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|---|---|---|---|
| 1 | #include "kamalagin_a_binary_image_convex_hull/seq/include/ops_seq.hpp" | ||
| 2 | |||
| 3 | #include <algorithm> | ||
| 4 | #include <array> | ||
| 5 | #include <cstddef> | ||
| 6 | #include <cstdint> | ||
| 7 | #include <utility> | ||
| 8 | #include <vector> | ||
| 9 | |||
| 10 | #include "kamalagin_a_binary_image_convex_hull/common/include/common.hpp" | ||
| 11 | |||
| 12 | namespace kamalagin_a_binary_image_convex_hull { | ||
| 13 | |||
| 14 | namespace { | ||
| 15 | |||
| 16 | constexpr std::array<std::pair<int, int>, 4> kFourNeighbors = {{{-1, 0}, {1, 0}, {0, -1}, {0, 1}}}; | ||
| 17 | |||
| 18 | int64_t Cross(const Point &o, const Point &a, const Point &b) { | ||
| 19 | 264 | return (static_cast<int64_t>(a.x - o.x) * (b.y - o.y)) - (static_cast<int64_t>(a.y - o.y) * (b.x - o.x)); | |
| 20 | } | ||
| 21 | |||
| 22 | int64_t DistSq(const Point &a, const Point &b) { | ||
| 23 | 112 | const int dx = a.x - b.x; | |
| 24 | 112 | const int dy = a.y - b.y; | |
| 25 | 112 | return (static_cast<int64_t>(dx) * dx) + (static_cast<int64_t>(dy) * dy); | |
| 26 | } | ||
| 27 | |||
| 28 | 24 | size_t GrahamFindPivot(std::vector<Point> &pts) { | |
| 29 | size_t pivot = 0; | ||
| 30 | const size_t n = pts.size(); | ||
| 31 |
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128 | for (size_t i = 1; i < n; ++i) { |
| 32 |
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104 | if (pts[i].y < pts[pivot].y || (pts[i].y == pts[pivot].y && pts[i].x < pts[pivot].x)) { |
| 33 | pivot = i; | ||
| 34 | } | ||
| 35 | } | ||
| 36 | 24 | return pivot; | |
| 37 | } | ||
| 38 | |||
| 39 | 24 | void GrahamCollinearReduce(std::vector<Point> &pts) { | |
| 40 | size_t m = 1; | ||
| 41 | const size_t n = pts.size(); | ||
| 42 |
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104 | for (size_t i = 2; i < n; ++i) { |
| 43 |
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144 | while (m > 0 && Cross(pts[m - 1], pts[m], pts[i]) == 0) { |
| 44 | --m; | ||
| 45 | } | ||
| 46 | 80 | ++m; | |
| 47 | 80 | pts[m] = pts[i]; | |
| 48 | } | ||
| 49 | 24 | pts.resize(m + 1); | |
| 50 | 24 | } | |
| 51 | |||
| 52 |
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24 | void GrahamScan(std::vector<Point> &pts, Hull &out) { |
| 53 | out.push_back(pts[0]); | ||
| 54 |
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24 | if (pts.size() <= 2) { |
| 55 |
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16 | if (pts.size() == 2) { |
| 56 | out.push_back(pts[1]); | ||
| 57 | } | ||
| 58 | 16 | return; | |
| 59 | } | ||
| 60 | out.push_back(pts[1]); | ||
| 61 |
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24 | for (size_t i = 2; i < pts.size(); ++i) { |
| 62 |
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16 | while (out.size() >= 2 && Cross(out[out.size() - 2], out.back(), pts[i]) <= 0) { |
| 63 | out.pop_back(); | ||
| 64 | } | ||
| 65 | out.push_back(pts[i]); | ||
| 66 | } | ||
| 67 | } | ||
| 68 | |||
| 69 |
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64 | void GrahamHull(std::vector<Point> &pts, Hull &out) { |
| 70 | out.clear(); | ||
| 71 | const size_t n = pts.size(); | ||
| 72 |
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64 | if (n <= 1) { |
| 73 |
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40 | if (n == 1) { |
| 74 | out.push_back(pts[0]); | ||
| 75 | } | ||
| 76 | 40 | return; | |
| 77 | } | ||
| 78 | 24 | const size_t pivot = GrahamFindPivot(pts); | |
| 79 | std::swap(pts[0], pts[pivot]); | ||
| 80 | const Point &p0 = pts[0]; | ||
| 81 | 184 | std::sort(pts.begin() + 1, pts.end(), [&p0](const Point &a, const Point &b) { | |
| 82 | 160 | const int64_t c = Cross(p0, a, b); | |
| 83 |
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160 | if (c != 0) { |
| 84 | 48 | return c > 0; | |
| 85 | } | ||
| 86 | 112 | return DistSq(p0, a) < DistSq(p0, b); | |
| 87 | }); | ||
| 88 | 24 | GrahamCollinearReduce(pts); | |
| 89 | 24 | GrahamScan(pts, out); | |
| 90 | } | ||
| 91 | |||
| 92 | 64 | void FloodFillComponent(const BinaryImage &img, int start_row, int start_col, std::vector<int> &label, | |
| 93 | std::vector<Point> &component_pts) { | ||
| 94 | 64 | const int rows = img.rows; | |
| 95 |
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64 | const int cols = img.cols; |
| 96 | component_pts.clear(); | ||
| 97 | 64 | std::vector<std::pair<int, int>> stack; | |
| 98 |
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64 | stack.emplace_back(start_row, start_col); |
| 99 | 64 | const size_t start_idx = img.Index(start_row, start_col); | |
| 100 | 64 | label[start_idx] = 1; | |
| 101 |
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232 | while (!stack.empty()) { |
| 102 | const auto [cur_r, cur_c] = stack.back(); | ||
| 103 | stack.pop_back(); | ||
| 104 |
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168 | component_pts.push_back(Point{.x = cur_c, .y = cur_r}); |
| 105 |
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840 | for (const auto &[dr, dc] : kFourNeighbors) { |
| 106 | 672 | const int nr = cur_r + dr; | |
| 107 | 672 | const int nc = cur_c + dc; | |
| 108 |
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672 | if (nr < 0 || nr >= rows || nc < 0 || nc >= cols) { |
| 109 | 384 | continue; | |
| 110 | } | ||
| 111 |
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288 | const size_t nidx = (static_cast<size_t>(nr) * static_cast<size_t>(cols)) + static_cast<size_t>(nc); |
| 112 |
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288 | if (img.data[nidx] != 0 && label[nidx] == 0) { |
| 113 | 104 | label[nidx] = 1; | |
| 114 |
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104 | stack.emplace_back(nr, nc); |
| 115 | } | ||
| 116 | } | ||
| 117 | } | ||
| 118 | 64 | } | |
| 119 | |||
| 120 |
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56 | void RunBinaryImageConvexHullSeq(const BinaryImage &img, HullList &hulls) { |
| 121 | hulls.clear(); | ||
| 122 | 56 | const int rows = img.rows; | |
| 123 | 56 | const int cols = img.cols; | |
| 124 | 56 | const size_t total = static_cast<size_t>(rows) * static_cast<size_t>(cols); | |
| 125 | 56 | std::vector<int> label(total, 0); | |
| 126 | 56 | std::vector<Point> component_pts; | |
| 127 |
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56 | component_pts.reserve(total); |
| 128 |
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160 | for (int row = 0; row < rows; ++row) { |
| 129 |
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352 | for (int col = 0; col < cols; ++col) { |
| 130 | const size_t idx = img.Index(row, col); | ||
| 131 |
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248 | if (img.data[idx] == 0 || label[idx] != 0) { |
| 132 | 184 | continue; | |
| 133 | } | ||
| 134 |
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64 | FloodFillComponent(img, row, col, label, component_pts); |
| 135 | 64 | Hull hull; | |
| 136 |
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64 | GrahamHull(component_pts, hull); |
| 137 | hulls.push_back(std::move(hull)); | ||
| 138 | } | ||
| 139 | } | ||
| 140 | 56 | } | |
| 141 | |||
| 142 | } // namespace | ||
| 143 | |||
| 144 |
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56 | KamalaginABinaryImageConvexHullSEQ::KamalaginABinaryImageConvexHullSEQ(const InType &in) { |
| 145 | SetTypeOfTask(GetStaticTypeOfTask()); | ||
| 146 | GetInput() = in; | ||
| 147 | 56 | GetOutput() = HullList{}; | |
| 148 | 56 | } | |
| 149 | |||
| 150 | 56 | bool KamalaginABinaryImageConvexHullSEQ::ValidationImpl() { | |
| 151 | const auto &img = GetInput(); | ||
| 152 |
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56 | if (img.rows < 0 || img.cols < 0) { |
| 153 | return false; | ||
| 154 | } | ||
| 155 |
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56 | if (img.rows == 0 || img.cols == 0) { |
| 156 | 8 | return img.data.empty(); | |
| 157 | } | ||
| 158 |
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48 | if (img.rows > 8192 || img.cols > 8192) { |
| 159 | return false; | ||
| 160 | } | ||
| 161 | 48 | return (static_cast<size_t>(img.rows) * static_cast<size_t>(img.cols)) == img.data.size(); | |
| 162 | } | ||
| 163 | |||
| 164 |
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56 | bool KamalaginABinaryImageConvexHullSEQ::PreProcessingImpl() { |
| 165 | GetOutput().clear(); | ||
| 166 | 56 | return true; | |
| 167 | } | ||
| 168 | |||
| 169 | 56 | bool KamalaginABinaryImageConvexHullSEQ::RunImpl() { | |
| 170 | 56 | RunBinaryImageConvexHullSeq(GetInput(), GetOutput()); | |
| 171 | 56 | return true; | |
| 172 | } | ||
| 173 | |||
| 174 | 56 | bool KamalaginABinaryImageConvexHullSEQ::PostProcessingImpl() { | |
| 175 | 56 | return true; | |
| 176 | } | ||
| 177 | |||
| 178 | } // namespace kamalagin_a_binary_image_convex_hull | ||
| 179 |