 0; j < transform_size; j++) {
		System.out.print(String.format("%10.5f ", lpf_rb_fd[transform_size * i + j]));
		}
		System.out.println();
		}
		System.out.println("=== R+B LPF-ed CORRELATION ===");
		for (int dct_mode = 0; dct_mode < 4; dct_mode++) {
		System.out.println("------dct_mode="+dct_mode);
		for (int i = 0; i < transform_size; i++) {
		for (int j = 0; j < transform_size; j++) {
		System.out.print(String.format("%10.3f ", tcorr[dct_mode][transform_size * i + j]));
		}
		System.out.println();
		}
		}
		}
		}
		}
		}
		}
		corrs2d[n_corr] = correlation2d.normalizeConvertCorr(

src/main/java/com/elphel/imagej/tileprocessor/TwoQuadCLT.java

+6 −4

Original line number	Diff line number	Diff line
		@@ -1994,7 +1994,8 @@ public class TwoQuadCLT {

		for (int i = 0; i < NREPEAT; i++ ) gPUTileProcessor.execCorr2D(
		scales,// double [] scales,
		fat_zero); // double fat_zero);
		fat_zero, // double fat_zero);
		clt_parameters.gpu_corr_rad); // int corr_radius

		long endCorr2d = System.nanoTime();

		@@ -2037,12 +2038,13 @@ public class TwoQuadCLT {
		debugLevel );

		}
		float [][] corr2D = gPUTileProcessor.getCorr2D();
		float [][] corr2D = gPUTileProcessor.getCorr2D(
		clt_parameters.gpu_corr_rad); // int corr_rad);
		// convert to 6-layer image using tasks
		int tilesX = GPUTileProcessor.IMG_WIDTH / GPUTileProcessor.DTT_SIZE;
		int tilesY = GPUTileProcessor.IMG_HEIGHT / GPUTileProcessor.DTT_SIZE;
		int [] wh = new int[2];
		double [][] dbg_corr = gPUTileProcessor.getCorr2DView(
		double [][] dbg_corr = GPUTileProcessor.getCorr2DView(
		tilesX,
		tilesY,
		corr_indices,
		@@ -2054,7 +2056,7 @@ public class TwoQuadCLT {
		wh[1],
		true,
		"CORR2D",
		gPUTileProcessor.getCorrTitles());
		GPUTileProcessor.getCorrTitles());

		if (clt_parameters.gen_chn_img) {
		// combine to a sliced color image

src/main/resources/TileProcessor.cuh

+49 −42

Original line number	Diff line number	Diff line
		@@ -57,7 +57,8 @@
		#define IMCLT_TILES_PER_BLOCK 4
		#define CORR_PAIR_SHIFT 8 // 8 lower bits - number of a pair, other bits tile number
		#define TASK_CORR_BITS 4
		#define CORR_OUT_RAD 7
		#define CORR_OUT_RAD 4
		//7


		#endif
		@@ -376,6 +377,7 @@ __device__ void debug_print_mclt(
		float * mclt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports)
		const int color);
		__device__ void debug_print_corr_15x15(
		int corr_radius,
		float * mclt_tile, //DTT_SIZE2M1 x DTT_SIZE2M1
		const int color);
		// Fractional pixel shift (phase rotation), horizontal. In-place.
		@@ -400,6 +402,7 @@ __device__ void normalizeTileAmplitude(
		float * clt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports
		float fat_zero); // fat zero is absolute, scale it outside
		__device__ void corrUnfoldTile(
		int corr_radius,
		float* qdata0, // [4][DTT_SIZE][DTT_SIZE1], // 4 quadrants of the clt data, rows extended to optimize shared ports
		float* rslt); // [DTT_SIZE2M1][DTT_SIZE2M1]) // 15x15
		__device__ void imclt( // implemented, used // why is it twice?
		@@ -426,6 +429,7 @@ __global__ void correlate2D(
		size_t num_corr_tiles, // number of correlation tiles to process
		int * gpu_corr_indices, // packed tile+pair
		const size_t corr_stride, // in floats
		int corr_radius, // radius of the output correlation (7 for 15x15)
		float * gpu_corrs) // correlation output data
		{
		/// int thr3 = threadIdx.x >> 3; // now zero?
		@@ -559,27 +563,17 @@ __global__ void correlate2D(
		#endif
		#endif


		// now new part - need to transform with DCT-II and make 15x15
		/*
		// quadrant 0 dct_ii hor, dct_ii vert,
		// quadrant 1 dct_ii hor, dst_ii vert,
		// quadrant 2 dst_ii hor, dct_ii vert,
		// quadrant 3 dst_ii hor, dst_ii vert,
		Java code:
		for (int quadrant = 0; quadrant < 4; quadrant++){
		int mode = ((quadrant << 1) & 2) \| ((quadrant >> 1) & 1); // transpose
		tcorr[first_col][quadrant] = dtt.dttt_iie(tcorr[first_col][quadrant], mode, transform_size);
		}

		*/
		// change to 16-32 threads?? in next iteration
		// hor pass
		// vert pass (hor pass in Java, before transpose. Here transposed, no transform needed)
		for (int q = 0; q < 4; q++){
		int is_sin = (q >> 1) & 1;
		// int is_sin = q & 1;
		// dttii_shared_mem(clt_corr + (q * DTT_SIZE + threadIdx.x) * DTT_SIZE1 , 1, is_sin); // horizontal pass, tread is row
		// dttii_shared_mem(clt_corr + q * (DTT_SIZE1 * DTT_SIZE) + threadIdx.x , DTT_SIZE1, is_sin); // vertical pass, thread is column
		dttii_shared_mem_nonortho(clt_corr + q * (DTT_SIZE1 * DTT_SIZE) + threadIdx.x , DTT_SIZE1, is_sin); // vertical pass, thread is column
		}
		__syncthreads();
		@@ -593,26 +587,25 @@ Java code:
		#endif
		#endif

		// vert pass
		// hor pass, corresponding to vert pass in Java
		for (int q = 0; q < 4; q++){
		int is_sin = q & 1;
		// int is_sin = (q >> 1) & 1;
		// dttii_shared_mem(clt_corr + q * (DTT_SIZE1 * DTT_SIZE) + threadIdx.x , DTT_SIZE1, is_sin); // vertical pass, thread is column
		// dttii_shared_mem(clt_corr + (q * DTT_SIZE + threadIdx.x) * DTT_SIZE1 , 1, is_sin); // horizontal pass, tread is row
		dttii_shared_mem_nonortho(clt_corr + (q * DTT_SIZE + threadIdx.x) * DTT_SIZE1 , 1, is_sin); // horizontal pass, tread is row
		}
		__syncthreads();
		#ifdef DBG_TILE
		#ifdef DEBUG6
		if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
		printf("\ncorrelate2D AFTER HOSIZONTAL (VERTICAL) PASS\n");
		if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 4)){
		printf("\ncorrelate2D AFTER HOSIZONTAL (VERTICAL) PASS, corr_radius=%d\n",corr_radius);
		debug_print_clt1(clt_corr, -1, 0xf);
		}
		__syncthreads();// __syncwarp();

		#endif
		#endif

		corrUnfoldTile(
		corr_radius, // int corr_radius,
		(float ) clt_corr, // float qdata0, // [4][DTT_SIZE][DTT_SIZE1], // 4 quadrants of the clt data, rows extended to optimize shared ports
		(float ) mclt_corr); // float rslt) // [DTT_SIZE2M1][DTT_SIZE2M1]) // 15x15

		@@ -621,23 +614,28 @@ Java code:
		#ifdef DBG_TILE
		#ifdef DEBUG6
		if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
		printf("\ncorrelate2D after UNFOLD\n");
		debug_print_corr_15x15(mclt_corr, -1);
		printf("\ncorrelate2D after UNFOL, corr_radius=%d\n",corr_radius);
		debug_print_corr_15x15(
		corr_radius, // int corr_radius,
		mclt_corr,
		-1);
		}
		__syncthreads();// __syncwarp();
		#endif
		#endif

		// copy 15x15 tile to main memory
		// searching for bug. Uncomment later
		// copy 15x15 tile to main memory (2 * corr_radius +1) x (2 * corr_radius +1)
		int size2r1 = 2 * corr_radius + 1;
		int len2r1x2r1 = size2r1 * size2r1;
		int corr_tile_offset = + corr_stride * corr_num;
		float *mem_corr = gpu_corrs + corr_tile_offset;

		//CORR_THREADS_PER_TILE
		// int offs = threadIdx.x;
		#pragma unroll
		for (int offs = threadIdx.x; offs < DTT_SIZE2M1*DTT_SIZE2M1; offs+=CORR_THREADS_PER_TILE){ // variable number of cycles per thread
		// for (int offs = threadIdx.x; offs < DTT_SIZE2M1*DTT_SIZE2M1; offs+=CORR_THREADS_PER_TILE){ // variable number of cycles per thread
		for (int offs = threadIdx.x; offs < len2r1x2r1; offs+=CORR_THREADS_PER_TILE){ // variable number of cycles per thread
		mem_corr[offs] = mclt_corr[offs];
		}

		__syncthreads();
		#ifdef DBG_TILE
		#ifdef DEBUG6
		@@ -969,27 +967,36 @@ Converted from DttRad2.java:443
		)
		*/
		__device__ void corrUnfoldTile(
		int corr_radius,
		float* qdata0, // [4][DTT_SIZE][DTT_SIZE1], // 4 quadrants of the clt data, rows extended to optimize shared ports
		float* rslt) // [DTT_SIZE2M1][DTT_SIZE2M1]) // 15x15
		{
		const int rslt_base_index = DTT_SIZE2M1 * (DTT_SIZE) - DTT_SIZE;
		int size2r1 = 2 * corr_radius + 1; // 15
		int crp1 = corr_radius + 1; //8
		/// const int rslt_base_index = DTT_SIZE2M1 * (DTT_SIZE) - DTT_SIZE; // offset of the center
		int rslt_base_index = size2r1 * crp1 - crp1; // offset of the center

		float * qdata1 = qdata0 + (DTT_SIZE * DTT_SIZE1);
		float * qdata2 = qdata1 + (DTT_SIZE * DTT_SIZE1);
		float * qdata3 = qdata2 + (DTT_SIZE * DTT_SIZE1);
		int i = threadIdx.x;
		if (i > corr_radius) {
		return; // not needed, only use inner
		}
		// printf("\corrUnfoldTile() corr_radius=%d, i=%d\n",corr_radius,i);
		float corr_pixscale = 0.25f;
		int i_transform_size = i * DTT_SIZE1; // used to address source rows which are 9 long
		int im1_transform_size = i_transform_size - DTT_SIZE1; // negative for i = 0, use only after divergence
		int rslt_row_offs = i * DTT_SIZE2M1;
		/// int rslt_row_offs = i * DTT_SIZE2M1;
		int rslt_row_offs = i * size2r1;
		int rslt_base_index_p = rslt_base_index + rslt_row_offs; // i * DTT_SIZE2M1;
		int rslt_base_index_m = rslt_base_index - rslt_row_offs; // i * DTT_SIZE2M1;
		rslt[rslt_base_index_p] = corr_pixscale * qdata0[i_transform_size]; // incomplete, will only be used for thread i=0
		rslt[rslt_base_index_m] = rslt[rslt_base_index_p]; // nop for i=0 incomplete, will only be used for thread i=0
		for (int j = 1; j < DTT_SIZE; j++) {
		/// for (int j = 1; j < DTT_SIZE; j++) {
		for (int j = 1; j <= corr_radius; j++) {
		int rslt_base_index_pp = rslt_base_index_p + j;
		int rslt_base_index_pm = rslt_base_index_p - j;
		/// int rslt_base_index_mp = rslt_base_index_m + j;
		/// int rslt_base_index_mm = rslt_base_index_m - j;
		rslt[rslt_base_index_pp] = corr_pixscale * (
		qdata0[i_transform_size + j] +
		qdata1[i_transform_size + j -1]); // incomplete, will only be used for thread i=0
		@@ -1000,12 +1007,11 @@ __device__ void corrUnfoldTile(
		if (i == 0) {
		return;
		}
		/// int im1 = i-1;
		im1_transform_size = i_transform_size - DTT_SIZE1;
		/// im1_transform_size = i_transform_size - DTT_SIZE1; // already is calculated
		float d = corr_pixscale * qdata2[im1_transform_size];
		rslt[rslt_base_index_p] += d;
		rslt[rslt_base_index_m] -= d;
		for (int j = 1; j < DTT_SIZE; j++) {
		for (int j = 1; j <= corr_radius; j++) {
		int rslt_base_index_pp = rslt_base_index_p + j;
		int rslt_base_index_pm = rslt_base_index_p - j;
		int rslt_base_index_mp = rslt_base_index_m + j;
		@@ -1068,14 +1074,15 @@ __device__ void debug_print_mclt(
		}

		__device__ void debug_print_corr_15x15(
		int corr_radius,
		float * mclt_tile, //DTT_SIZE2M1 x DTT_SIZE2M1
		const int color)
		{

		int size2r1 = 2 * corr_radius + 1;
		if (color >= 0) printf("----------- Color = %d -----------\n",color);
		for (int dbg_row = 0; dbg_row < DTT_SIZE2M1; dbg_row++){
		for (int dbg_col = 0; dbg_col < DTT_SIZE2M1; dbg_col++){
		printf ("%10.5f ", mclt_tile[dbg_row * DTT_SIZE2M1 + dbg_col]);
		for (int dbg_row = 0; dbg_row < size2r1; dbg_row++){
		for (int dbg_col = 0; dbg_col < size2r1; dbg_col++){
		printf ("%10.5f ", mclt_tile[dbg_row * size2r1 + dbg_col]);
		}
		printf("\n");
		}

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