KCF_Tracker::KCF_Tracker(double padding, double kernel_sigma, double lambda, double interp_factor,
double output_sigma_factor, int cell_size)
- : fft(*new FFT()), p_padding(padding), p_output_sigma_factor(output_sigma_factor), p_kernel_sigma(kernel_sigma),
- p_lambda(lambda), p_interp_factor(interp_factor), p_cell_size(cell_size), d(*new Kcf_Tracker_Private)
+ : p_cell_size(cell_size), fft(*new FFT()), p_padding(padding), p_output_sigma_factor(output_sigma_factor), p_kernel_sigma(kernel_sigma),
+ p_lambda(lambda), p_interp_factor(interp_factor), d(*new Kcf_Tracker_Private)
{
}
tmp.w *= p_current_scale;
tmp.h *= p_current_scale;
- if (p_resize_image) tmp.scale(1 / p_downscale_factor);
+ if (p_resize_image)
+ tmp.scale(1 / p_downscale_factor);
if (p_fit_to_pw2) {
tmp.scale_x(1 / p_scale_factor_x);
tmp.scale_y(1 / p_scale_factor_y);
}
}
#else
- // FIXME: Iterate correctly in big batch mode - perhaps have only one element in the list
for (uint j = 0; j < p_scales.size(); ++j) {
if (d.threadctxs[0].max[j].response > max) {
max = d.threadctxs[0].max[j].response;
it.async_res.wait();
#else // !ASYNC
- // FIXME: Iterate correctly in big batch mode - perhaps have only one element in the list
NORMAL_OMP_PARALLEL_FOR
for (uint i = 0; i < d.threadctxs.size(); ++i)
d.threadctxs[i].track(*this, input_rgb, input_gray);