static void kalman_correct(kalman_t *kf, float p, float v)
{
/* K = P * HT * inv(H * P * HT + R) */
m_mlt(kf->H, kf->P, kf->T0);
mmtr_mlt(kf->T0, kf->H, kf->T1);
m_add(kf->T1, kf->R, kf->T0);
m_inverse(kf->T0, kf->T1);
mmtr_mlt(kf->P, kf->H, kf->T0);
m_mlt(kf->T0, kf->T1, kf->K);
/* x = x + K * (z - H * x) */
mv_mlt(kf->H, kf->x, kf->t0);
v_set_val(kf->z, 0, p);
v_set_val(kf->z, 1, v);
v_sub(kf->z, kf->t0, kf->t1);
mv_mlt(kf->K, kf->t1, kf->t0);
v_add(kf->x, kf->t0, kf->t1);
v_copy(kf->t1, kf->x);
/* P = (I - K * H) * P */
m_mlt(kf->K, kf->H, kf->T0);
m_sub(kf->I, kf->T0, kf->T1);
m_mlt(kf->T1, kf->P, kf->T0);
m_copy(kf->T0, kf->P);
}
static void test_gmres(ITER *ip, int i, MAT *Q, MAT *R,
VEC *givc, VEC *givs, double h_val)
#endif
{
VEC vt, vt1;
STATIC MAT *Q1=MNULL, *R1=MNULL;
int j;
/* test Q*A*Q^T = R */
Q = m_resize(Q,i+1,ip->b->dim);
Q1 = m_resize(Q1,i+1,ip->b->dim);
R1 = m_resize(R1,i+1,i+1);
MEM_STAT_REG(Q1,TYPE_MAT);
MEM_STAT_REG(R1,TYPE_MAT);
vt.dim = vt.max_dim = ip->b->dim;
vt1.dim = vt1.max_dim = ip->b->dim;
for (j=0; j <= i; j++) {
vt.ve = Q->me[j];
vt1.ve = Q1->me[j];
ip->Ax(ip->A_par,&vt,&vt1);
}
mmtr_mlt(Q,Q1,R1);
R1 = m_resize(R1,i+2,i+1);
for (j=0; j < i; j++)
R1->me[i+1][j] = 0.0;
R1->me[i+1][i] = h_val;
for (j = 0; j <= i; j++) {
rot_rows(R1,j,j+1,givc->ve[j],givs->ve[j],R1);
}
R1 = m_resize(R1,i+1,i+1);
m_sub(R,R1,R1);
/* if (m_norm_inf(R1) > MACHEPS*ip->b->dim) */
#ifndef MEX
printf(" %d. ||Q*A*Q^T - H|| = %g [cf. MACHEPS = %g]\n",
ip->steps,m_norm_inf(R1),MACHEPS);
#endif
/* check Q*Q^T = I */
Q = m_resize(Q,i+1,ip->b->dim);
mmtr_mlt(Q,Q,R1);
for (j=0; j <= i; j++)
R1->me[j][j] -= 1.0;
#ifndef MEX
if (m_norm_inf(R1) > MACHEPS*ip->b->dim)
printf(" ! m_norm_inf(Q*Q^T) = %g\n",m_norm_inf(R1));
#endif
#ifdef THREADSAFE
M_FREE(Q1);
M_FREE(R1);
#endif
}
MAT *XVXt_mlt(MAT *X, MAT *V, MAT *out) {
/* for a symmetric matrix V, return X V X' */
static MAT *VXt = MNULL;
int i, j, k;
if (X==(MAT *)NULL || V==(MAT *)NULL )
error(E_NULL, "XtVX_mlt");
if (X->n != V->m)
error(E_SIZES, "XtVX_mlt");
if (V->m != V->n)
error(E_SQUARE, "XtVX_mlt");
out = m_resize(out, X->m, X->m);
VXt = m_resize(VXt, V->m, X->n);
m_zero(out);
VXt = mmtr_mlt(V, X, VXt);
for (i = 0; i < X->m; i++) {
for (j = i; j < X->m; j++)
for (k = 0; k < X->n; k++)
out->me[i][j] += X->me[i][k] * VXt->me[k][j];
for (j = 0; j <= i; j++) /* symmetry */
out->me[i][j] = out->me[j][i];
}
return out;
}
static void kalman_predict(kalman_t *kf, float a)
{
/* x = A * x + B * u */
v_set_val(kf->u, 0, a);
mv_mlt(kf->A, kf->x, kf->t0);
mv_mlt(kf->B, kf->u, kf->t1);
v_add(kf->t0, kf->t1, kf->x);
/* P = A * P * AT + Q */
m_mlt(kf->A, kf->P, kf->T0);
mmtr_mlt(kf->T0, kf->A, kf->T1);
m_add(kf->T1, kf->Q, kf->P);
}
// Main
int main(int argc, char ** argv) {
// Choose the best GPU in case there are multiple available
choose_GPU();
// Keep track of the start time of the program
long long program_start_time = get_time();
if (argc !=3){
fprintf(stderr, "usage: %s <input file> <number of frames to process>", argv[0]);
exit(1);
}
// Let the user specify the number of frames to process
int num_frames = atoi(argv[2]);
// Open video file
char *video_file_name = argv[1];
avi_t *cell_file = AVI_open_input_file(video_file_name, 1);
if (cell_file == NULL) {
AVI_print_error("Error with AVI_open_input_file");
return -1;
}
int i, j, *crow, *ccol, pair_counter = 0, x_result_len = 0, Iter = 20, ns = 4, k_count = 0, n;
MAT *cellx, *celly, *A;
double *GICOV_spots, *t, *G, *x_result, *y_result, *V, *QAX_CENTERS, *QAY_CENTERS;
double threshold = 1.8, radius = 10.0, delta = 3.0, dt = 0.01, b = 5.0;
// Extract a cropped version of the first frame from the video file
MAT *image_chopped = get_frame(cell_file, 0, 1, 0);
printf("Detecting cells in frame 0\n");
// Get gradient matrices in x and y directions
MAT *grad_x = gradient_x(image_chopped);
MAT *grad_y = gradient_y(image_chopped);
// Allocate for gicov_mem and strel
gicov_mem = (float*) malloc(sizeof(float) * grad_x->m * grad_y->n);
strel = (float*) malloc(sizeof(float) * strel_m * strel_n);
m_free(image_chopped);
int grad_m = grad_x->m;
int grad_n = grad_y->n;
#pragma acc data create(sin_angle,cos_angle,theta,tX,tY) \
create(gicov_mem[0:grad_x->m*grad_y->n])
{
// Precomputed constants on GPU
compute_constants();
// Get GICOV matrices corresponding to image gradients
long long GICOV_start_time = get_time();
MAT *gicov = GICOV(grad_x, grad_y);
long long GICOV_end_time = get_time();
// Dilate the GICOV matrices
long long dilate_start_time = get_time();
MAT *img_dilated = dilate(gicov);
long long dilate_end_time = get_time();
} /* end acc data */
// Find possible matches for cell centers based on GICOV and record the rows/columns in which they are found
pair_counter = 0;
crow = (int *) malloc(gicov->m * gicov->n * sizeof(int));
ccol = (int *) malloc(gicov->m * gicov->n * sizeof(int));
for(i = 0; i < gicov->m; i++) {
for(j = 0; j < gicov->n; j++) {
if(!double_eq(m_get_val(gicov,i,j), 0.0) && double_eq(m_get_val(img_dilated,i,j), m_get_val(gicov,i,j)))
{
crow[pair_counter]=i;
ccol[pair_counter]=j;
pair_counter++;
}
}
}
GICOV_spots = (double *) malloc(sizeof(double) * pair_counter);
for(i = 0; i < pair_counter; i++)
GICOV_spots[i] = sqrt(m_get_val(gicov, crow[i], ccol[i]));
G = (double *) calloc(pair_counter, sizeof(double));
x_result = (double *) calloc(pair_counter, sizeof(double));
y_result = (double *) calloc(pair_counter, sizeof(double));
x_result_len = 0;
for (i = 0; i < pair_counter; i++) {
if ((crow[i] > 29) && (crow[i] < BOTTOM - TOP + 39)) {
x_result[x_result_len] = ccol[i];
y_result[x_result_len] = crow[i] - 40;
G[x_result_len] = GICOV_spots[i];
x_result_len++;
}
}
// Make an array t which holds each "time step" for the possible cells
t = (double *) malloc(sizeof(double) * 36);
for (i = 0; i < 36; i++) {
t[i] = (double)i * 2.0 * PI / 36.0;
}
// Store cell boundaries (as simple circles) for all cells
cellx = m_get(x_result_len, 36);
celly = m_get(x_result_len, 36);
for(i = 0; i < x_result_len; i++) {
for(j = 0; j < 36; j++) {
m_set_val(cellx, i, j, x_result[i] + radius * cos(t[j]));
m_set_val(celly, i, j, y_result[i] + radius * sin(t[j]));
}
}
A = TMatrix(9,4);
V = (double *) malloc(sizeof(double) * pair_counter);
QAX_CENTERS = (double * )malloc(sizeof(double) * pair_counter);
QAY_CENTERS = (double *) malloc(sizeof(double) * pair_counter);
memset(V, 0, sizeof(double) * pair_counter);
memset(QAX_CENTERS, 0, sizeof(double) * pair_counter);
memset(QAY_CENTERS, 0, sizeof(double) * pair_counter);
// For all possible results, find the ones that are feasibly leukocytes and store their centers
k_count = 0;
for (n = 0; n < x_result_len; n++) {
if ((G[n] < -1 * threshold) || G[n] > threshold) {
MAT * x, *y;
VEC * x_row, * y_row;
x = m_get(1, 36);
y = m_get(1, 36);
x_row = v_get(36);
y_row = v_get(36);
// Get current values of possible cells from cellx/celly matrices
x_row = get_row(cellx, n, x_row);
y_row = get_row(celly, n, y_row);
uniformseg(x_row, y_row, x, y);
// Make sure that the possible leukocytes are not too close to the edge of the frame
if ((m_min(x) > b) && (m_min(y) > b) && (m_max(x) < cell_file->width - b) && (m_max(y) < cell_file->height - b)) {
MAT * Cx, * Cy, *Cy_temp, * Ix1, * Iy1;
VEC *Xs, *Ys, *W, *Nx, *Ny, *X, *Y;
Cx = m_get(1, 36);
Cy = m_get(1, 36);
Cx = mmtr_mlt(A, x, Cx);
Cy = mmtr_mlt(A, y, Cy);
Cy_temp = m_get(Cy->m, Cy->n);
for (i = 0; i < 9; i++)
m_set_val(Cy, i, 0, m_get_val(Cy, i, 0) + 40.0);
// Iteratively refine the snake/spline
for (i = 0; i < Iter; i++) {
int typeofcell;
if(G[n] > 0.0) typeofcell = 0;
else typeofcell = 1;
splineenergyform01(Cx, Cy, grad_x, grad_y, ns, delta, 2.0 * dt, typeofcell);
}
X = getsampling(Cx, ns);
for (i = 0; i < Cy->m; i++)
m_set_val(Cy_temp, i, 0, m_get_val(Cy, i, 0) - 40.0);
Y = getsampling(Cy_temp, ns);
Ix1 = linear_interp2(grad_x, X, Y);
Iy1 = linear_interp2(grad_x, X, Y);
Xs = getfdriv(Cx, ns);
Ys = getfdriv(Cy, ns);
Nx = v_get(Ys->dim);
for (i = 0; i < Ys->dim; i++)
v_set_val(Nx, i, v_get_val(Ys, i) / sqrt(v_get_val(Xs, i)*v_get_val(Xs, i) + v_get_val(Ys, i)*v_get_val(Ys, i)));
Ny = v_get(Xs->dim);
for (i = 0; i < Xs->dim; i++)
v_set_val(Ny, i, -1.0 * v_get_val(Xs, i) / sqrt(v_get_val(Xs, i)*v_get_val(Xs, i) + v_get_val(Ys, i)*v_get_val(Ys, i)));
W = v_get(Nx->dim);
for (i = 0; i < Nx->dim; i++)
v_set_val(W, i, m_get_val(Ix1, 0, i) * v_get_val(Nx, i) + m_get_val(Iy1, 0, i) * v_get_val(Ny, i));
V[n] = mean(W) / std_dev(W);
// Find the cell centers by computing the means of X and Y values for all snaxels of the spline contour
QAX_CENTERS[k_count] = mean(X);
QAY_CENTERS[k_count] = mean(Y) + TOP;
k_count++;
// Free memory
v_free(W);
v_free(Ny);
v_free(Nx);
v_free(Ys);
v_free(Xs);
m_free(Iy1);
m_free(Ix1);
v_free(Y);
v_free(X);
m_free(Cy_temp);
m_free(Cy);
m_free(Cx);
}
// Free memory
v_free(y_row);
v_free(x_row);
m_free(y);
m_free(x);
}
}
// Free memory
free(gicov_mem);
free(strel);
free(V);
free(ccol);
free(crow);
free(GICOV_spots);
free(t);
free(G);
free(x_result);
free(y_result);
m_free(A);
m_free(celly);
m_free(cellx);
m_free(img_dilated);
m_free(gicov);
m_free(grad_y);
m_free(grad_x);
// Report the total number of cells detected
printf("Cells detected: %d\n\n", k_count);
// Report the breakdown of the detection runtime
printf("Detection runtime\n");
printf("-----------------\n");
printf("GICOV computation: %.5f seconds\n", ((float) (GICOV_end_time - GICOV_start_time)) / (1000*1000));
printf(" GICOV dilation: %.5f seconds\n", ((float) (dilate_end_time - dilate_start_time)) / (1000*1000));
printf(" Total: %.5f seconds\n", ((float) (get_time() - program_start_time)) / (1000*1000));
// Now that the cells have been detected in the first frame,
// track the ellipses through subsequent frames
if (num_frames > 1) printf("\nTracking cells across %d frames\n", num_frames);
else printf("\nTracking cells across 1 frame\n");
long long tracking_start_time = get_time();
int num_snaxels = 20;
ellipsetrack(cell_file, QAX_CENTERS, QAY_CENTERS, k_count, radius, num_snaxels, num_frames);
printf(" Total: %.5f seconds\n", ((float) (get_time() - tracking_start_time)) / (float) (1000*1000*num_frames));
// Report total program execution time
printf("\nTotal application run time: %.5f seconds\n", ((float) (get_time() - program_start_time)) / (1000*1000));
return 0;
}
