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|---|---|---|---|
| 1 | #include "kondrashova_v_marking_components/tbb/include/ops_tbb.hpp" | ||
| 2 | |||
| 3 | #include <tbb/blocked_range.h> | ||
| 4 | #include <tbb/parallel_for.h> | ||
| 5 | #include <tbb/task_arena.h> | ||
| 6 | |||
| 7 | #include <algorithm> | ||
| 8 | #include <cstddef> | ||
| 9 | #include <cstdint> | ||
| 10 | #include <vector> | ||
| 11 | |||
| 12 | #include "kondrashova_v_marking_components/common/include/common.hpp" | ||
| 13 | #include "util/include/util.hpp" | ||
| 14 | |||
| 15 | namespace kondrashova_v_marking_components { | ||
| 16 | |||
| 17 |
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52 | KondrashovaVTaskTBB::KondrashovaVTaskTBB(const InType &in) { |
| 18 | SetTypeOfTask(GetStaticTypeOfTask()); | ||
| 19 | GetInput() = in; | ||
| 20 | 52 | GetOutput() = {}; | |
| 21 | 52 | } | |
| 22 | |||
| 23 | 52 | bool KondrashovaVTaskTBB::ValidationImpl() { | |
| 24 | 52 | return true; | |
| 25 | } | ||
| 26 | |||
| 27 | 52 | bool KondrashovaVTaskTBB::PreProcessingImpl() { | |
| 28 | const auto &in = GetInput(); | ||
| 29 | |||
| 30 | 52 | width_ = in.width; | |
| 31 | 52 | height_ = in.height; | |
| 32 | 52 | image_ = in.data; | |
| 33 | |||
| 34 |
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52 | if (width_ > 0 && height_ > 0 && static_cast<int>(image_.size()) == width_ * height_) { |
| 35 | ✗ | labels_1d_.assign(static_cast<size_t>(width_) * static_cast<size_t>(height_), 0); | |
| 36 | } else { | ||
| 37 | labels_1d_.clear(); | ||
| 38 | } | ||
| 39 | |||
| 40 |
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52 | GetOutput().count = 0; |
| 41 | GetOutput().labels.clear(); | ||
| 42 | 52 | return true; | |
| 43 | } | ||
| 44 | |||
| 45 | namespace { | ||
| 46 | |||
| 47 | int Find(std::vector<int> &parent, int xx) { | ||
| 48 | ✗ | while (parent[static_cast<size_t>(xx)] != xx) { | |
| 49 | ✗ | parent[static_cast<size_t>(xx)] = parent[static_cast<size_t>(parent[static_cast<size_t>(xx)])]; | |
| 50 | xx = parent[static_cast<size_t>(xx)]; | ||
| 51 | } | ||
| 52 | return xx; | ||
| 53 | } | ||
| 54 | |||
| 55 | ✗ | void Unite(std::vector<int> &parent, std::vector<int> &rnk, int aa, int bb) { | |
| 56 | aa = Find(parent, aa); | ||
| 57 | bb = Find(parent, bb); | ||
| 58 | ✗ | if (aa == bb) { | |
| 59 | return; | ||
| 60 | } | ||
| 61 | ✗ | if (rnk[static_cast<size_t>(aa)] < rnk[static_cast<size_t>(bb)]) { | |
| 62 | std::swap(aa, bb); | ||
| 63 | } | ||
| 64 | ✗ | parent[static_cast<size_t>(bb)] = aa; | |
| 65 | ✗ | if (rnk[static_cast<size_t>(aa)] == rnk[static_cast<size_t>(bb)]) { | |
| 66 | ✗ | rnk[static_cast<size_t>(aa)]++; | |
| 67 | } | ||
| 68 | } | ||
| 69 | |||
| 70 | int GetNeighborLabel(int ii, int jj, int di, int dj, int row_start, int row_end, int width, | ||
| 71 | const std::vector<uint8_t> &image, const std::vector<int> &local_labels) { | ||
| 72 | ✗ | int ni = ii + di; | |
| 73 | ✗ | int nj = jj + dj; | |
| 74 | ✗ | if (ni < row_start || ni >= row_end || nj < 0 || nj >= width) { | |
| 75 | return 0; | ||
| 76 | } | ||
| 77 | ✗ | auto nidx = (static_cast<size_t>(ni) * static_cast<size_t>(width)) + static_cast<size_t>(nj); | |
| 78 | ✗ | if (image[nidx] == 0) { | |
| 79 | ✗ | return local_labels[nidx]; | |
| 80 | } | ||
| 81 | return 0; | ||
| 82 | } | ||
| 83 | |||
| 84 | ✗ | void ScanStripe(int row_start, int row_end, int width, int label_offset, const std::vector<uint8_t> &image, | |
| 85 | std::vector<int> &local_labels) { | ||
| 86 | int current_label = label_offset; | ||
| 87 | ✗ | for (int ii = row_start; ii < row_end; ++ii) { | |
| 88 | ✗ | for (int jj = 0; jj < width; ++jj) { | |
| 89 | ✗ | auto idx = (static_cast<size_t>(ii) * static_cast<size_t>(width)) + static_cast<size_t>(jj); | |
| 90 | ✗ | if (image[idx] != 0) { | |
| 91 | ✗ | continue; | |
| 92 | } | ||
| 93 | |||
| 94 | ✗ | int left_label = GetNeighborLabel(ii, jj, 0, -1, row_start, row_end, width, image, local_labels); | |
| 95 | ✗ | int top_label = GetNeighborLabel(ii, jj, -1, 0, row_start, row_end, width, image, local_labels); | |
| 96 | |||
| 97 | ✗ | if (left_label == 0 && top_label == 0) { | |
| 98 | ✗ | local_labels[idx] = ++current_label; | |
| 99 | ✗ | } else if (left_label != 0 && top_label == 0) { | |
| 100 | ✗ | local_labels[idx] = left_label; | |
| 101 | ✗ | } else if (left_label == 0) { | |
| 102 | ✗ | local_labels[idx] = top_label; | |
| 103 | } else { | ||
| 104 | ✗ | local_labels[idx] = std::min(left_label, top_label); | |
| 105 | } | ||
| 106 | } | ||
| 107 | } | ||
| 108 | ✗ | } | |
| 109 | |||
| 110 | ✗ | void MergeHorizontal(int height, int width, const std::vector<int> &local_labels, std::vector<int> &parent, | |
| 111 | std::vector<int> &rnk) { | ||
| 112 | ✗ | for (int ii = 0; ii < height; ++ii) { | |
| 113 | ✗ | for (int jj = 1; jj < width; ++jj) { | |
| 114 | ✗ | auto idx = (static_cast<size_t>(ii) * static_cast<size_t>(width)) + static_cast<size_t>(jj); | |
| 115 | ✗ | auto lidx = (static_cast<size_t>(ii) * static_cast<size_t>(width)) + static_cast<size_t>(jj - 1); | |
| 116 | ✗ | if (local_labels[idx] != 0 && local_labels[lidx] != 0 && local_labels[idx] != local_labels[lidx]) { | |
| 117 | ✗ | Unite(parent, rnk, local_labels[idx], local_labels[lidx]); | |
| 118 | } | ||
| 119 | } | ||
| 120 | } | ||
| 121 | ✗ | } | |
| 122 | |||
| 123 | ✗ | void MergeBoundaries(int height, int width, int num_threads, const std::vector<int> &local_labels, | |
| 124 | std::vector<int> &parent, std::vector<int> &rnk) { | ||
| 125 | ✗ | for (int tid = 1; tid < num_threads; ++tid) { | |
| 126 | ✗ | const int boundary_row = (tid * height) / num_threads; | |
| 127 | ✗ | if (boundary_row >= height) { | |
| 128 | ✗ | continue; | |
| 129 | } | ||
| 130 | ✗ | for (int jj = 0; jj < width; ++jj) { | |
| 131 | ✗ | auto idx = (static_cast<size_t>(boundary_row) * static_cast<size_t>(width)) + static_cast<size_t>(jj); | |
| 132 | ✗ | auto tidx = (static_cast<size_t>(boundary_row - 1) * static_cast<size_t>(width)) + static_cast<size_t>(jj); | |
| 133 | ✗ | if (local_labels[idx] != 0 && local_labels[tidx] != 0 && local_labels[idx] != local_labels[tidx]) { | |
| 134 | ✗ | Unite(parent, rnk, local_labels[idx], local_labels[tidx]); | |
| 135 | } | ||
| 136 | } | ||
| 137 | } | ||
| 138 | ✗ | } | |
| 139 | |||
| 140 | ✗ | int Relabel(int total, const std::vector<int> &local_labels, std::vector<int> &parent, std::vector<int> &relabel_map, | |
| 141 | std::vector<int> &labels_1d) { | ||
| 142 | int count = 0; | ||
| 143 | ✗ | for (int ii = 0; ii < total; ++ii) { | |
| 144 | ✗ | auto idx = static_cast<size_t>(ii); | |
| 145 | ✗ | if (local_labels[idx] == 0) { | |
| 146 | ✗ | continue; | |
| 147 | } | ||
| 148 | int root = Find(parent, local_labels[idx]); | ||
| 149 | ✗ | if (relabel_map[static_cast<size_t>(root)] == 0) { | |
| 150 | ✗ | relabel_map[static_cast<size_t>(root)] = ++count; | |
| 151 | } | ||
| 152 | ✗ | labels_1d[idx] = relabel_map[static_cast<size_t>(root)]; | |
| 153 | } | ||
| 154 | ✗ | return count; | |
| 155 | } | ||
| 156 | |||
| 157 | } // namespace | ||
| 158 | |||
| 159 | 52 | bool KondrashovaVTaskTBB::RunImpl() { | |
| 160 |
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52 | if (width_ <= 0 || height_ <= 0 || image_.empty()) { |
| 161 | 52 | GetOutput().count = 0; | |
| 162 | 52 | return true; | |
| 163 | } | ||
| 164 | |||
| 165 | ✗ | const int total = width_ * height_; | |
| 166 | ✗ | const int num_threads = ppc::util::GetNumThreads(); | |
| 167 | ✗ | const int max_labels_per_thread = total + 1; | |
| 168 | ✗ | const int max_total_labels = (num_threads * max_labels_per_thread) + 1; | |
| 169 | |||
| 170 | ✗ | std::vector<int> local_labels(static_cast<size_t>(total), 0); | |
| 171 | |||
| 172 | ✗ | const int width = width_; | |
| 173 | ✗ | const int height = height_; | |
| 174 | ✗ | const std::vector<uint8_t> &image = image_; | |
| 175 | |||
| 176 | // Параллельное сканирование через TBB | ||
| 177 | ✗ | tbb::task_arena arena(num_threads); | |
| 178 | ✗ | arena.execute([&] { | |
| 179 | ✗ | tbb::parallel_for(tbb::blocked_range<int>(0, num_threads), [&](const tbb::blocked_range<int> &range) { | |
| 180 | ✗ | for (int tid = range.begin(); tid < range.end(); ++tid) { | |
| 181 | ✗ | const int row_start = (tid * height) / num_threads; | |
| 182 | ✗ | const int row_end = ((tid + 1) * height) / num_threads; | |
| 183 | ✗ | const int label_offset = tid * max_labels_per_thread; | |
| 184 | ✗ | ScanStripe(row_start, row_end, width, label_offset, image, local_labels); | |
| 185 | } | ||
| 186 | ✗ | }, tbb::simple_partitioner()); | |
| 187 | ✗ | }); | |
| 188 | |||
| 189 | ✗ | std::vector<int> parent(static_cast<size_t>(max_total_labels)); | |
| 190 | ✗ | std::vector<int> rnk(static_cast<size_t>(max_total_labels), 0); | |
| 191 | ✗ | for (int ii = 0; ii < max_total_labels; ++ii) { | |
| 192 | ✗ | parent[static_cast<size_t>(ii)] = ii; | |
| 193 | } | ||
| 194 | |||
| 195 | ✗ | MergeHorizontal(height, width, local_labels, parent, rnk); | |
| 196 | ✗ | MergeBoundaries(height, width, num_threads, local_labels, parent, rnk); | |
| 197 | |||
| 198 | ✗ | std::vector<int> relabel_map(static_cast<size_t>(max_total_labels), 0); | |
| 199 | ✗ | GetOutput().count = Relabel(total, local_labels, parent, relabel_map, labels_1d_); | |
| 200 | |||
| 201 | return true; | ||
| 202 | } | ||
| 203 | |||
| 204 | 52 | bool KondrashovaVTaskTBB::PostProcessingImpl() { | |
| 205 |
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52 | if (width_ <= 0 || height_ <= 0) { |
| 206 | GetOutput().labels.clear(); | ||
| 207 | 52 | return true; | |
| 208 | } | ||
| 209 | |||
| 210 | ✗ | GetOutput().labels.assign(height_, std::vector<int>(width_, 0)); | |
| 211 | ✗ | for (int ii = 0; ii < height_; ++ii) { | |
| 212 | ✗ | for (int jj = 0; jj < width_; ++jj) { | |
| 213 | ✗ | auto idx = (static_cast<size_t>(ii) * static_cast<size_t>(width_)) + static_cast<size_t>(jj); | |
| 214 | ✗ | GetOutput().labels[ii][jj] = labels_1d_[idx]; | |
| 215 | } | ||
| 216 | } | ||
| 217 | return true; | ||
| 218 | } | ||
| 219 | |||
| 220 | } // namespace kondrashova_v_marking_components | ||
| 221 |