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reduction to 2x2 clusters for general clusters

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mazzol_a
2025-08-18 18:23:15 +02:00
parent 9a3694b980
commit cb163c79b4
5 changed files with 205 additions and 106 deletions
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220
include/aare/Cluster.hpp
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@@ -8,6 +8,7 @@
#pragma once
#include "logger.hpp"
#include <algorithm>
#include <array>
#include <cstdint>
@@ -74,104 +75,149 @@ struct Cluster {
}
};
template<typename T>
Cluster<T, 2, 2, uint16_t> reduce_3x3_to_2x2(const Cluster<T, 3, 3, uint16_t> &c) {
Cluster<T, 2, 2, uint16_t> result;
auto [s, i] = c.max_sum_2x2();
switch (i) {
case 0:
result.x = c.x-1;
result.y = c.y+1;
result.data = {c.data[0], c.data[1], c.data[3], c.data[4]};
break;
case 1:
result.x = c.x;
result.y = c.y + 1;
result.data = {c.data[1], c.data[2], c.data[4], c.data[5]};
break;
case 2:
result.x = c.x -1;
result.y = c.y;
result.data = {c.data[3], c.data[4], c.data[6], c.data[7]};
break;
case 3:
result.x = c.x;
result.y = c.y;
result.data = {c.data[4], c.data[5], c.data[7], c.data[8]};
break;
}
/**
* @brief Reduce a cluster to a 2x2 cluster by selecting the 2x2 block with the
* highest sum.
* @param c Cluster to reduce
* @return Cluster<T, 2, 2, uint16_t> reduced cluster
*/
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
typename CoordType = int16_t>
Cluster<T, 2, 2, CoordType>
reduce_to_2x2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &c) {
// do some stuff
static_assert(ClusterSizeX >= 2 && ClusterSizeY >= 2,
"Cluster sizes must be at least 2x2 for reduction to 2x2");
Cluster<T, 2, 2, CoordType> result;
auto [sum, index] = c.max_sum_2x2();
int16_t cluster_center_index =
(ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
int16_t index_bottom_left_max_2x2_subcluster =
(int(index / (ClusterSizeX - 1))) * ClusterSizeX +
index % (ClusterSizeX - 1);
result.x =
c.x + (index_bottom_left_max_2x2_subcluster - cluster_center_index) %
ClusterSizeX;
result.y =
c.y - (index_bottom_left_max_2x2_subcluster - cluster_center_index) /
ClusterSizeX;
result.data = {
c.data[index_bottom_left_max_2x2_subcluster],
c.data[index_bottom_left_max_2x2_subcluster + 1],
c.data[index_bottom_left_max_2x2_subcluster + ClusterSizeX],
c.data[index_bottom_left_max_2x2_subcluster + ClusterSizeX + 1]};
return result;
}
template<typename T>
Cluster<T, 3, 3, uint16_t> reduce_5x5_to_3x3(const Cluster<T, 5, 5, uint16_t> &c) {
template <typename T>
Cluster<T, 3, 3, uint16_t>
reduce_5x5_to_3x3(const Cluster<T, 5, 5, uint16_t> &c) {
Cluster<T, 3, 3, uint16_t> result;
// Reduce the 5x5 cluster to a 3x3 cluster by selecting the 3x3 block with the highest sum
// Reduce the 5x5 cluster to a 3x3 cluster by selecting the 3x3 block with
// the highest sum
std::array<T, 9> sum_3x3_subclusters;
//Write out the sums in the hope that the compiler can optimize this
sum_3x3_subclusters[0] = c.data[0] + c.data[1] + c.data[2] + c.data[5] + c.data[6] + c.data[7] + c.data[10] + c.data[11] + c.data[12];
sum_3x3_subclusters[1] = c.data[1] + c.data[2] + c.data[3] + c.data[6] + c.data[7] + c.data[8] + c.data[11] + c.data[12] + c.data[13];
sum_3x3_subclusters[2] = c.data[2] + c.data[3] + c.data[4] + c.data[7] + c.data[8] + c.data[9] + c.data[12] + c.data[13] + c.data[14];
sum_3x3_subclusters[3] = c.data[5] + c.data[6] + c.data[7] + c.data[10] + c.data[11] + c.data[12] + c.data[15] + c.data[16] + c.data[17];
sum_3x3_subclusters[4] = c.data[6] + c.data[7] + c.data[8] + c.data[11] + c.data[12] + c.data[13] + c.data[16] + c.data[17] + c.data[18];
sum_3x3_subclusters[5] = c.data[7] + c.data[8] + c.data[9] + c.data[12] + c.data[13] + c.data[14] + c.data[17] + c.data[18] + c.data[19];
sum_3x3_subclusters[6] = c.data[10] + c.data[11] + c.data[12] + c.data[15] + c.data[16] + c.data[17] + c.data[20] + c.data[21] + c.data[22];
sum_3x3_subclusters[7] = c.data[11] + c.data[12] + c.data[13] + c.data[16] + c.data[17] + c.data[18] + c.data[21] + c.data[22] + c.data[23];
sum_3x3_subclusters[8] = c.data[12] + c.data[13] + c.data[14] + c.data[17] + c.data[18] + c.data[19] + c.data[22] + c.data[23] + c.data[24];
// Write out the sums in the hope that the compiler can optimize this
sum_3x3_subclusters[0] = c.data[0] + c.data[1] + c.data[2] + c.data[5] +
c.data[6] + c.data[7] + c.data[10] + c.data[11] +
c.data[12];
sum_3x3_subclusters[1] = c.data[1] + c.data[2] + c.data[3] + c.data[6] +
c.data[7] + c.data[8] + c.data[11] + c.data[12] +
c.data[13];
sum_3x3_subclusters[2] = c.data[2] + c.data[3] + c.data[4] + c.data[7] +
c.data[8] + c.data[9] + c.data[12] + c.data[13] +
c.data[14];
sum_3x3_subclusters[3] = c.data[5] + c.data[6] + c.data[7] + c.data[10] +
c.data[11] + c.data[12] + c.data[15] + c.data[16] +
c.data[17];
sum_3x3_subclusters[4] = c.data[6] + c.data[7] + c.data[8] + c.data[11] +
c.data[12] + c.data[13] + c.data[16] + c.data[17] +
c.data[18];
sum_3x3_subclusters[5] = c.data[7] + c.data[8] + c.data[9] + c.data[12] +
c.data[13] + c.data[14] + c.data[17] + c.data[18] +
c.data[19];
sum_3x3_subclusters[6] = c.data[10] + c.data[11] + c.data[12] + c.data[15] +
c.data[16] + c.data[17] + c.data[20] + c.data[21] +
c.data[22];
sum_3x3_subclusters[7] = c.data[11] + c.data[12] + c.data[13] + c.data[16] +
c.data[17] + c.data[18] + c.data[21] + c.data[22] +
c.data[23];
sum_3x3_subclusters[8] = c.data[12] + c.data[13] + c.data[14] + c.data[17] +
c.data[18] + c.data[19] + c.data[22] + c.data[23] +
c.data[24];
auto index = std::max_element(sum_3x3_subclusters.begin(), sum_3x3_subclusters.end()) - sum_3x3_subclusters.begin();
auto index = std::max_element(sum_3x3_subclusters.begin(),
sum_3x3_subclusters.end()) -
sum_3x3_subclusters.begin();
switch (index) {
case 0:
result.x = c.x - 1;
result.y = c.y + 1;
result.data = {c.data[0], c.data[1], c.data[2], c.data[5], c.data[6], c.data[7], c.data[10], c.data[11], c.data[12]};
break;
case 1:
result.x = c.x;
result.y = c.y + 1;
result.data = {c.data[1], c.data[2], c.data[3], c.data[6], c.data[7], c.data[8], c.data[11], c.data[12], c.data[13]};
break;
case 2:
result.x = c.x + 1;
result.y = c.y + 1;
result.data = {c.data[2], c.data[3], c.data[4], c.data[7], c.data[8], c.data[9], c.data[12], c.data[13], c.data[14]};
break;
case 3:
result.x = c.x - 1;
result.y = c.y;
result.data = {c.data[5], c.data[6], c.data[7], c.data[10], c.data[11], c.data[12], c.data[15], c.data[16], c.data[17]};
break;
case 4:
result.x = c.x + 1;
result.y = c.y;
result.data = {c.data[6], c.data[7], c.data[8], c.data[11], c.data[12], c.data[13], c.data[16], c.data[17], c.data[18]};
break;
case 5:
result.x = c.x + 1;
result.y = c.y;
result.data = {c.data[7], c.data[8], c.data[9], c.data[12], c.data[13], c.data[14], c.data[17], c.data[18], c.data[19]};
break;
case 6:
result.x = c.x + 1;
result.y = c.y -1;
result.data = {c.data[10], c.data[11], c.data[12], c.data[15], c.data[16], c.data[17], c.data[20], c.data[21], c.data[22]};
break;
case 7:
result.x = c.x + 1;
result.y = c.y-1;
result.data = {c.data[11], c.data[12], c.data[13], c.data[16], c.data[17], c.data[18], c.data[21], c.data[22], c.data[23]};
break;
case 8:
result.x = c.x + 1;
result.y = c.y-1;
result.data = {c.data[12], c.data[13], c.data[14], c.data[17], c.data[18], c.data[19], c.data[22], c.data[23], c.data[24]};
break;
case 0:
result.x = c.x - 1;
result.y = c.y + 1;
result.data = {c.data[0], c.data[1], c.data[2], c.data[5], c.data[6],
c.data[7], c.data[10], c.data[11], c.data[12]};
break;
case 1:
result.x = c.x;
result.y = c.y + 1;
result.data = {c.data[1], c.data[2], c.data[3], c.data[6], c.data[7],
c.data[8], c.data[11], c.data[12], c.data[13]};
break;
case 2:
result.x = c.x + 1;
result.y = c.y + 1;
result.data = {c.data[2], c.data[3], c.data[4], c.data[7], c.data[8],
c.data[9], c.data[12], c.data[13], c.data[14]};
break;
case 3:
result.x = c.x - 1;
result.y = c.y;
result.data = {c.data[5], c.data[6], c.data[7],
c.data[10], c.data[11], c.data[12],
c.data[15], c.data[16], c.data[17]};
break;
case 4:
result.x = c.x + 1;
result.y = c.y;
result.data = {c.data[6], c.data[7], c.data[8],
c.data[11], c.data[12], c.data[13],
c.data[16], c.data[17], c.data[18]};
break;
case 5:
result.x = c.x + 1;
result.y = c.y;
result.data = {c.data[7], c.data[8], c.data[9],
c.data[12], c.data[13], c.data[14],
c.data[17], c.data[18], c.data[19]};
break;
case 6:
result.x = c.x + 1;
result.y = c.y - 1;
result.data = {c.data[10], c.data[11], c.data[12],
c.data[15], c.data[16], c.data[17],
c.data[20], c.data[21], c.data[22]};
break;
case 7:
result.x = c.x + 1;
result.y = c.y - 1;
result.data = {c.data[11], c.data[12], c.data[13],
c.data[16], c.data[17], c.data[18],
c.data[21], c.data[22], c.data[23]};
break;
case 8:
result.x = c.x + 1;
result.y = c.y - 1;
result.data = {c.data[12], c.data[13], c.data[14],
c.data[17], c.data[18], c.data[19],
c.data[22], c.data[23], c.data[24]};
break;
}
// do some stuff

19
include/aare/ClusterVector.hpp
View File

@@ -32,8 +32,7 @@ class ClusterVector; // Forward declaration
*/
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
typename CoordType>
class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>
{
class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
std::vector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> m_data{};
int32_t m_frame_number{0}; // TODO! Check frame number size and type
@@ -173,17 +172,21 @@ class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>
}
};
template<typename T>
ClusterVector<Cluster<T, 2, 2, uint16_t>> reduce_3x3_to_2x2(const ClusterVector<Cluster<T, 3, 3, uint16_t>> &cv) {
ClusterVector<Cluster<T, 2, 2, uint16_t>> result;
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
typename CoordType>
ClusterVector<Cluster<T, 2, 2, CoordType>> reduce_to_2x2(
const ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>
&cv) {
ClusterVector<Cluster<T, 2, 2, CoordType>> result;
for (const auto &c : cv) {
result.push_back(reduce_3x3_to_2x2(c));
result.push_back(reduce_to_2x2(c));
}
return result;
}
template<typename T>
ClusterVector<Cluster<T, 3, 3, uint16_t>> reduce_5x5_to_3x3(const ClusterVector<Cluster<T, 5, 5, uint16_t>> &cv) {
template <typename T>
ClusterVector<Cluster<T, 3, 3, uint16_t>>
reduce_5x5_to_3x3(const ClusterVector<Cluster<T, 5, 5, uint16_t>> &cv) {
ClusterVector<Cluster<T, 3, 3, uint16_t>> result;
for (const auto &c : cv) {
result.push_back(reduce_5x5_to_3x3(c));