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imagej-elphel
Commit fa5947b6 authored by Andrey Filippov's avatar Andrey Filippov
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tested gpu intrascene

parent 2eae496d
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Showing with 364 additions and 56 deletions
src/main/java/com/elphel/imagej/gpu/GPUTileProcessor.java
View file @ fa5947b6
......@@ -100,6 +100,8 @@ public class GPUTileProcessor {
static String GPU_CONVERT_DIRECT_NAME = "convert_direct"; // name in C code
static String GPU_IMCLT_ALL_NAME = "imclt_rbg_all";
static String GPU_CORRELATE2D_NAME = "correlate2D"; // name in C code
static String GPU_CORR2D_COMBINE_NAME = "corr2D_combine"; // name in C code
static String GPU_CORR2D_NORMALIZE_NAME = "corr2D_normalize"; // name in C code
static String GPU_TEXTURES_NAME = "textures_nonoverlap"; // name in C code
static String GPU_RBGA_NAME = "generate_RBGA"; // name in C code
static String GPU_ROT_DERIV = "calc_rot_deriv"; // calculate rotation matrices and derivatives
......@@ -122,6 +124,8 @@ public class GPUTileProcessor {
static int TILES_PER_BLOCK = 4; // 8 - slower
static int CORR_THREADS_PER_TILE = 8;
static int CORR_TILES_PER_BLOCK = 4;
static int CORR_TILES_PER_BLOCK_NORMALIZE = 4; // maybe change to 8?
static int CORR_TILES_PER_BLOCK_COMBINE = 4; // increase to 16?
static int TEXTURE_THREADS_PER_TILE = 8; // 16;
static int TEXTURE_TILES_PER_BLOCK = 1;
static int IMCLT_THREADS_PER_TILE = 16;
......@@ -159,6 +163,8 @@ public class GPUTileProcessor {
private CUfunction GPU_CONVERT_DIRECT_kernel = null;
private CUfunction GPU_IMCLT_ALL_kernel = null;
private CUfunction GPU_CORRELATE2D_kernel = null;
private CUfunction GPU_CORR2D_COMBINE_kernel = null;
private CUfunction GPU_CORR2D_NORMALIZE_kernel = null;
private CUfunction GPU_TEXTURES_kernel = null;
private CUfunction GPU_RBGA_kernel = null;
private CUfunction GPU_ROT_DERIV_kernel = null;
......@@ -248,6 +254,8 @@ public class GPUTileProcessor {
"#define TILES_PER_BLOCK " + TILES_PER_BLOCK+"\n"+
"#define CORR_THREADS_PER_TILE " + CORR_THREADS_PER_TILE+"\n"+
"#define CORR_TILES_PER_BLOCK " + CORR_TILES_PER_BLOCK+"\n"+
"#define CORR_TILES_PER_BLOCK_NORMALIZE " + CORR_TILES_PER_BLOCK_NORMALIZE+"\n"+
"#define CORR_TILES_PER_BLOCK_COMBINE " + CORR_TILES_PER_BLOCK_COMBINE+"\n"+
"#define TEXTURE_THREADS_PER_TILE " + TEXTURE_THREADS_PER_TILE+"\n"+
"#define TEXTURE_TILES_PER_BLOCK " + TEXTURE_TILES_PER_BLOCK+"\n"+
"#define IMCLT_THREADS_PER_TILE " + IMCLT_THREADS_PER_TILE+"\n"+
......@@ -267,8 +275,6 @@ public class GPUTileProcessor {
"#define RBYRDIST_LEN " + RBYRDIST_LEN+"\n"+
"#define RBYRDIST_STEP " + RBYRDIST_STEP+"\n"+
"#define TILES_PER_BLOCK_GEOM " + TILES_PER_BLOCK_GEOM+"\n";
}
public GPUTileProcessor(
......@@ -338,6 +344,8 @@ public class GPUTileProcessor {
GPU_CONVERT_DIRECT_NAME,
GPU_IMCLT_ALL_NAME,
GPU_CORRELATE2D_NAME,
GPU_CORR2D_COMBINE_NAME,
GPU_CORR2D_NORMALIZE_NAME,
GPU_TEXTURES_NAME,
GPU_RBGA_NAME,
GPU_ROT_DERIV,
......@@ -351,16 +359,20 @@ public class GPUTileProcessor {
GPU_CONVERT_DIRECT_kernel = functions[0];
GPU_IMCLT_ALL_kernel = functions[1];
GPU_CORRELATE2D_kernel = functions[2];
GPU_TEXTURES_kernel= functions[3];
GPU_RBGA_kernel= functions[4];
GPU_ROT_DERIV_kernel = functions[5];
GPU_SET_TILES_OFFSETS_kernel = functions[6];
GPU_CALC_REVERSE_DISTORTION_kernel = functions[7];
GPU_CORR2D_COMBINE_kernel = functions[3];
GPU_CORR2D_NORMALIZE_kernel = functions[4];
GPU_TEXTURES_kernel= functions[5];
GPU_RBGA_kernel= functions[6];
GPU_ROT_DERIV_kernel = functions[7];
GPU_SET_TILES_OFFSETS_kernel = functions[8];
GPU_CALC_REVERSE_DISTORTION_kernel = functions[9];
System.out.println("GPU kernel functions initialized");
System.out.println(GPU_CONVERT_DIRECT_kernel.toString());
System.out.println(GPU_IMCLT_ALL_kernel.toString());
System.out.println(GPU_CORRELATE2D_kernel.toString());
System.out.println(GPU_CORR2D_COMBINE_kernel.toString());
System.out.println(GPU_CORR2D_NORMALIZE_kernel.toString());
System.out.println(GPU_TEXTURES_kernel.toString());
System.out.println(GPU_RBGA_kernel.toString());
System.out.println(GPU_ROT_DERIV_kernel.toString());
......@@ -372,7 +384,7 @@ public class GPUTileProcessor {
public static String [] getCorrTitles() {
return new String []{"hor-top","hor-bottom","vert-left","vert-right","diag-main","diag-other"};
return new String []{"hor-top","hor-bottom","vert-left","vert-right","diag-main","diag-other","quad","cross"};
}
public static double [][] getCorr2DView(
int tilesX,
......@@ -383,28 +395,48 @@ public class GPUTileProcessor {
if ((corr2d == null) || (corr2d.length == 0)) {
return new double [NUM_PAIRS][0];
}
int num_pairs = -1; // corr2d.length;
for (int n = 0; n < indices.length; n++) {
int np = indices[n] & CORR_PAIRS_MASK; // ((1 << CORR_NTILE_SHIFT) - 1); // np should
if (np > num_pairs) num_pairs = np;
}
num_pairs++;
if (num_pairs < 1) {
return new double [NUM_PAIRS][0];
}
boolean [] bpairs = new boolean[num_pairs];
for (int n = 0; n < indices.length; n++) {
bpairs[indices[n] & CORR_PAIRS_MASK] = true;
}
int first_pair = -1;
for (int i = 0; (i < bpairs.length) && (first_pair < 0); i++) {
if (bpairs[i]) first_pair = i;
}
int corr_size = (int)(Math.round(Math.sqrt(corr2d[0].length)));// make smaller later?
int width = tilesX * (corr_size + 1) + 1;
int height = tilesY * (corr_size + 1) + 1;
double [][] data = new double [NUM_PAIRS][];
data[0] = new double[height*width];
double [][] data = new double [num_pairs][];
data[first_pair] = new double[height*width];
for (int ty = 0; ty < tilesY; ty++) {
for (int tx = 0; tx < tilesX; tx++) {
for (int i = 0; i< corr_size; i++) {
for (int j = 0; j < corr_size; j++) {
data[0][(ty * (corr_size + 1) + i + 1) * width + (tx * (corr_size + 1) + j + 1)] = Double.NaN;
data[first_pair][(ty * (corr_size + 1) + i + 1) * width + (tx * (corr_size + 1) + j + 1)] = Double.NaN;
}
}
}
}
for (int np = first_pair+1; np < num_pairs; np++) {
if (bpairs[np]) {
data[np] = data[first_pair].clone();
}
for (int np = 1; np < NUM_PAIRS; np++) {
data[np] = data[0].clone();
}
for (int n = 0; n < indices.length; n++) {
int nt = indices[n] >> CORR_NTILE_SHIFT;
int np = indices[n] & CORR_PAIRS_MASK; // ((1 << CORR_NTILE_SHIFT) - 1); // np should
assert np < NUM_PAIRS : "invalid correllation pair";
assert np < num_pairs : "invalid correllation pair";
int tx = nt % tilesX;
int ty = nt / tilesX;
for (int i = 0; i< corr_size; i++) {
......@@ -534,10 +566,15 @@ public class GPUTileProcessor {
private CUdeviceptr gpu_bayer;
private CUdeviceptr gpu_tasks;
private CUdeviceptr gpu_corrs;
private CUdeviceptr gpu_corrs_td;
private CUdeviceptr gpu_corrs_combo;
private CUdeviceptr gpu_corrs_combo_td;
private CUdeviceptr gpu_textures;
private CUdeviceptr gpu_clt;
private CUdeviceptr gpu_4_images;
private CUdeviceptr gpu_corr_indices;
private CUdeviceptr gpu_corr_combo_indices;
private CUdeviceptr gpu_num_corr_tiles;
private CUdeviceptr gpu_texture_indices_ovlp;
private CUdeviceptr gpu_num_texture_ovlp;
......@@ -556,12 +593,18 @@ public class GPUTileProcessor {
private CUdeviceptr gpu_num_active_tiles;
private int mclt_stride;
private int corr_stride;
private int corr_stride_td;
private int corr_stride_combo;
private int corr_stride_combo_td;
private int imclt_stride;
private int texture_stride;
private int texture_stride_rgba;
private int num_task_tiles;
private int num_corr_tiles;
private int num_texture_tiles;
private int num_pairs = 6; // number of correlation pairs per tile (should match tsaks)
private int num_corr_combo_tiles;
private boolean geometry_correction_set = false;
private boolean geometry_correction_vector_set = false;
public GpuQuad(
......@@ -598,10 +641,17 @@ public class GPUTileProcessor {
gpu_bayer = new CUdeviceptr();
gpu_tasks = new CUdeviceptr(); // allocate tilesX * tilesY * TPTASK_SIZE * Sizeof.FLOAT
gpu_corrs = new CUdeviceptr(); // allocate tilesX * tilesY * NUM_PAIRS * CORR_SIZE * Sizeof.FLOAT
gpu_corrs_td = new CUdeviceptr(); // allocate tilesX * tilesY * NUM_PAIRS * 4 * DTT_SIZE * DTT_SIZE * Sizeof.FLOAT
gpu_corrs_combo = new CUdeviceptr(); // allocate tilesX * tilesY * CORR_SIZE * Sizeof.FLOAT
gpu_corrs_combo_td = new CUdeviceptr(); // allocate tilesX * tilesY * 4 * DTT_SIZE * DTT_SIZE * Sizeof.FLOAT
gpu_textures = new CUdeviceptr(); // allocate tilesX * tilesY * ? * 256 * Sizeof.FLOAT
gpu_clt = new CUdeviceptr();
gpu_4_images = new CUdeviceptr();
gpu_corr_indices = new CUdeviceptr(); // allocate tilesX * tilesY * 6 * Sizeof.FLOAT
// May add separate gpu_corr_indices_td here
gpu_corr_combo_indices = new CUdeviceptr(); // allocate tilesX * tilesY * 1 * Sizeof.FLOAT
gpu_num_corr_tiles = new CUdeviceptr(); // allocate tilesX * tilesY * 6 * Sizeof.FLOAT
gpu_texture_indices_ovlp =new CUdeviceptr(); // allocate tilesX * tilesY * 6 * Sizeof.FLOAT
gpu_num_texture_ovlp = new CUdeviceptr(); // 8 ints
......@@ -695,6 +745,8 @@ public class GPUTileProcessor {
//=========== Seems that in many places Sizeof.POINTER (==8) is used instead of Sizeof.FLOAT !!! ============
// Set corrs array
cuMemAlloc(gpu_corr_indices, tilesX * tilesY * NUM_PAIRS * Sizeof.FLOAT);
cuMemAlloc(gpu_corr_combo_indices, tilesX * tilesY * Sizeof.FLOAT);
cuMemAlloc(gpu_num_corr_tiles, 1 * Sizeof.FLOAT);
//#define TILESYA ((TILESY +3) & (~3))
......@@ -716,6 +768,7 @@ public class GPUTileProcessor {
cuMemAlloc(gpu_active_tiles, tilesX * tilesY * Sizeof.FLOAT);
cuMemAlloc(gpu_num_active_tiles, 1 * Sizeof.FLOAT);
// allocate space for pixel-domain correlations (6 per tile)
cuMemAllocPitch (
gpu_corrs, // CUdeviceptr dptr,
device_stride, // long[] pPitch,
......@@ -723,6 +776,34 @@ public class GPUTileProcessor {
NUM_PAIRS * tilesX * tilesY, // long Height,
Sizeof.FLOAT); // int ElementSizeBytes)
corr_stride = (int)(device_stride[0] / Sizeof.FLOAT);
// allocate space for transform-domain correlations (6 per tile)
cuMemAllocPitch (
gpu_corrs_td, // CUdeviceptr dptr,
device_stride, // long[] pPitch,
4 * DTT_SIZE * DTT_SIZE * Sizeof.FLOAT,// long WidthInBytes,
NUM_PAIRS * tilesX * tilesY, // long Height,
Sizeof.FLOAT); // int ElementSizeBytes)
corr_stride_td = (int)(device_stride[0] / Sizeof.FLOAT);
// allocate space for pixel-domain combined correlations (1 per tile)
cuMemAllocPitch (
gpu_corrs_combo, // CUdeviceptr dptr,
device_stride, // long[] pPitch,
CORR_SIZE * Sizeof.FLOAT, // long WidthInBytes,
tilesX * tilesY, // long Height,
Sizeof.FLOAT); // int ElementSizeBytes)
corr_stride_combo = (int)(device_stride[0] / Sizeof.FLOAT);
// allocate space for transform-domain combined correlations (1 per tile)
cuMemAllocPitch (
gpu_corrs_combo_td, // CUdeviceptr dptr,
device_stride, // long[] pPitch,
4 * DTT_SIZE * DTT_SIZE * Sizeof.FLOAT,// long WidthInBytes,
tilesX * tilesY, // long Height,
Sizeof.FLOAT); // int ElementSizeBytes)
corr_stride_combo_td = (int)(device_stride[0] / Sizeof.FLOAT);
int max_texture_size = (num_colors + 1 + (num_cams + num_colors + 1)) * (2 * DTT_SIZE)* (2 * DTT_SIZE);
cuMemAllocPitch (
gpu_textures, // CUdeviceptr dptr,
......@@ -1556,6 +1637,134 @@ public class GPUTileProcessor {
cuCtxSynchronize();
}
/**
* Generate 2D correlations from the CLT representation in transform domain, no normalization
* @param scales R,G,B weights
*/
public void execCorr2D_TD(
double [] scales) {
if (GPU_CORRELATE2D_kernel == null)
{
IJ.showMessage("Error", "No GPU kernel: GPU_CORRELATE2D_kernel");
return;
}
int tilesX = img_width / DTT_SIZE;
int num_colors = scales.length;
if (num_colors > 3) num_colors = 3;
float fscale0 = (float) scales[0];
float fscale1 = (num_colors >1)?((float) scales[1]):0.0f;
float fscale2 = (num_colors >2)?((float) scales[2]):0.0f;
int [] GridFullWarps = {1, 1, 1};
int [] ThreadsFullWarps = {1, 1, 1};
Pointer kernelParameters = Pointer.to(
Pointer.to(gpu_clt), // float ** gpu_clt,
Pointer.to(new int[] { num_colors }), // int colors, // number of colors (3/1)
Pointer.to(new float[] {fscale0 }), // float scale0, // scale for R
Pointer.to(new float[] {fscale1 }), // float scale1, // scale for B
Pointer.to(new float[] {fscale2 }), // float scale2, // scale for G
Pointer.to(new float[] {(float) 0.0 }), // float fat_zero, // here - absolute
Pointer.to(gpu_tasks), // struct tp_task * gpu_tasks,
Pointer.to(new int[] { num_task_tiles }), // int num_tiles // number of tiles in task
Pointer.to(new int[] { tilesX }), // int tilesx, // number of tile rows
Pointer.to(gpu_corr_indices), // int * gpu_corr_indices, // packed tile+pair
Pointer.to(gpu_num_corr_tiles), // int * pnum_corr_tiles, // pointer to a number of tiles to process
Pointer.to(new int[] { corr_stride_td }), // const size_t corr_stride, // in floats
Pointer.to(new int[] { 0 }), // generate TD // int corr_radius, // radius of the output correlation (7 for 15x15)
Pointer.to(gpu_corrs_td) // float * gpu_corrs); // correlation output data
);
cuCtxSynchronize();
// Call the kernel function
cuLaunchKernel(GPU_CORRELATE2D_kernel,
GridFullWarps[0], GridFullWarps[1], GridFullWarps[2], // Grid dimension
ThreadsFullWarps[0], ThreadsFullWarps[1],ThreadsFullWarps[2],// Block dimension
0, null, // Shared memory size and stream (shared - only dynamic, static is in code)
kernelParameters, null); // Kernel- and extra parameters
cuCtxSynchronize();
}
/**
* Combine intra-scene correlations in transform domain (possible to accumulate more)
* @param init_corr - true: init output to 0 before accumulating, false: add to current value
* @param num_pairs_in - typically ==6 - number of pairs per tile (tile task should have same number per each tile).
* This number should match correlations in tasks
* @param pairs_mask - selected pairs (0x3 - horizontal, 0xc - vertical, 0xf - quad, 0x30 - cross)
*/
public void execCorr2D_combine(
boolean init_corr, // initialize output tiles (false - add to current)
int num_pairs_in, // typically 6 - number of pairs per tile (tile task should have same number per each tile
int pairs_mask // selected pairs (0x3 - horizontal, 0xc - vertical, 0xf - quad, 0x30 - cross)
) {
if (GPU_CORR2D_COMBINE_kernel == null)
{
IJ.showMessage("Error", "No GPU kernel: GPU_CORR2D_COMBINE_kernel");
return;
}
num_pairs = num_pairs_in;
float [] fnum_corrs = new float[1];
cuMemcpyDtoH(Pointer.to(fnum_corrs), gpu_num_corr_tiles, 1 * Sizeof.FLOAT);
num_corr_combo_tiles = Float.floatToIntBits(fnum_corrs[0])/num_pairs; // number of correlation tiles calculated
int [] GridFullWarps = {1, 1, 1};
int [] ThreadsFullWarps = {1, 1, 1};
Pointer kernelParameters = Pointer.to(
Pointer.to(new int[] { num_corr_combo_tiles }), // num_task_tiles }), // int num_tiles // number of tiles in task
Pointer.to(new int[] { num_pairs }), // int num_pairs, // num pairs per tile (should be the same)
Pointer.to(new int[] { init_corr ? 1 : 0 }), // int init_output, // 1- reset output tiles to zero before accumulating
Pointer.to(new int[] { pairs_mask }), // int pairs_mask, // selected pairs
Pointer.to(gpu_corr_indices), // int * gpu_corr_indices, // packed tile+pair
Pointer.to(gpu_corr_combo_indices), // int * gpu_combo_indices, // output if not null: packed tile+pairs_mask
Pointer.to(new int[] { corr_stride_td }), // const size_t corr_stride, // (in floats) stride for the input TD correlations
Pointer.to(gpu_corrs_td), // float * gpu_corrs, // input correlation tiles
Pointer.to(new int[] { corr_stride_combo_td }),// const size_t corr_stride_combo, // (in floats) stride for the output TD
Pointer.to(gpu_corrs_combo_td)); // float * gpu_corrs_combo); // combined correlation output (one per tile)
cuCtxSynchronize();
// Call the kernel function
cuLaunchKernel(GPU_CORR2D_COMBINE_kernel,
GridFullWarps[0], GridFullWarps[1], GridFullWarps[2], // Grid dimension
ThreadsFullWarps[0], ThreadsFullWarps[1],ThreadsFullWarps[2],// Block dimension
0, null, // Shared memory size and stream (shared - only dynamic, static is in code)
kernelParameters, null); // Kernel- and extra parameters
cuCtxSynchronize();
}
/**
* Normalize 2D correlations, transform and unfold
* @param fat_zero - absolute fat zero - add to correlations before normalization
* @param corr_radius - correlation result size (maximal 7 for 15x15)
*/
public void execCorr2D_normalize(
double fat_zero,
int corr_radius) {
if (GPU_CORR2D_NORMALIZE_kernel == null)
{
IJ.showMessage("Error", "No GPU kernel: GPU_CORR2D_NORMALIZE_kernel");
return;
}
// float [] fnum_corrs = new float[1];
// cuMemcpyDtoH(Pointer.to(fnum_corrs), gpu_num_corr_tiles, 1 * Sizeof.FLOAT);
// int num_tiles = Float.floatToIntBits(fnum_corrs[0])/num_pairs; // number of correlation tiles calculated
int [] GridFullWarps = {1, 1, 1};
int [] ThreadsFullWarps = {1, 1, 1};
Pointer kernelParameters = Pointer.to(
Pointer.to(new int[] { num_corr_combo_tiles }), // num_task_tiles }), // int num_corr_tiles, // number of correlation tiles to process
Pointer.to(new int[] { corr_stride_combo_td }),// const size_t corr_stride_td, // in floats
Pointer.to(gpu_corrs_combo_td), // float * gpu_corrs_combo); // combined correlation output (one per tile)
Pointer.to(new int[] { corr_stride_combo }), // const size_t corr_stride, // in floats
Pointer.to(gpu_corrs_combo), // float * gpu_corrs, // correlation output data (pixel domain)
Pointer.to(new float[] {(float) fat_zero }), // float fat_zero, // here - absolute
Pointer.to(new int[] { corr_radius })); // int corr_radius, // radius of the output correlation (7 for 15x15)
cuCtxSynchronize();
// Call the kernel function
cuLaunchKernel(GPU_CORR2D_NORMALIZE_kernel,
GridFullWarps[0], GridFullWarps[1], GridFullWarps[2], // Grid dimension
ThreadsFullWarps[0], ThreadsFullWarps[1],ThreadsFullWarps[2],// Block dimension
0, null, // Shared memory size and stream (shared - only dynamic, static is in code)
kernelParameters, null); // Kernel- and extra parameters
cuCtxSynchronize();
}
/**
* Generate combined (overlapping) texture
* @param color_weights - [3] (RGB) or [1] (mono) color weights for matching
......@@ -1734,6 +1943,20 @@ public class GPUTileProcessor {
}
public int [] getCorrComboIndices() {
// float [] fnum_corrs = new float[1];
// cuMemcpyDtoH(Pointer.to(fnum_corrs), gpu_num_corr_tiles, 1 * Sizeof.FLOAT);
// int num_corrs = Float.floatToIntBits(fnum_corrs[0]);
float [] fcorr_combo_indices = new float [num_corr_combo_tiles];
cuMemcpyDtoH(Pointer.to(fcorr_combo_indices), gpu_corr_combo_indices, num_corr_combo_tiles * Sizeof.FLOAT);
int [] corr_combo_indices = new int [num_corr_combo_tiles];
for (int i = 0; i < num_corr_combo_tiles; i++) {
corr_combo_indices[i] = Float.floatToIntBits(fcorr_combo_indices[i]);
}
return corr_combo_indices;
}
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];
......@@ -1758,6 +1981,30 @@ public class GPUTileProcessor {
return corrs;
}
public float [][] getCorr2DCombo(int corr_rad){
int corr_size = (2 * corr_rad + 1) * (2 * corr_rad + 1);
float [] cpu_corrs = new float [ num_corr_combo_tiles * corr_size];
CUDA_MEMCPY2D copyD2H = new CUDA_MEMCPY2D();
copyD2H.srcMemoryType = CUmemorytype.CU_MEMORYTYPE_DEVICE;
copyD2H.srcDevice = gpu_corrs_combo;
copyD2H.srcPitch = corr_stride_combo * Sizeof.FLOAT;
copyD2H.dstMemoryType = CUmemorytype.CU_MEMORYTYPE_HOST;
copyD2H.dstHost = Pointer.to(cpu_corrs);
copyD2H.dstPitch = corr_size * Sizeof.FLOAT;
copyD2H.WidthInBytes = corr_size * Sizeof.FLOAT;
copyD2H.Height = num_corr_combo_tiles;
cuMemcpy2D(copyD2H); // run copy
float [][] corrs = new float [num_corr_combo_tiles][ corr_size];
for (int ncorr = 0; ncorr < num_corr_combo_tiles; ncorr++) {
System.arraycopy(cpu_corrs, ncorr*corr_size, corrs[ncorr], 0, corr_size);
}
return corrs;
}
//
/**
......
src/main/java/com/elphel/imagej/tileprocessor/QuadCLT.java
View file @ fa5947b6
......@@ -657,6 +657,30 @@ public class QuadCLT extends QuadCLTCPU {
clt_parameters.gpu_corr_rad); // int corr_radius
long endCorr2d = System.nanoTime();
// SHould be done before execCorr2D_TD as corr_indices are shared to save memory
int [] corr_indices = quadCLT_main.getGPU().getCorrIndices();
// the following is not yet shared
float [][] corr2D = quadCLT_main.getGPU().getCorr2D(
clt_parameters.gpu_corr_rad); // int corr_rad);
// calculate correlations, keep TD
quadCLT_main.getGPU().execCorr2D_TD(
scales);// double [] scales,
quadCLT_main.getGPU().execCorr2D_combine( // calculate cross pairs
true, // boolean init_corr, // initialize output tiles (false - add to current)
6, // int num_pairs_in, // typically 6 - number of pairs per tile (tile task should have same number per each tile
0x0f); // int pairs_mask // selected pairs (0x3 - horizontal, 0xc - vertical, 0xf - quad, 0x30 - cross)
quadCLT_main.getGPU().execCorr2D_normalize(
fat_zero, // double fat_zero);
clt_parameters.gpu_corr_rad); // int corr_radius
// run textures
long startTextures = System.nanoTime(); // System.nanoTime();
boolean calc_textures = clt_parameters.gpu_show_jtextures; // true;
......@@ -770,16 +794,52 @@ public class QuadCLT extends QuadCLTCPU {
//Show 2D correlations
int [] wh = new int[2];
if (clt_parameters.show_corr) {
int [] corr_indices = quadCLT_main.getGPU().getCorrIndices();
float [][] corr2D = quadCLT_main.getGPU().getCorr2D(
clt_parameters.gpu_corr_rad); // int corr_rad);
// convert to 6-layer image using tasks
double [][] dbg_corr = GPUTileProcessor.getCorr2DView(
int [] corr_quad_indices = quadCLT_main.getGPU().getCorrComboIndices(); // get quad
float [][] corr2D_quad = quadCLT_main.getGPU().getCorr2DCombo(clt_parameters.gpu_corr_rad);
// calculate and get cross here!
quadCLT_main.getGPU().execCorr2D_combine( // calculate cross pairs
true, // boolean init_corr, // initialize output tiles (false - add to current)
6, // int num_pairs_in, // typically 6 - number of pairs per tile (tile task should have same number per each tile
0x30); // int pairs_mask // selected pairs (0x3 - horizontal, 0xc - vertical, 0xf - quad, 0x30 - cross)
quadCLT_main.getGPU().execCorr2D_normalize(
fat_zero, // double fat_zero);
clt_parameters.gpu_corr_rad); // int corr_radius
int [] corr_cross_indices = quadCLT_main.getGPU().getCorrComboIndices(); // get quad
float [][] corr2D_cross = quadCLT_main.getGPU().getCorr2DCombo(clt_parameters.gpu_corr_rad);
double [][] dbg_corr_pairs = GPUTileProcessor.getCorr2DView(
tilesX,
tilesY,
corr_indices,
corr2D,
wh);
double [][] dbg_corr_quad = GPUTileProcessor.getCorr2DView(
tilesX,
tilesY,
corr_quad_indices,
corr2D_quad,
wh);
double [][] dbg_corr_cross = GPUTileProcessor.getCorr2DView(
tilesX,
tilesY,
corr_cross_indices,
corr2D_cross,
wh);
double [][] dbg_corr = {
dbg_corr_pairs[0],
dbg_corr_pairs[1],
dbg_corr_pairs[2],
dbg_corr_pairs[3],
dbg_corr_pairs[4],
dbg_corr_pairs[5],
dbg_corr_quad[15],
dbg_corr_cross[48]
};
(new ShowDoubleFloatArrays()).showArrays(
dbg_corr,
wh[0],
......@@ -788,6 +848,7 @@ public class QuadCLT extends QuadCLTCPU {
name+"-CORR2D-D"+clt_parameters.disparity,
GPUTileProcessor.getCorrTitles());
}
// convert to overlapping and show
if (clt_parameters.gen_chn_img) { // save and show 4-slice image
// combine to a sliced color image
......
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