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disparity_method.cu
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disparity_method.cu
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/**
This file is part of sgm. (https://github.com/dhernandez0/sgm).
Copyright (c) 2016 Daniel Hernandez Juarez.
sgm is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
sgm is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with sgm. If not, see <http://www.gnu.org/licenses/>.
**/
#include "disparity_method.h"
static cudaStream_t stream1, stream2, stream3;//, stream4, stream5, stream6, stream7, stream8;
static uint8_t *d_im0;
static uint8_t *d_im1;
static cost_t *d_transform0;
static cost_t *d_transform1;
static uint8_t *d_cost;
static uint8_t *d_disparity;
static uint8_t *d_disparity_filtered_uchar;
static uint8_t *h_disparity;
// not used
// static uint16_t *d_S;
static uint8_t *d_L0;
static uint8_t *d_L1;
static uint8_t *d_L2;
static uint8_t *d_L3;
static uint8_t *d_L4;
static uint8_t *d_L5;
static uint8_t *d_L6;
static uint8_t *d_L7;
static uint8_t p1, p2;
static bool first_alloc;
static uint32_t cols, rows, size, size_cube_l;
void init_disparity_method(const uint8_t _p1, const uint8_t _p2) {
// We are not using shared memory, use L1
//CUDA_CHECK_RETURN(cudaDeviceSetCacheConfig(cudaFuncCachePreferL1));
//CUDA_CHECK_RETURN(cudaDeviceSetCacheConfig(cudaFuncCachePreferShared));
// Create streams
CUDA_CHECK_RETURN(cudaStreamCreate(&stream1));
CUDA_CHECK_RETURN(cudaStreamCreate(&stream2));
CUDA_CHECK_RETURN(cudaStreamCreate(&stream3));
first_alloc = true;
p1 = _p1;
p2 = _p2;
rows = 0;
cols = 0;
}
Mat_<unsigned char, 1> compute_disparity_method(Mat_<unsigned char, 1> left, Mat_<unsigned char, 1> right, float *elapsed_time_ms, const char* directory, const char* fname) {
if(cols != left.cols || rows != left.rows) {
debug_log("WARNING: cols or rows are different");
if(!first_alloc) {
debug_log("Freeing memory");
free_memory();
}
first_alloc = false;
cols = left.cols;
rows = left.rows;
size = rows*cols;
size_cube_l = size*MAX_DISPARITY;
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_transform0, sizeof(cost_t)*size));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_transform1, sizeof(cost_t)*size));
// redefined
int size_cube = size*MAX_DISPARITY;
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_cost, sizeof(uint8_t)*size_cube));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_im0, sizeof(uint8_t)*size));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_im1, sizeof(uint8_t)*size));
// not used
//CUDA_CHECK_RETURN(cudaMalloc((void **)&d_S, sizeof(uint16_t)*size_cube_l));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L0, sizeof(uint8_t)*size_cube_l));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L1, sizeof(uint8_t)*size_cube_l));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L2, sizeof(uint8_t)*size_cube_l));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L3, sizeof(uint8_t)*size_cube_l));
#if PATH_AGGREGATION == 8
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L4, sizeof(uint8_t)*size_cube_l));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L5, sizeof(uint8_t)*size_cube_l));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L6, sizeof(uint8_t)*size_cube_l));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_L7, sizeof(uint8_t)*size_cube_l));
#endif
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_disparity, sizeof(uint8_t)*size));
CUDA_CHECK_RETURN(cudaMalloc((void **)&d_disparity_filtered_uchar, sizeof(uint8_t)*size));
h_disparity = new uint8_t[size];
}
debug_log("Copying images to the GPU");
CUDA_CHECK_RETURN(cudaMemcpyAsync(d_im0, left.ptr(), sizeof(uint8_t)*size, cudaMemcpyHostToDevice, stream1));
CUDA_CHECK_RETURN(cudaMemcpyAsync(d_im1, right.ptr(), sizeof(uint8_t)*size, cudaMemcpyHostToDevice, stream1));
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start, 0);
dim3 block_size;
block_size.x = 32;
block_size.y = 32;
dim3 grid_size;
grid_size.x = (cols+block_size.x-1) / block_size.x;
grid_size.y = (rows+block_size.y-1) / block_size.y;
debug_log("Calling CSCT");
CenterSymmetricCensusKernelSM2<<<grid_size, block_size, 0, stream1>>>(d_im0, d_im1, d_transform0, d_transform1, rows, cols);
cudaError_t err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
// Hamming distance
CUDA_CHECK_RETURN(cudaStreamSynchronize(stream1));
debug_log("Calling Hamming Distance");
HammingDistanceCostKernel<<<rows, MAX_DISPARITY, 0, stream1>>>(d_transform0, d_transform1, d_cost, rows, cols);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
// Cost Aggregation
// PIXELS_PER_BLOCK 64/32=2
const int PIXELS_PER_BLOCK = COSTAGG_BLOCKSIZE/WARP_SIZE;
const int PIXELS_PER_BLOCK_HORIZ = COSTAGG_BLOCKSIZE_HORIZ/WARP_SIZE;
debug_log("Calling Left to Right");
CostAggregationKernelLeftToRight<<<(rows+PIXELS_PER_BLOCK_HORIZ-1)/PIXELS_PER_BLOCK_HORIZ, COSTAGG_BLOCKSIZE_HORIZ, 0, stream2>>>(d_cost, d_L0, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
//CUDA_CHECK_RETURN(cudaDeviceSynchronize());
debug_log("Calling Right to Left");
CostAggregationKernelRightToLeft<<<(rows+PIXELS_PER_BLOCK_HORIZ-1)/PIXELS_PER_BLOCK_HORIZ, COSTAGG_BLOCKSIZE_HORIZ, 0, stream3>>>(d_cost, d_L1, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
debug_log("Calling Up to Down");
CostAggregationKernelUpToDown<<<(cols+PIXELS_PER_BLOCK-1)/PIXELS_PER_BLOCK, COSTAGG_BLOCKSIZE, 0, stream1>>>(d_cost, d_L2, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
CUDA_CHECK_RETURN(cudaDeviceSynchronize());
debug_log("Calling Down to Up");
CostAggregationKernelDownToUp<<<(cols+PIXELS_PER_BLOCK-1)/PIXELS_PER_BLOCK, COSTAGG_BLOCKSIZE, 0, stream1>>>(d_cost, d_L3, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
#if PATH_AGGREGATION == 8
CostAggregationKernelDiagonalDownUpLeftRight<<<(cols+PIXELS_PER_BLOCK-1)/PIXELS_PER_BLOCK, COSTAGG_BLOCKSIZE, 0, stream1>>>(d_cost, d_L4, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
CostAggregationKernelDiagonalUpDownLeftRight<<<(cols+PIXELS_PER_BLOCK-1)/PIXELS_PER_BLOCK, COSTAGG_BLOCKSIZE, 0, stream1>>>(d_cost, d_L5, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
CostAggregationKernelDiagonalDownUpRightLeft<<<(cols+PIXELS_PER_BLOCK-1)/PIXELS_PER_BLOCK, COSTAGG_BLOCKSIZE, 0, stream1>>>(d_cost, d_L6, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
CostAggregationKernelDiagonalUpDownRightLeft<<<(cols+PIXELS_PER_BLOCK-1)/PIXELS_PER_BLOCK, COSTAGG_BLOCKSIZE, 0, stream1>>>(d_cost, d_L7, p1, p2, rows, cols, d_transform0, d_transform1, d_disparity, d_L0, d_L1, d_L2, d_L3, d_L4, d_L5, d_L6);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
#endif
debug_log("Calling Median Filter");
MedianFilter3x3<<<(size+MAX_DISPARITY-1)/MAX_DISPARITY, MAX_DISPARITY, 0, stream1>>>(d_disparity, d_disparity_filtered_uchar, rows, cols);
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("Error: %s %d\n", cudaGetErrorString(err), err);
exit(-1);
}
cudaEventRecord(stop, 0);
CUDA_CHECK_RETURN(cudaDeviceSynchronize());
cudaEventElapsedTime(elapsed_time_ms, start, stop);
cudaEventDestroy(start);
cudaEventDestroy(stop);
debug_log("Copying final disparity to CPU");
CUDA_CHECK_RETURN(cudaMemcpy(h_disparity, d_disparity_filtered_uchar, sizeof(uint8_t)*size, cudaMemcpyDeviceToHost));
//CUDA_CHECK_RETURN(cudaMemcpy(h_disparity, d_disparity, sizeof(uint8_t)*size, cudaMemcpyDeviceToHost));
Mat_<unsigned char, 1> disparity(rows, cols, h_disparity);
return disparity;
}
static void free_memory() {
CUDA_CHECK_RETURN(cudaFree(d_im0));
CUDA_CHECK_RETURN(cudaFree(d_im1));
CUDA_CHECK_RETURN(cudaFree(d_transform0));
CUDA_CHECK_RETURN(cudaFree(d_transform1));
CUDA_CHECK_RETURN(cudaFree(d_L0));
CUDA_CHECK_RETURN(cudaFree(d_L1));
CUDA_CHECK_RETURN(cudaFree(d_L2));
CUDA_CHECK_RETURN(cudaFree(d_L3));
#if PATH_AGGREGATION == 8
CUDA_CHECK_RETURN(cudaFree(d_L4));
CUDA_CHECK_RETURN(cudaFree(d_L5));
CUDA_CHECK_RETURN(cudaFree(d_L6));
CUDA_CHECK_RETURN(cudaFree(d_L7));
#endif
CUDA_CHECK_RETURN(cudaFree(d_disparity));
CUDA_CHECK_RETURN(cudaFree(d_disparity_filtered_uchar));
CUDA_CHECK_RETURN(cudaFree(d_cost));
delete[] h_disparity;
}
void finish_disparity_method() {
if(!first_alloc) {
free_memory();
CUDA_CHECK_RETURN(cudaStreamDestroy(stream1));
CUDA_CHECK_RETURN(cudaStreamDestroy(stream2));
CUDA_CHECK_RETURN(cudaStreamDestroy(stream3));
}
}