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remove constant memory from init_data_cost

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pull/2983/head
Aaron Denney 11 years ago
parent 1ff270e41c
commit 52516085d9
1 changed files with 48 additions and 44 deletions
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  1. 92
      modules/cudastereo/src/cuda/stereocsbp.cu

92
modules/cudastereo/src/cuda/stereocsbp.cu
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@ -92,16 +92,17 @@ namespace cv { namespace cuda { namespace device
}
template <typename T>
__global__ void get_first_k_initial_global(uchar *ctemp, T* data_cost_selected_, T *selected_disp_pyr, int h, int w, int nr_plane, int ndisp)
__global__ void get_first_k_initial_global(uchar *ctemp, T* data_cost_selected_, T *selected_disp_pyr, int h, int w, int nr_plane, int ndisp,
size_t msg_step, size_t disp_step)
{
int x = blockIdx.x * blockDim.x + threadIdx.x;
int y = blockIdx.y * blockDim.y + threadIdx.y;
if (y < h && x < w)
{
T* selected_disparity = selected_disp_pyr + y * cmsg_step + x;
T* data_cost_selected = data_cost_selected_ + y * cmsg_step + x;
T* data_cost = (T*)ctemp + y * cmsg_step + x;
T* selected_disparity = selected_disp_pyr + y * msg_step + x;
T* data_cost_selected = data_cost_selected_ + y * msg_step + x;
T* data_cost = (T*)ctemp + y * msg_step + x;
for(int i = 0; i < nr_plane; i++)
{
@ -109,7 +110,7 @@ namespace cv { namespace cuda { namespace device
int id = 0;
for(int d = 0; d < ndisp; d++)
{
T cur = data_cost[d * cdisp_step1];
T cur = data_cost[d * disp_step];
if(cur < minimum)
{
minimum = cur;
@ -117,46 +118,47 @@ namespace cv { namespace cuda { namespace device
}
}
data_cost_selected[i * cdisp_step1] = minimum;
selected_disparity[i * cdisp_step1] = id;
data_cost [id * cdisp_step1] = numeric_limits<T>::max();
data_cost_selected[i * disp_step] = minimum;
selected_disparity[i * disp_step] = id;
data_cost [id * disp_step] = numeric_limits<T>::max();
}
}
}
template <typename T>
__global__ void get_first_k_initial_local(uchar *ctemp, T* data_cost_selected_, T* selected_disp_pyr, int h, int w, int nr_plane, int ndisp)
__global__ void get_first_k_initial_local(uchar *ctemp, T* data_cost_selected_, T* selected_disp_pyr, int h, int w, int nr_plane, int ndisp,
size_t msg_step, size_t disp_step)
{
int x = blockIdx.x * blockDim.x + threadIdx.x;
int y = blockIdx.y * blockDim.y + threadIdx.y;
if (y < h && x < w)
{
T* selected_disparity = selected_disp_pyr + y * cmsg_step + x;
T* data_cost_selected = data_cost_selected_ + y * cmsg_step + x;
T* data_cost = (T*)ctemp + y * cmsg_step + x;
T* selected_disparity = selected_disp_pyr + y * msg_step + x;
T* data_cost_selected = data_cost_selected_ + y * msg_step + x;
T* data_cost = (T*)ctemp + y * msg_step + x;
int nr_local_minimum = 0;
T prev = data_cost[0 * cdisp_step1];
T cur = data_cost[1 * cdisp_step1];
T next = data_cost[2 * cdisp_step1];
T prev = data_cost[0 * disp_step];
T cur = data_cost[1 * disp_step];
T next = data_cost[2 * disp_step];
for (int d = 1; d < ndisp - 1 && nr_local_minimum < nr_plane; d++)
{
if (cur < prev && cur < next)
{
data_cost_selected[nr_local_minimum * cdisp_step1] = cur;
selected_disparity[nr_local_minimum * cdisp_step1] = d;
data_cost_selected[nr_local_minimum * disp_step] = cur;
selected_disparity[nr_local_minimum * disp_step] = d;
data_cost[d * cdisp_step1] = numeric_limits<T>::max();
data_cost[d * disp_step] = numeric_limits<T>::max();
nr_local_minimum++;
}
prev = cur;
cur = next;
next = data_cost[(d + 1) * cdisp_step1];
next = data_cost[(d + 1) * disp_step];
}
for (int i = nr_local_minimum; i < nr_plane; i++)
@ -166,23 +168,25 @@ namespace cv { namespace cuda { namespace device
for (int d = 0; d < ndisp; d++)
{
cur = data_cost[d * cdisp_step1];
cur = data_cost[d * disp_step];
if (cur < minimum)
{
minimum = cur;
id = d;
}
}
data_cost_selected[i * cdisp_step1] = minimum;
selected_disparity[i * cdisp_step1] = id;
data_cost_selected[i * disp_step] = minimum;
selected_disparity[i * disp_step] = id;
data_cost[id * cdisp_step1] = numeric_limits<T>::max();
data_cost[id * disp_step] = numeric_limits<T>::max();
}
}
}
template <typename T, int channels>
__global__ void init_data_cost(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int h, int w, int level, int ndisp, float data_weight, float max_data_term, int min_disp)
__global__ void init_data_cost(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step,
int h, int w, int level, int ndisp, float data_weight, float max_data_term,
int min_disp, size_t msg_step, size_t disp_step)
{
int x = blockIdx.x * blockDim.x + threadIdx.x;
int y = blockIdx.y * blockDim.y + threadIdx.y;
@ -195,7 +199,7 @@ namespace cv { namespace cuda { namespace device
int x0 = x << level;
int xt = (x + 1) << level;
T* data_cost = (T*)ctemp + y * cmsg_step + x;
T* data_cost = (T*)ctemp + y * msg_step + x;
for(int d = 0; d < ndisp; ++d)
{
@ -216,13 +220,15 @@ namespace cv { namespace cuda { namespace device
}
}
}
data_cost[cdisp_step1 * d] = saturate_cast<T>(val);
data_cost[disp_step * d] = saturate_cast<T>(val);
}
}
}
template <typename T, int winsz, int channels>
__global__ void init_data_cost_reduce(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int level, int rows, int cols, int h, int ndisp, float data_weight, float max_data_term, int min_disp)
__global__ void init_data_cost_reduce(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step,
int level, int rows, int cols, int h, int ndisp, float data_weight, float max_data_term,
int min_disp, size_t msg_step, size_t disp_step)
{
int x_out = blockIdx.x;
int y_out = blockIdx.y % h;
@ -261,16 +267,16 @@ namespace cv { namespace cuda { namespace device
reduce<winsz>(smem + winsz * threadIdx.z, val, tid, plus<float>());
T* data_cost = (T*)ctemp + y_out * cmsg_step + x_out;
T* data_cost = (T*)ctemp + y_out * msg_step + x_out;
if (tid == 0)
data_cost[cdisp_step1 * d] = saturate_cast<T>(val);
data_cost[disp_step * d] = saturate_cast<T>(val);
}
}
template <typename T>
void init_data_cost_caller_(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int /*rows*/, int /*cols*/, int h, int w, int level, int ndisp, int channels, float data_weight, float max_data_term, int min_disp, cudaStream_t stream)
void init_data_cost_caller_(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int /*rows*/, int /*cols*/, int h, int w, int level, int ndisp, int channels, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@ -280,15 +286,15 @@ namespace cv { namespace cuda { namespace device
switch (channels)
{
case 1: init_data_cost<T, 1><<<grid, threads, 0, stream>>>(cleft, cright, ctemp, cimg_step, h, w, level, ndisp, data_weight, max_data_term, min_disp); break;
case 3: init_data_cost<T, 3><<<grid, threads, 0, stream>>>(cleft, cright, ctemp, cimg_step, h, w, level, ndisp, data_weight, max_data_term, min_disp); break;
case 4: init_data_cost<T, 4><<<grid, threads, 0, stream>>>(cleft, cright, ctemp, cimg_step, h, w, level, ndisp, data_weight, max_data_term, min_disp); break;
case 1: init_data_cost<T, 1><<<grid, threads, 0, stream>>>(cleft, cright, ctemp, cimg_step, h, w, level, ndisp, data_weight, max_data_term, min_disp, msg_step, disp_step); break;
case 3: init_data_cost<T, 3><<<grid, threads, 0, stream>>>(cleft, cright, ctemp, cimg_step, h, w, level, ndisp, data_weight, max_data_term, min_disp, msg_step, disp_step); break;
case 4: init_data_cost<T, 4><<<grid, threads, 0, stream>>>(cleft, cright, ctemp, cimg_step, h, w, level, ndisp, data_weight, max_data_term, min_disp, msg_step, disp_step); break;
default: CV_Error(cv::Error::BadNumChannels, "Unsupported channels count");
}
}
template <typename T, int winsz>
void init_data_cost_reduce_caller_(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int rows, int cols, int h, int w, int level, int ndisp, int channels, float data_weight, float max_data_term, int min_disp, cudaStream_t stream)
void init_data_cost_reduce_caller_(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int rows, int cols, int h, int w, int level, int ndisp, int channels, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step, cudaStream_t stream)
{
const int threadsNum = 256;
const size_t smem_size = threadsNum * sizeof(float);
@ -299,9 +305,9 @@ namespace cv { namespace cuda { namespace device
switch (channels)
{
case 1: init_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>(cleft, cright, ctemp, cimg_step, level, rows, cols, h, ndisp, data_weight, max_data_term, min_disp); break;
case 3: init_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>(cleft, cright, ctemp, cimg_step, level, rows, cols, h, ndisp, data_weight, max_data_term, min_disp); break;
case 4: init_data_cost_reduce<T, winsz, 4><<<grid, threads, smem_size, stream>>>(cleft, cright, ctemp, cimg_step, level, rows, cols, h, ndisp, data_weight, max_data_term, min_disp); break;
case 1: init_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>(cleft, cright, ctemp, cimg_step, level, rows, cols, h, ndisp, data_weight, max_data_term, min_disp, msg_step, disp_step); break;
case 3: init_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>(cleft, cright, ctemp, cimg_step, level, rows, cols, h, ndisp, data_weight, max_data_term, min_disp, msg_step, disp_step); break;
case 4: init_data_cost_reduce<T, winsz, 4><<<grid, threads, smem_size, stream>>>(cleft, cright, ctemp, cimg_step, level, rows, cols, h, ndisp, data_weight, max_data_term, min_disp, msg_step, disp_step); break;
default: CV_Error(cv::Error::BadNumChannels, "Unsupported channels count");
}
}
@ -311,7 +317,7 @@ namespace cv { namespace cuda { namespace device
int h, int w, int level, int nr_plane, int ndisp, int channels, float data_weight, float max_data_term, int min_disp, bool use_local_init_data_cost, cudaStream_t stream)
{
typedef void (*InitDataCostCaller)(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int cols, int rows, int w, int h, int level, int ndisp, int channels, float data_weight, float max_data_term, int min_disp, cudaStream_t stream);
typedef void (*InitDataCostCaller)(const uchar *cleft, const uchar *cright, uchar *ctemp, size_t cimg_step, int cols, int rows, int w, int h, int level, int ndisp, int channels, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step, cudaStream_t stream);
static const InitDataCostCaller init_data_cost_callers[] =
{
@ -321,10 +327,8 @@ namespace cv { namespace cuda { namespace device
};
size_t disp_step = msg_step * h;
cudaSafeCall( cudaMemcpyToSymbol(cdisp_step1, &disp_step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(cmsg_step, &msg_step, sizeof(size_t)) );
init_data_cost_callers[level](cleft, cright, ctemp, cimg_step, rows, cols, h, w, level, ndisp, channels, data_weight, max_data_term, min_disp, stream);
init_data_cost_callers[level](cleft, cright, ctemp, cimg_step, rows, cols, h, w, level, ndisp, channels, data_weight, max_data_term, min_disp, msg_step, disp_step, stream);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
@ -337,9 +341,9 @@ namespace cv { namespace cuda { namespace device
grid.y = divUp(h, threads.y);
if (use_local_init_data_cost == true)
get_first_k_initial_local<<<grid, threads, 0, stream>>> (ctemp, data_cost_selected, disp_selected_pyr, h, w, nr_plane, ndisp);
get_first_k_initial_local<<<grid, threads, 0, stream>>> (ctemp, data_cost_selected, disp_selected_pyr, h, w, nr_plane, ndisp, msg_step, disp_step);
else
get_first_k_initial_global<<<grid, threads, 0, stream>>>(ctemp, data_cost_selected, disp_selected_pyr, h, w, nr_plane, ndisp);
get_first_k_initial_global<<<grid, threads, 0, stream>>>(ctemp, data_cost_selected, disp_selected_pyr, h, w, nr_plane, ndisp, msg_step, disp_step);
cudaSafeCall( cudaGetLastError() );
@ -542,7 +546,7 @@ namespace cv { namespace cuda { namespace device
int id = 0;
for(int j = 0; j < nr_plane2; j++)
{
T cur = data_cost_new[j * cdisp_step1];
T cur = data_cost_new[j * disp_step1];
if(cur < minimum)
{
minimum = cur;

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