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Gaurav Kukreja
cuda_lab
Commits
c0feb1cd
Commit
c0feb1cd
authored
Mar 27, 2014
by
Ravi
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qt camera code with primal dual integrated
parent
ee8872d5
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kernel.cu
miklos/project_integration/kernel.cu
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miklos/project_integration/kernel.cu
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c0feb1cd
#include "kernel.h"
#include <algorithm>
template<typename T>
__device__ __host__ T min(T a, T b)
{
return (a < b) ? a : b;
}
template<typename T>
__device__ __host__ T max(T a, T b)
{
return (a > b) ? a : b;
}
template<typename T>
__device__ __host__ T clamp(T m, T x, T M)
{
return max(m, min(x, M));
}
__global__ void calculate_F(float *U, float *F, int w, int h, float c1, float c2, float lambda)
{
int x = threadIdx.x + blockDim.x * blockIdx.x;
int y = threadIdx.y + blockDim.y * blockIdx.y;
if (x < w && y < h) {
size_t i = x + (size_t)w*y;
F[i] = lambda * ((c1 - U[i])*(c1 - U[i]) - (c2 - U[i])*(c2 - U[i]));
}
}
__device__ float diff_i(float *M, int w, int h, int x, int y)
{
size_t i = x + (size_t)w*y;
return (x+1 < w) ? (M[i + 1] - M[i]) : 0.f;
}
__device__ float diff_j(float *M, int w, int h, int x, int y)
{
size_t i = x + (size_t)w*y;
return (y+1 < h) ? (M[i + w] - M[i]) : 0.f;
}
__global__ void update_Xij(float *Xi, float *Xj, float *T, float *U, int w, int h, float sigma)
{
int x = threadIdx.x + blockDim.x * blockIdx.x;
int y = threadIdx.y + blockDim.y * blockIdx.y;
if (x < w && y < h) {
size_t i = x + (size_t)w*y;
float xi = Xi[i] - sigma * (2 * diff_i(U, w, h, x, y) - diff_i(T, w, h, x, y));
float xj = Xj[i] - sigma * (2 * diff_j(U, w, h, x, y) - diff_j(T, w, h, x, y));
float dn = max(1.f, sqrtf(xi*xi + xj*xj));
Xi[i] = xi / dn;
Xj[i] = xj / dn;
}
}
__device__ float divergence(float *X, float *Y, int w, int h, int x, int y)
{
size_t i = x + (size_t)w*y;
float dx_x = ((x+1 < w) ? X[i] : 0.f) - ((x > 0) ? X[i - 1] : 0.f);
float dy_y = ((y+1 < h) ? Y[i] : 0.f) - ((y > 0) ? Y[i - w] : 0.f);
return dx_x + dy_y;
}
__global__ void update_U(float *T, float *Xi, float *Xj, float *F, float *U, int w, int h, float tau)
{
int x = threadIdx.x + blockDim.x * blockIdx.x;
int y = threadIdx.y + blockDim.y * blockIdx.y;
if (x < w && y < h) {
size_t i = x + (size_t)w*y;
U[i] = clamp(0.f, T[i] - tau * (divergence(Xi, Xj, w, h, x, y) + F[i]), 1.f);
}
}
__global__ void update_Output(uchar4* output, float *U, int w, int h) {
int x = threadIdx.x + blockDim.x * blockIdx.x;
int y = threadIdx.y + blockDim.y * blockIdx.y;
size_t i = x + (size_t)w*y;
size_t idx = x + (size_t) w*(h-1 - y);
unsigned char temp_res = roundf((U[i] * 255.f));
output[idx].x = temp_res;
output[idx].y = temp_res;
output[idx].z = temp_res;
output[idx].w = 255;
}
inline int div_ceil(int n, int b) { return (n + b - 1) / b; }
__global__ void createVertices(float *in, uchar4* pixel, int w, int h)
{
...
...
@@ -17,9 +108,42 @@ __global__ void createVertices(float *in, uchar4* pixel, int w, int h)
void executeKernel(void *d_in, void *d_out, size_t w, size_t h)
{
float *
in
= reinterpret_cast<float *>(d_in);
float *
d_U
= reinterpret_cast<float *>(d_in);
uchar4 *pixel = reinterpret_cast<uchar4 *>(d_out);
dim3 dimBlock(16, 16, 1);
dim3 dimGrid(w / dimBlock.x, h / dimBlock.y, 1);
createVertices<<<dimGrid, dimBlock>>>(in, pixel, w, h);
// set parameters manually here
float lambda = 1.0;
float sigma = 0.4;
float tau = 0.4;
int N = 160;
float c1 = 1.0;
float c2 = 0.00;
float *d_T, *d_F, *d_Xi, *d_Xj;
size_t imageBytes = w*h*sizeof(float);
cudaMalloc(&d_T, imageBytes);
cudaMalloc(&d_F, imageBytes);
cudaMalloc(&d_Xi, imageBytes);
cudaMalloc(&d_Xj, imageBytes);
cudaMemcpy(d_T, d_U, imageBytes, cudaMemcpyDeviceToDevice);
cudaMemset(d_Xi, 0, imageBytes);
cudaMemset(d_Xj, 0, imageBytes);
calculate_F<<< dimGrid, dimBlock >>>(d_U, d_F, w, h, c1, c2, lambda);
for (int n = 0; n < N; n++) {
update_Xij<<< dimGrid, dimBlock >>>(d_Xi, d_Xj, d_T, d_U, w, h, sigma);
std::swap(d_U, d_T);
update_U<<< dimGrid, dimBlock >>>(d_T, d_Xi, d_Xj, d_F, d_U, w, h, tau);
}
update_Output<<< dimGrid, dimBlock >>>(pixel, d_U, w, h);
cudaFree(d_T);
cudaFree(d_F);
cudaFree(d_Xi);
cudaFree(d_Xj);
// createVertices<<<dimGrid, dimBlock>>>(in, pixel, w, h);
}
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