inline __host__ __device__
i_short2 gradient_descent_match2(i_short2 prediction, F f, FI& feature_img, float& distance, unsigned scale = 1)
{
i_short2 match = prediction;
float match_distance = feature_img.distance(f, prediction);
unsigned match_i = 8;
box2d domain = feature_img.domain() - border(7);
if (!domain.has(prediction)) return prediction;
assert(domain.has(prediction));
for (int search = 0; search < 7; search++)
{
for(int i = 0; i != 25; i++)
{
i_int2 n(prediction + i_int2(c25_h[i]));
{
float d = feature_img.distance(f, n, scale);
if (d < match_distance)
{
match = n;
match_i = i;
match_distance = d;
}
}
}
if (i_int2(prediction) == i_int2(match) || !domain.has(match))
break;
else
prediction = match;
}
distance = match_distance;
return match;
}
inline __host__ __device__
std::pair<i_short2, float> gradient_descent_match(i_short2 prediction_, F f, FI& feature_img, unsigned scale = 1)
{
typedef std::pair<i_short2, float> ret;
i_short2 prediction = prediction_;
typedef typename FI::architecture A;
i_short2 match = prediction;
float match_distance = feature_img.distance(f, prediction);
unsigned match_i = 8;
box2d domain = feature_img.domain() - border(0);
if (!domain.has(prediction))
{
return ret(prediction, 999999.f);
}
assert(domain.has(prediction));
for (int search = 0; search < 10; search++)
{
int i = arch_neighb2d<A>::get(c8_it_h, c8_it, match_i)[0];
int end = arch_neighb2d<A>::get(c8_it_h, c8_it, match_i)[1];
{
i_int2 n(prediction + i_int2(arch_neighb2d<A>::get(c8_h, c8, i)));
if (feature_img.domain().has(n))
{
float d = feature_img.distance(f, n, scale);
if (d < match_distance)
{
match = n;
match_i = i;
match_distance = d;
}
}
i = (i + 1) & 7;
}
#pragma unroll 4
for(; i != end; i = (i + 1) & 7)
{
i_int2 n(prediction + i_int2(arch_neighb2d<A>::get(c8_h, c8, i)));
if (feature_img.domain().has(n))
{
float d = feature_img.distance(f, n, scale);
if (d < match_distance)
{
match = n;
match_i = i;
match_distance = d;
}
}
}
if (i_int2(prediction) == i_int2(match) || !domain.has(match))
break;
else
prediction = match;
}
// if (scale == 2)
// match = prediction + 2 * (match - prediction);
// match_distance = feature_img.distance(f, match, scale);
return ret(match, match_distance);
}