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added support of multichannel images into gpu::matchTemplate for CCOEFF method

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This commit is contained in:
Alexey Spizhevoy 2010-12-15 16:04:10 +00:00
parent f56d9c340f
commit 3db5b687f6
1 changed files with 118 additions and 1 deletions
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119
modules/gpu/src/cuda/match_template.cu
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@ -49,7 +49,6 @@ using namespace cv::gpu::device;
namespace cv { namespace gpu { namespace imgproc {
__device__ float sum(float v) { return v; }
__device__ float sum(float2 v) { return v.x + v.y; }
__device__ float sum(float3 v) { return v.x + v.y + v.z; }
@ -447,6 +446,124 @@ void matchTemplatePrepared_CCOFF_8UC2(
}
__global__ void matchTemplatePreparedKernel_CCOFF_8UC3(
int w, int h,
float templ_sum_scale_r,
float templ_sum_scale_g,
float templ_sum_scale_b,
const PtrStep_<unsigned int> image_sum_r,
const PtrStep_<unsigned int> image_sum_g,
const PtrStep_<unsigned int> image_sum_b,
DevMem2Df result)
{
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x < result.cols && y < result.rows)
{
float image_sum_r_ = (float)(
(image_sum_r.ptr(y + h)[x + w] - image_sum_r.ptr(y)[x + w]) -
(image_sum_r.ptr(y + h)[x] - image_sum_r.ptr(y)[x]));
float image_sum_g_ = (float)(
(image_sum_g.ptr(y + h)[x + w] - image_sum_g.ptr(y)[x + w]) -
(image_sum_g.ptr(y + h)[x] - image_sum_g.ptr(y)[x]));
float image_sum_b_ = (float)(
(image_sum_b.ptr(y + h)[x + w] - image_sum_b.ptr(y)[x + w]) -
(image_sum_b.ptr(y + h)[x] - image_sum_b.ptr(y)[x]));
float ccorr = result.ptr(y)[x];
result.ptr(y)[x] = ccorr - image_sum_r_ * templ_sum_scale_r
- image_sum_g_ * templ_sum_scale_g
- image_sum_b_ * templ_sum_scale_b;
}
}
void matchTemplatePrepared_CCOFF_8UC3(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
const DevMem2D_<unsigned int> image_sum_b,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
DevMem2Df result)
{
dim3 threads(32, 8);
dim3 grid(divUp(result.cols, threads.x), divUp(result.rows, threads.y));
matchTemplatePreparedKernel_CCOFF_8UC3<<<grid, threads>>>(
w, h,
(float)templ_sum_r / (w * h),
(float)templ_sum_g / (w * h),
(float)templ_sum_b / (w * h),
image_sum_r, image_sum_g, image_sum_b, result);
cudaSafeCall(cudaThreadSynchronize());
}
__global__ void matchTemplatePreparedKernel_CCOFF_8UC4(
int w, int h,
float templ_sum_scale_r,
float templ_sum_scale_g,
float templ_sum_scale_b,
float templ_sum_scale_a,
const PtrStep_<unsigned int> image_sum_r,
const PtrStep_<unsigned int> image_sum_g,
const PtrStep_<unsigned int> image_sum_b,
const PtrStep_<unsigned int> image_sum_a,
DevMem2Df result)
{
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x < result.cols && y < result.rows)
{
float image_sum_r_ = (float)(
(image_sum_r.ptr(y + h)[x + w] - image_sum_r.ptr(y)[x + w]) -
(image_sum_r.ptr(y + h)[x] - image_sum_r.ptr(y)[x]));
float image_sum_g_ = (float)(
(image_sum_g.ptr(y + h)[x + w] - image_sum_g.ptr(y)[x + w]) -
(image_sum_g.ptr(y + h)[x] - image_sum_g.ptr(y)[x]));
float image_sum_b_ = (float)(
(image_sum_b.ptr(y + h)[x + w] - image_sum_b.ptr(y)[x + w]) -
(image_sum_b.ptr(y + h)[x] - image_sum_b.ptr(y)[x]));
float image_sum_a_ = (float)(
(image_sum_a.ptr(y + h)[x + w] - image_sum_a.ptr(y)[x + w]) -
(image_sum_a.ptr(y + h)[x] - image_sum_a.ptr(y)[x]));
float ccorr = result.ptr(y)[x];
result.ptr(y)[x] = ccorr - image_sum_r_ * templ_sum_scale_r
- image_sum_g_ * templ_sum_scale_g
- image_sum_b_ * templ_sum_scale_b
- image_sum_a_ * templ_sum_scale_a;
}
}
void matchTemplatePrepared_CCOFF_8UC4(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
const DevMem2D_<unsigned int> image_sum_b,
const DevMem2D_<unsigned int> image_sum_a,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
unsigned int templ_sum_a,
DevMem2Df result)
{
dim3 threads(32, 8);
dim3 grid(divUp(result.cols, threads.x), divUp(result.rows, threads.y));
matchTemplatePreparedKernel_CCOFF_8UC4<<<grid, threads>>>(
w, h,
(float)templ_sum_r / (w * h),
(float)templ_sum_g / (w * h),
(float)templ_sum_b / (w * h),
(float)templ_sum_a / (w * h),
image_sum_r, image_sum_g, image_sum_b, image_sum_a,
result);
cudaSafeCall(cudaThreadSynchronize());
}
__global__ void matchTemplatePreparedKernel_CCOFF_NORMED_8U(
int w, int h, float weight,
float templ_sum_scale, float templ_sqsum_scale,