Merge pull request #25146 from mshabunin:cpp-contours
Reworked findContours to reduce C-API usage #25146 What is done: * rewritten `findContours` and `icvApproximateChainTC89` using C++ data structures * extracted LINK_RUNS mode to separate new public functions - `findContoursLinkRuns` (it uses completely different algorithm) * ~added new public `cv::approximateChainTC89`~ - **❌ decided to hide it** * enabled chain code output (method = 0, no public enum value for this in C++ yet) * kept old function as `findContours_old` (exported, but not exposed to user) * added more tests for findContours (`test_contours_new.cpp`), some tests compare results of old function with new one. Following tests have been added: * contours of random rectangle * contours of many small (1-2px) blobs * contours of random noise * backport of old accuracy test * separate test for LINK RUNS variant What is left to be done (can be done now or later): * improve tests: * some tests have limited verification (e.g. only verify contour sizes) * perhaps reference data can be collected and stored * maybe more test variants can be added (?) * add enum value for chain code output and a method of returning starting points (e.g. first 8 elements of returned `vector<uchar>` can represent 2 int point coordinates) * add documentation for new functions - **✔️ DONE** * check and improve performance (my experiment showed 0.7x-1.1x some time ago) * remove old functions completely (?) * change contour return order (BFS) or allow to select it (?) * return result tree as-is (?) (new data structures should be exposed, bindings should adapt)pull/25375/head
Maksim Shabunin
1 year ago
committed by
GitHub
parent
e5d530abae
commit
a25132986a
10 changed files with 2417 additions and 3 deletions
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#ifndef OPENCV_IMGPROC_DETAIL_LEGACY_HPP |
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#define OPENCV_IMGPROC_DETAIL_LEGACY_HPP |
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#include "opencv2/imgproc.hpp" |
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namespace cv { |
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#ifdef __OPENCV_BUILD |
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CV_EXPORTS void findContours_legacy(InputArray _image, |
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OutputArrayOfArrays _contours, |
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OutputArray _hierarchy, |
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int mode, |
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int method, |
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Point offset = Point()); |
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CV_EXPORTS void findContours_legacy(InputArray image, |
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OutputArrayOfArrays contours, |
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int mode, |
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int method, |
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Point offset = Point()); |
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#endif |
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} // namespace cv
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#endif // OPENCV_IMGPROC_DETAIL_LEGACY_HPP
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#include "opencv2/core/base.hpp" |
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#include "opencv2/core/types.hpp" |
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#include "opencv2/imgproc.hpp" |
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#include "contours_common.hpp" |
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#include <vector> |
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using namespace std; |
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using namespace cv; |
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namespace { |
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struct ApproxItem |
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{ |
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Point pt; |
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size_t k; // support region
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int s; // 1-curvature
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bool removed; |
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ApproxItem() : k(0), s(0), removed(false) {} |
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ApproxItem(const Point& pt_, int s_) : pt(pt_), k(0), s(s_), removed(false) {} |
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}; |
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static const schar abs_diff[16] = {1, 2, 3, 4, 3, 2, 1, 0, 1, 2, 3, 4, 3, 2, 1}; |
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static const Point chainCodeDeltas[8] = |
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{{1, 0}, {1, -1}, {0, -1}, {-1, -1}, {-1, 0}, {-1, 1}, {0, 1}, {1, 1}}; |
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// Pass 0.
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// Restores all the digital curve points from the chain code.
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// Removes the points (from the resultant polygon)
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// that have zero 1-curvature
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static vector<ApproxItem> pass_0(const vector<schar>& chain, Point pt, bool isApprox, bool isFull) |
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{ |
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vector<ApproxItem> res; |
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const size_t len = chain.size(); |
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res.reserve(len / 2); |
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for (size_t i = 0; i < len; ++i) |
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{ |
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const schar prev = (i == 0) ? chain[len - 1] : chain[i - 1]; |
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const schar cur = chain[i]; |
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const schar s = abs_diff[cur - prev + 7]; |
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if ((!isApprox && (isFull || s != 0)) || isApprox) |
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{ |
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res.push_back(ApproxItem(pt, s)); |
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if (s == 0) |
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(res.end() - 1)->removed = true; |
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} |
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pt += chainCodeDeltas[cur]; |
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} |
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return res; |
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} |
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static vector<Point> gatherPoints(const vector<ApproxItem>& ares) |
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{ |
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vector<Point> res; |
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res.reserve(ares.size() / 2); |
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for (const ApproxItem& item : ares) |
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{ |
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if (item.removed) |
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continue; |
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res.push_back(item.pt); |
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} |
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return res; |
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} |
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static size_t calc_support(const vector<ApproxItem>& ares, size_t i) |
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{ |
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const size_t len = ares.size(); |
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/* determine support region */ |
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int d_num = 0; |
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int l = 0; |
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size_t k = 1; |
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for (;; k++) |
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{ |
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CV_Assert(k <= len); |
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/* calc indices */ |
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const size_t i1 = (i >= k) ? (i - k) : (len - k + i); |
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const size_t i2 = (i + k < len) ? (i + k) : (i + k - len); |
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const int dx = ares[i2].pt.x - ares[i1].pt.x; |
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const int dy = ares[i2].pt.y - ares[i1].pt.y; |
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/* distance between p_(i - k) and p_(i + k) */ |
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const int lk = dx * dx + dy * dy; |
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/* distance between p_i and the line (p_(i-k), p_(i+k)) */ |
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const int dk_num = |
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(ares[i].pt.x - ares[i1].pt.x) * dy - (ares[i].pt.y - ares[i1].pt.y) * dx; |
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union
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{ |
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int i; |
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float f; |
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} d; |
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d.f = (float)(((double)d_num) * lk - ((double)dk_num) * l); |
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if (k > 1 && (l >= lk || ((d_num > 0 && d.i <= 0) || (d_num < 0 && d.i >= 0)))) |
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break; |
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d_num = dk_num; |
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l = lk; |
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} |
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return k - 1; |
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} |
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static int calc_cosine(const vector<ApproxItem>& ares, size_t i) |
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{ |
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const size_t k = ares[i].k; |
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size_t j; |
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int s; |
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const size_t len = ares.size(); |
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/* calc k-cosine curvature */ |
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for (j = k, s = 0; j > 0; j--) |
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{ |
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const size_t i1 = (i >= j) ? (i - j) : (len - j + i); |
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const size_t i2 = (i + j < len) ? (i + j) : (i + j - len); |
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const int dx1 = ares[i1].pt.x - ares[i].pt.x; |
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const int dy1 = ares[i1].pt.y - ares[i].pt.y; |
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const int dx2 = ares[i2].pt.x - ares[i].pt.x; |
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const int dy2 = ares[i2].pt.y - ares[i].pt.y; |
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if ((dx1 | dy1) == 0 || (dx2 | dy2) == 0) |
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break; |
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double temp_num = dx1 * dx2 + dy1 * dy2; |
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temp_num = (float)(temp_num / sqrt(((double)dx1 * dx1 + (double)dy1 * dy1) * |
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((double)dx2 * dx2 + (double)dy2 * dy2))); |
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Cv32suf sk; |
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sk.f = (float)(temp_num + 1.1); |
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CV_Assert(0 <= sk.f && sk.f <= 2.2); |
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if (j < k && sk.i <= s) |
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break; |
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s = sk.i; |
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} |
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return s; |
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} |
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static bool calc_nms_cleanup(const vector<ApproxItem>& ares, size_t i) |
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{ |
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const size_t k2 = ares[i].k >> 1; |
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const int s = ares[i].s; |
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const size_t len = ares.size(); |
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size_t j; |
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for (j = 1; j <= k2; j++) |
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{ |
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const size_t i1 = (i >= j) ? (i - j) : (len - j + i); |
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const size_t i2 = (i + j < len) ? (i + j) : (i + j - len); |
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if (ares[i1].s > s || ares[i2].s > s) |
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break; |
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} |
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return j <= k2; |
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} |
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static bool calc_dominance(const vector<ApproxItem>& ares, size_t i) |
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{ |
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const size_t len = ares.size(); |
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CV_Assert(len > 0); |
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const size_t i1 = (i >= 1) ? (i - 1) : (len - 1 + i); |
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const size_t i2 = (i + 1 < len) ? (i + 1) : (i + 1 - len); |
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return ares[i].s <= ares[i1].s || ares[i].s <= ares[i2].s; |
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} |
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inline size_t get_next_idx(const vector<ApproxItem>& ares, const size_t start) |
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{ |
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const size_t len = ares.size(); |
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size_t res = start + 1; |
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for (; res < len; ++res) |
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{ |
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if (!ares[res].removed) |
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break; |
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} |
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return res; |
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} |
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inline void clear_until(vector<ApproxItem>& ares, const size_t start, const size_t finish) |
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{ |
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const size_t len = ares.size(); |
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for (size_t i = start + 1; i < finish && i < len; ++i) |
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{ |
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ares[i].removed = true; |
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} |
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} |
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static bool calc_new_start(vector<ApproxItem>& ares, size_t& res) |
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{ |
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const size_t len = ares.size(); |
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CV_Assert(len > 0); |
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size_t i1; |
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// remove all previous items from the beginning
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for (i1 = 1; i1 < len && ares[i1].s != 0; i1++) |
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{ |
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ares[i1 - 1].s = 0; |
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} |
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if (i1 == len) |
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{ |
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// all points survived - skip to the end
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return false; |
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} |
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i1--; |
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size_t i2; |
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// remove all following items from the end
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for (i2 = len - 2; i2 > 0 && ares[i2].s != 0; i2--) |
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{ |
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clear_until(ares, i2, len); |
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ares[i2 + 1].s = 0; |
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} |
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i2++; |
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// only two points left
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if (i1 == 0 && i2 == len - 1) |
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{ |
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// find first non-removed element from the start
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i1 = get_next_idx(ares, 0); |
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// append first item to the end
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ares.push_back(ares[0]); |
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(ares.end() - 1)->removed = false; |
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} |
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res = i1; |
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return true; |
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} |
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static void pass_cleanup(vector<ApproxItem>& ares, size_t start_idx) |
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{ |
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int count = 1; |
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const size_t len = ares.size(); |
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size_t first = start_idx; |
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for (size_t i = start_idx, prev = i; i < len; ++i) |
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{ |
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ApproxItem& item = ares[i]; |
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if (item.removed) |
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continue; |
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size_t next_idx = get_next_idx(ares, i); |
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if (next_idx == len || next_idx - i != 1) |
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{ |
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if (count >= 2) |
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{ |
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if (count == 2) |
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{ |
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const int s1 = ares[prev].s; |
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const int s2 = ares[i].s; |
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if (s1 > s2 || (s1 == s2 && ares[prev].k <= ares[i].k)) |
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/* remove second */ |
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clear_until(ares, get_next_idx(ares, prev), get_next_idx(ares, i)); |
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else |
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/* remove first */ |
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clear_until(ares, first, i); |
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} |
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else |
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{ |
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first = get_next_idx(ares, first); |
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clear_until(ares, first, i); |
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} |
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} |
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clear_until(ares, first, i); |
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first = i; |
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count = 1; |
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} |
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else |
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{ |
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++count; |
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} |
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prev = i; |
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} |
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} |
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} // namespace
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vector<Point> cv::approximateChainTC89(vector<schar> chain, const Point& origin, const int method) |
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{ |
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if (chain.size() == 0) |
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{ |
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return vector<Point>({origin}); |
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} |
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const bool isApprox = method == CHAIN_APPROX_TC89_L1 || method == CHAIN_APPROX_TC89_KCOS; |
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ApproxItem root; |
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vector<ApproxItem> ares = pass_0(chain, origin, isApprox, method == CHAIN_APPROX_NONE); |
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if (isApprox) |
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{ |
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CV_DbgAssert(ares.size() < (size_t)numeric_limits<int>::max()); |
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// Pass 1.
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// Determines support region for all the remained points */
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for (size_t i = 0; i < ares.size(); ++i) |
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{ |
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ApproxItem& item = ares[i]; |
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if (item.removed) |
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continue; |
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item.k = calc_support(ares, i); |
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if (method == CHAIN_APPROX_TC89_KCOS) |
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item.s = calc_cosine(ares, i); |
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} |
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// Pass 2.
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// Performs non-maxima suppression
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for (size_t i = 0; i < ares.size(); ++i) |
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{ |
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ApproxItem& item = ares[i]; |
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if (calc_nms_cleanup(ares, i)) |
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{ |
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item.s = 0; // "clear"
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item.removed = true; |
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} |
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} |
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// Pass 3.
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// Removes non-dominant points with 1-length support region */
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for (size_t i = 0; i < ares.size(); ++i) |
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{ |
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ApproxItem& item = ares[i]; |
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if (item.removed) |
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continue; |
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if (item.k == 1 && calc_dominance(ares, i)) |
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{ |
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item.s = 0; |
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item.removed = true; |
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} |
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} |
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if (method == cv::CHAIN_APPROX_TC89_L1) |
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{ |
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// Pass 4.
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// Cleans remained couples of points
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bool skip = false; |
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size_t new_start_idx = 0; |
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const size_t len = ares.size(); |
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if (ares[0].s != 0 && ares[len - 1].s != 0) |
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{ |
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if (!calc_new_start(ares, new_start_idx)) |
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{ |
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skip = true; |
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} |
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} |
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if (!skip) |
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{ |
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pass_cleanup(ares, new_start_idx); |
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} |
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} |
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} |
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return gatherPoints(ares); |
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} |
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#include "precomp.hpp" |
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#include "contours_common.hpp" |
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#include <map> |
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#include <limits> |
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using namespace std; |
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using namespace cv; |
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void cv::contourTreeToResults(CTree& tree, |
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int res_type, |
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OutputArrayOfArrays& _contours, |
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OutputArray& _hierarchy) |
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{ |
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// check if there are no results
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if (tree.isEmpty() || (tree.elem(0).body.isEmpty() && (tree.elem(0).first_child == -1))) |
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{ |
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_contours.clear(); |
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return; |
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} |
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// mapping for indexes (original -> resulting)
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map<int, int> index_mapping; |
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index_mapping[-1] = -1; |
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index_mapping[0] = -1; |
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CV_Assert(tree.size() < (size_t)numeric_limits<int>::max()); |
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const int total = (int)tree.size() - 1; |
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_contours.create(total, 1, 0, -1, true); |
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{ |
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int i = 0; |
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CIterator it(tree); |
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while (!it.isDone()) |
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{ |
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const CNode& elem = it.getNext_s(); |
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CV_Assert(elem.self() != -1); |
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if (elem.self() == 0) |
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continue; |
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index_mapping[elem.self()] = i; |
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CV_Assert(elem.body.size() < (size_t)numeric_limits<int>::max()); |
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const int sz = (int)elem.body.size(); |
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_contours.create(sz, 1, res_type, i, true); |
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if (sz > 0) |
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{ |
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Mat cmat = _contours.getMat(i); |
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CV_Assert(cmat.isContinuous()); |
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elem.body.copyTo(cmat.data); |
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} |
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++i; |
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} |
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} |
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if (_hierarchy.needed()) |
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{ |
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_hierarchy.create(1, total, CV_32SC4, -1, true); |
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Mat h_mat = _hierarchy.getMat(); |
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int i = 0; |
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CIterator it(tree); |
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while (!it.isDone()) |
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{ |
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const CNode& elem = it.getNext_s(); |
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if (elem.self() == 0) |
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continue; |
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Vec4i& h_vec = h_mat.at<Vec4i>(i); |
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h_vec = Vec4i(index_mapping.at(elem.next), |
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index_mapping.at(elem.prev), |
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index_mapping.at(elem.first_child), |
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index_mapping.at(elem.parent)); |
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++i; |
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} |
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} |
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} |
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@ -0,0 +1,219 @@ |
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#ifndef OPENCV_CONTOURS_COMMON_HPP |
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#define OPENCV_CONTOURS_COMMON_HPP |
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#include "precomp.hpp" |
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#include <stack> |
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namespace cv { |
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static const schar MAX_SIZE = 16; |
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static const cv::Point chainCodeDeltas[8] = |
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{{1, 0}, {1, -1}, {0, -1}, {-1, -1}, {-1, 0}, {-1, 1}, {0, 1}, {1, 1}}; |
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static inline int getDelta(schar s, size_t step) |
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{ |
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CV_DbgAssert(s >= 0 && s < 16); |
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const cv::Point res = chainCodeDeltas[s % 8]; |
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return res.x + res.y * (int)step; |
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} |
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inline schar clamp_direction(schar dir) |
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{ |
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return std::min(dir, (schar)15); |
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} |
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template <typename T> |
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class TreeNode |
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{ |
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private: |
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int self_; |
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public: |
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// tree hierarchy (parent - children)
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int parent; |
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int first_child; |
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// 1st linked list - bidirectional - sibling children
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int prev; |
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int next; |
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// 2nd linked list - unidirectional - not related to 1st list
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int ctable_next; |
||||
T body; |
||||
|
||||
public: |
||||
TreeNode(int self) : |
||||
self_(self), parent(-1), first_child(-1), prev(-1), next(-1), ctable_next(-1) |
||||
{ |
||||
CV_Assert(self >= 0); |
||||
} |
||||
int self() const |
||||
{ |
||||
return self_; |
||||
} |
||||
}; |
||||
|
||||
template <typename T> |
||||
class Tree |
||||
{ |
||||
private: |
||||
std::vector<TreeNode<T>> nodes; |
||||
|
||||
public: |
||||
TreeNode<T>& newElem() |
||||
{ |
||||
const size_t idx = nodes.size(); |
||||
CV_DbgAssert(idx < (size_t)std::numeric_limits<int>::max()); |
||||
nodes.push_back(TreeNode<T>((int)idx)); |
||||
return nodes[idx]; |
||||
} |
||||
TreeNode<T>& elem(int idx) |
||||
{ |
||||
CV_DbgAssert(idx >= 0 && (size_t)idx < nodes.size()); |
||||
return nodes[(size_t)idx]; |
||||
} |
||||
const TreeNode<T>& elem(int idx) const |
||||
{ |
||||
CV_DbgAssert(idx >= 0 && (size_t)idx < nodes.size()); |
||||
return nodes[(size_t)idx]; |
||||
} |
||||
int lastSibling(int e) const |
||||
{ |
||||
if (e != -1) |
||||
{ |
||||
while (true) |
||||
{ |
||||
const TreeNode<T>& cur_elem = elem(e); |
||||
if (cur_elem.next == -1) |
||||
break; |
||||
e = cur_elem.next; |
||||
} |
||||
} |
||||
return e; |
||||
} |
||||
void addSiblingAfter(int prev, int idx) |
||||
{ |
||||
TreeNode<T>& prev_item = nodes[prev]; |
||||
TreeNode<T>& child = nodes[idx]; |
||||
child.parent = prev_item.parent; |
||||
if (prev_item.next != -1) |
||||
{ |
||||
nodes[prev_item.next].prev = idx; |
||||
child.next = prev_item.next; |
||||
} |
||||
child.prev = prev; |
||||
prev_item.next = idx; |
||||
} |
||||
void addChild(int parent_idx, int child_idx) |
||||
{ |
||||
TreeNode<T>& parent = nodes[parent_idx]; |
||||
TreeNode<T>& child = nodes[child_idx]; |
||||
if (parent.first_child != -1) |
||||
{ |
||||
TreeNode<T>& fchild_ = nodes[parent.first_child]; |
||||
fchild_.prev = child_idx; |
||||
child.next = parent.first_child; |
||||
} |
||||
parent.first_child = child_idx; |
||||
child.parent = parent_idx; |
||||
child.prev = -1; |
||||
} |
||||
bool isEmpty() const |
||||
{ |
||||
return nodes.size() == 0; |
||||
} |
||||
size_t size() const |
||||
{ |
||||
return nodes.size(); |
||||
} |
||||
}; |
||||
|
||||
template <typename T> |
||||
class TreeIterator |
||||
{ |
||||
public: |
||||
TreeIterator(Tree<T>& tree_) : tree(tree_) |
||||
{ |
||||
CV_Assert(!tree.isEmpty()); |
||||
levels.push(0); |
||||
} |
||||
bool isDone() const |
||||
{ |
||||
return levels.empty(); |
||||
} |
||||
const TreeNode<T>& getNext_s() |
||||
{ |
||||
int idx = levels.top(); |
||||
levels.pop(); |
||||
const TreeNode<T>& res = tree.elem(idx); |
||||
int cur = tree.lastSibling(res.first_child); |
||||
while (cur != -1) |
||||
{ |
||||
levels.push(cur); |
||||
cur = tree.elem(cur).prev; |
||||
} |
||||
return res; |
||||
} |
||||
|
||||
private: |
||||
std::stack<int> levels; |
||||
Tree<T>& tree; |
||||
}; |
||||
|
||||
//==============================================================================
|
||||
|
||||
class Contour |
||||
{ |
||||
public: |
||||
cv::Rect brect; |
||||
cv::Point origin; |
||||
std::vector<cv::Point> pts; |
||||
std::vector<schar> codes; |
||||
bool isHole; |
||||
bool isChain; |
||||
|
||||
Contour() : isHole(false), isChain(false) {} |
||||
void updateBoundingRect() {} |
||||
bool isEmpty() const |
||||
{ |
||||
return pts.size() == 0 && codes.size() == 0; |
||||
} |
||||
size_t size() const |
||||
{ |
||||
return isChain ? codes.size() : pts.size(); |
||||
} |
||||
void copyTo(void* data) const |
||||
{ |
||||
// NOTE: Mat::copyTo doesn't work because it creates new Mat object
|
||||
// instead of reusing existing vector data
|
||||
if (isChain) |
||||
{ |
||||
memcpy(data, &codes[0], codes.size() * sizeof(codes[0])); |
||||
} |
||||
else |
||||
{ |
||||
memcpy(data, &pts[0], pts.size() * sizeof(pts[0])); |
||||
} |
||||
} |
||||
}; |
||||
|
||||
typedef TreeNode<Contour> CNode; |
||||
typedef Tree<Contour> CTree; |
||||
typedef TreeIterator<Contour> CIterator; |
||||
|
||||
|
||||
void contourTreeToResults(CTree& tree, |
||||
int res_type, |
||||
cv::OutputArrayOfArrays& _contours, |
||||
cv::OutputArray& _hierarchy); |
||||
|
||||
|
||||
std::vector<Point> |
||||
approximateChainTC89(std::vector<schar> chain, const Point& origin, const int method); |
||||
|
||||
} // namespace cv
|
||||
|
||||
#endif // OPENCV_CONTOURS_COMMON_HPP
|
||||
@ -0,0 +1,417 @@ |
||||
// This file is part of OpenCV project.
|
||||
// It is subject to the license terms in the LICENSE file found in the top-level directory
|
||||
// of this distribution and at http://opencv.org/license.html
|
||||
|
||||
#include "precomp.hpp" |
||||
#include "contours_common.hpp" |
||||
#include "opencv2/core/hal/intrin.hpp" |
||||
|
||||
using namespace cv; |
||||
using namespace std; |
||||
|
||||
//==============================================================================
|
||||
|
||||
namespace { |
||||
|
||||
inline static int findStartContourPoint(uchar* src_data, Size img_size, int j) |
||||
{ |
||||
#if (CV_SIMD || CV_SIMD_SCALABLE) |
||||
v_uint8 v_zero = vx_setzero_u8(); |
||||
for (; j <= img_size.width - VTraits<v_uint8>::vlanes(); j += VTraits<v_uint8>::vlanes()) |
||||
{ |
||||
v_uint8 vmask = (v_ne(vx_load((uchar*)(src_data + j)), v_zero)); |
||||
if (v_check_any(vmask)) |
||||
{ |
||||
j += v_scan_forward(vmask); |
||||
return j; |
||||
} |
||||
} |
||||
#endif |
||||
for (; j < img_size.width && !src_data[j]; ++j) |
||||
; |
||||
return j; |
||||
} |
||||
|
||||
inline static int findEndContourPoint(uchar* src_data, Size img_size, int j) |
||||
{ |
||||
#if (CV_SIMD || CV_SIMD_SCALABLE) |
||||
if (j < img_size.width && !src_data[j]) |
||||
{ |
||||
return j; |
||||
} |
||||
else |
||||
{ |
||||
v_uint8 v_zero = vx_setzero_u8(); |
||||
for (; j <= img_size.width - VTraits<v_uint8>::vlanes(); j += VTraits<v_uint8>::vlanes()) |
||||
{ |
||||
v_uint8 vmask = (v_eq(vx_load((uchar*)(src_data + j)), v_zero)); |
||||
if (v_check_any(vmask)) |
||||
{ |
||||
j += v_scan_forward(vmask); |
||||
return j; |
||||
} |
||||
} |
||||
} |
||||
#endif |
||||
for (; j < img_size.width && src_data[j]; ++j) |
||||
; |
||||
|
||||
return j; |
||||
} |
||||
|
||||
//==============================================================================
|
||||
|
||||
struct LinkRunPoint |
||||
{ |
||||
int link; |
||||
int next; |
||||
Point pt; |
||||
LinkRunPoint() : link(-1), next(-1) {} |
||||
LinkRunPoint(const Point& pt_) : link(-1), next(-1), pt(pt_) {} |
||||
}; |
||||
|
||||
typedef LinkRunPoint LRP; |
||||
|
||||
//==============================================================================
|
||||
|
||||
class LinkRunner |
||||
{ |
||||
public: |
||||
enum LinkConnectionDirection |
||||
{ |
||||
ICV_SINGLE = 0, |
||||
ICV_CONNECTING_ABOVE = 1, |
||||
ICV_CONNECTING_BELOW = -1, |
||||
}; |
||||
|
||||
CTree tree; |
||||
|
||||
vector<LRP> rns; |
||||
vector<int> ext_rns; |
||||
vector<int> int_rns; |
||||
|
||||
public: |
||||
LinkRunner() |
||||
{ |
||||
tree.newElem(); |
||||
rns.reserve(100); |
||||
} |
||||
void process(Mat& image); |
||||
void convertLinks(int& first, int& prev, bool isHole); |
||||
void establishLinks(int& prev_point, |
||||
int upper_run, |
||||
int lower_run, |
||||
const int upper_total, |
||||
const int lower_total); |
||||
}; |
||||
|
||||
void LinkRunner::convertLinks(int& first, int& prev, bool isHole) |
||||
{ |
||||
const vector<int>& contours = isHole ? int_rns : ext_rns; |
||||
int count = 0; |
||||
for (int j = 0; j < (int)contours.size(); j++, count++) |
||||
{ |
||||
int start = contours[j]; |
||||
int cur = start; |
||||
|
||||
if (rns[cur].link == -1) |
||||
continue; |
||||
|
||||
CNode& node = tree.newElem(); |
||||
node.body.isHole = isHole; |
||||
|
||||
do |
||||
{ |
||||
node.body.pts.push_back(rns[cur].pt); |
||||
int p_temp = cur; |
||||
cur = rns[cur].link; |
||||
rns[p_temp].link = -1; |
||||
} |
||||
while (cur != start); |
||||
|
||||
if (first == 0) |
||||
{ |
||||
tree.addChild(0, node.self()); |
||||
prev = first = node.self(); |
||||
} |
||||
else |
||||
{ |
||||
tree.addSiblingAfter(prev, node.self()); |
||||
prev = node.self(); |
||||
} |
||||
} |
||||
} |
||||
void LinkRunner::establishLinks(int& prev_point, |
||||
int upper_run, |
||||
int lower_run, |
||||
const int upper_total, |
||||
const int lower_total) |
||||
{ |
||||
int k, n; |
||||
int connect_flag = ICV_SINGLE; |
||||
for (k = 0, n = 0; k < upper_total / 2 && n < lower_total / 2;) |
||||
{ |
||||
switch (connect_flag) |
||||
{ |
||||
case ICV_SINGLE: |
||||
if (rns[rns[upper_run].next].pt.x < rns[rns[lower_run].next].pt.x) |
||||
{ |
||||
if (rns[rns[upper_run].next].pt.x >= rns[lower_run].pt.x - 1) |
||||
{ |
||||
rns[lower_run].link = upper_run; |
||||
connect_flag = ICV_CONNECTING_ABOVE; |
||||
prev_point = rns[upper_run].next; |
||||
} |
||||
else |
||||
rns[rns[upper_run].next].link = upper_run; |
||||
k++; |
||||
upper_run = rns[rns[upper_run].next].next; |
||||
} |
||||
else |
||||
{ |
||||
if (rns[upper_run].pt.x <= rns[rns[lower_run].next].pt.x + 1) |
||||
{ |
||||
rns[lower_run].link = upper_run; |
||||
connect_flag = ICV_CONNECTING_BELOW; |
||||
prev_point = rns[lower_run].next; |
||||
} |
||||
else |
||||
{ |
||||
rns[lower_run].link = rns[lower_run].next; |
||||
// First point of contour
|
||||
ext_rns.push_back(lower_run); |
||||
} |
||||
n++; |
||||
lower_run = rns[rns[lower_run].next].next; |
||||
} |
||||
break; |
||||
case ICV_CONNECTING_ABOVE: |
||||
if (rns[upper_run].pt.x > rns[rns[lower_run].next].pt.x + 1) |
||||
{ |
||||
rns[prev_point].link = rns[lower_run].next; |
||||
connect_flag = ICV_SINGLE; |
||||
n++; |
||||
lower_run = rns[rns[lower_run].next].next; |
||||
} |
||||
else |
||||
{ |
||||
rns[prev_point].link = upper_run; |
||||
if (rns[rns[upper_run].next].pt.x < rns[rns[lower_run].next].pt.x) |
||||
{ |
||||
k++; |
||||
prev_point = rns[upper_run].next; |
||||
upper_run = rns[rns[upper_run].next].next; |
||||
} |
||||
else |
||||
{ |
||||
connect_flag = ICV_CONNECTING_BELOW; |
||||
prev_point = rns[lower_run].next; |
||||
n++; |
||||
lower_run = rns[rns[lower_run].next].next; |
||||
} |
||||
} |
||||
break; |
||||
case ICV_CONNECTING_BELOW: |
||||
if (rns[lower_run].pt.x > rns[rns[upper_run].next].pt.x + 1) |
||||
{ |
||||
rns[rns[upper_run].next].link = prev_point; |
||||
connect_flag = ICV_SINGLE; |
||||
k++; |
||||
upper_run = rns[rns[upper_run].next].next; |
||||
} |
||||
else |
||||
{ |
||||
// First point of contour
|
||||
int_rns.push_back(lower_run); |
||||
|
||||
rns[lower_run].link = prev_point; |
||||
if (rns[rns[lower_run].next].pt.x < rns[rns[upper_run].next].pt.x) |
||||
{ |
||||
n++; |
||||
prev_point = rns[lower_run].next; |
||||
lower_run = rns[rns[lower_run].next].next; |
||||
} |
||||
else |
||||
{ |
||||
connect_flag = ICV_CONNECTING_ABOVE; |
||||
k++; |
||||
prev_point = rns[upper_run].next; |
||||
upper_run = rns[rns[upper_run].next].next; |
||||
} |
||||
} |
||||
break; |
||||
} |
||||
} // k, n
|
||||
|
||||
for (; n < lower_total / 2; n++) |
||||
{ |
||||
if (connect_flag != ICV_SINGLE) |
||||
{ |
||||
rns[prev_point].link = rns[lower_run].next; |
||||
connect_flag = ICV_SINGLE; |
||||
lower_run = rns[rns[lower_run].next].next; |
||||
continue; |
||||
} |
||||
rns[rns[lower_run].next] = rns[rns[lower_run].next]; |
||||
rns[lower_run].link = rns[lower_run].next; |
||||
|
||||
// First point of contour
|
||||
ext_rns.push_back(lower_run); |
||||
lower_run = rns[rns[lower_run].next].next; |
||||
} |
||||
|
||||
for (; k < upper_total / 2; k++) |
||||
{ |
||||
if (connect_flag != ICV_SINGLE) |
||||
{ |
||||
rns[rns[upper_run].next].link = prev_point; |
||||
connect_flag = ICV_SINGLE; |
||||
upper_run = rns[rns[upper_run].next].next; |
||||
continue; |
||||
} |
||||
rns[rns[upper_run].next] = rns[rns[upper_run].next]; |
||||
rns[rns[upper_run].next].link = upper_run; |
||||
upper_run = rns[rns[upper_run].next].next; |
||||
} |
||||
} |
||||
|
||||
|
||||
void LinkRunner::process(Mat& image) |
||||
{ |
||||
const Size sz = image.size(); |
||||
int j; |
||||
int lower_total; |
||||
int upper_total; |
||||
int all_total; |
||||
|
||||
Point cur_point; |
||||
|
||||
rns.reserve(sz.height); // optimization, assuming some contours exist
|
||||
|
||||
// First line. None of runs is binded
|
||||
rns.push_back(LRP()); |
||||
int upper_line = (int)rns.size() - 1; |
||||
int cur = upper_line; |
||||
for (j = 0; j < sz.width;) |
||||
{ |
||||
j = findStartContourPoint(image.ptr<uchar>(), sz, j); |
||||
|
||||
if (j == sz.width) |
||||
break; |
||||
|
||||
cur_point.x = j; |
||||
|
||||
rns.push_back(LRP(cur_point)); |
||||
rns[cur].next = (int)rns.size() - 1; |
||||
cur = rns[cur].next; |
||||
|
||||
j = findEndContourPoint(image.ptr<uchar>(), sz, j + 1); |
||||
|
||||
cur_point.x = j - 1; |
||||
|
||||
rns.push_back(LRP(cur_point)); |
||||
rns[cur].next = (int)rns.size() - 1; |
||||
rns[cur].link = rns[cur].next; |
||||
|
||||
// First point of contour
|
||||
ext_rns.push_back(cur); |
||||
cur = rns[cur].next; |
||||
} |
||||
upper_line = rns[upper_line].next; |
||||
upper_total = (int)rns.size() - 1; // runs->total - 1;
|
||||
|
||||
int last_elem = cur; |
||||
rns[cur].next = -1; |
||||
int prev_point = -1; |
||||
int lower_line = -1; |
||||
for (int i = 1; i < sz.height; i++) |
||||
{ |
||||
// Find runs in next line
|
||||
cur_point.y = i; |
||||
all_total = (int)rns.size(); // runs->total;
|
||||
for (j = 0; j < sz.width;) |
||||
{ |
||||
j = findStartContourPoint(image.ptr<uchar>(i), sz, j); |
||||
|
||||
if (j == sz.width) |
||||
break; |
||||
|
||||
cur_point.x = j; |
||||
|
||||
rns.push_back(LRP(cur_point)); |
||||
rns[cur].next = (int)rns.size() - 1; |
||||
cur = rns[cur].next; |
||||
|
||||
j = findEndContourPoint(image.ptr<uchar>(i), sz, j + 1); |
||||
|
||||
cur_point.x = j - 1; |
||||
rns.push_back(LRP(cur_point)); |
||||
cur = rns[cur].next = (int)rns.size() - 1; |
||||
} // j
|
||||
lower_line = rns[last_elem].next; |
||||
lower_total = (int)rns.size() - all_total; // runs->total - all_total;
|
||||
last_elem = cur; |
||||
rns[cur].next = -1; |
||||
|
||||
CV_DbgAssert(rns.size() < (size_t)numeric_limits<int>::max()); |
||||
|
||||
// Find links between runs of lower_line and upper_line
|
||||
establishLinks(prev_point, upper_line, lower_line, upper_total, lower_total); |
||||
|
||||
upper_line = lower_line; |
||||
upper_total = lower_total; |
||||
} // i
|
||||
|
||||
// the last line of image
|
||||
int upper_run = upper_line; |
||||
for (int k = 0; k < upper_total / 2; k++) |
||||
{ |
||||
rns[rns[upper_run].next].link = upper_run; |
||||
upper_run = rns[rns[upper_run].next].next; |
||||
} |
||||
|
||||
int first = 0; |
||||
int prev = 0; |
||||
convertLinks(first, prev, false); |
||||
convertLinks(first, prev, true); |
||||
} |
||||
|
||||
} // namespace
|
||||
|
||||
//==============================================================================
|
||||
|
||||
void cv::findContoursLinkRuns(InputArray _image, |
||||
OutputArrayOfArrays _contours, |
||||
OutputArray _hierarchy) |
||||
{ |
||||
CV_INSTRUMENT_REGION(); |
||||
|
||||
CV_CheckType(_image.type(), |
||||
_image.type() == CV_8UC1 || _image.type() == CV_8SC1, |
||||
"Bad input image type, must be CV_8UC1 or CV_8SC1"); |
||||
|
||||
// Sanity check: output must be of type vector<vector<Point>>
|
||||
CV_Assert(_contours.kind() == _InputArray::STD_VECTOR_VECTOR || |
||||
_contours.kind() == _InputArray::STD_VECTOR_MAT || |
||||
_contours.kind() == _InputArray::STD_VECTOR_UMAT); |
||||
|
||||
if (!_contours.empty()) |
||||
CV_CheckTypeEQ(_contours.type(), CV_32SC2, "Contours must have type CV_32SC2"); |
||||
|
||||
if (_hierarchy.needed()) |
||||
_hierarchy.clear(); |
||||
|
||||
Mat image = _image.getMat(); |
||||
|
||||
LinkRunner runner; |
||||
runner.process(image); |
||||
|
||||
contourTreeToResults(runner.tree, CV_32SC2, _contours, _hierarchy); |
||||
} |
||||
|
||||
|
||||
void cv::findContoursLinkRuns(InputArray _image, OutputArrayOfArrays _contours) |
||||
{ |
||||
CV_INSTRUMENT_REGION(); |
||||
findContoursLinkRuns(_image, _contours, noArray()); |
||||
} |
||||
@ -0,0 +1,697 @@ |
||||
// This file is part of OpenCV project.
|
||||
// It is subject to the license terms in the LICENSE file found in the top-level directory
|
||||
// of this distribution and at http://opencv.org/license.html
|
||||
|
||||
#include "opencv2/imgproc.hpp" |
||||
#include "precomp.hpp" |
||||
#include "opencv2/core/hal/intrin.hpp" |
||||
#include "opencv2/core/check.hpp" |
||||
#include "opencv2/core/utils/logger.hpp" |
||||
#include <iostream> |
||||
#include <array> |
||||
#include <limits> |
||||
#include <map> |
||||
|
||||
#include "contours_common.hpp" |
||||
|
||||
using namespace std; |
||||
using namespace cv; |
||||
|
||||
//==============================================================================
|
||||
|
||||
namespace { |
||||
|
||||
template <typename T> |
||||
struct Trait |
||||
{ |
||||
}; |
||||
|
||||
static const schar MASK8_RIGHT = '\x80'; // 1000 0000
|
||||
static const schar MASK8_NEW = '\x02'; // 0000 0010 (+2)
|
||||
static const schar MASK8_FLAGS = '\xFE'; // 1111 1110 (-2)
|
||||
static const schar MASK8_BLACK = '\x01'; // 0000 0001 - black pixel
|
||||
|
||||
static const schar MASK8_LVAL = '\x7F'; // 0111 1111 (for table)
|
||||
|
||||
template <> |
||||
struct Trait<schar> |
||||
{ |
||||
static inline bool checkValue(const schar* elem, const schar*) |
||||
{ |
||||
return *elem != 0; |
||||
} |
||||
static inline bool isVal(const schar* elem, const schar*) |
||||
{ |
||||
return *elem == MASK8_BLACK; |
||||
} |
||||
static inline bool isRight(const schar* elem, const schar*) |
||||
{ |
||||
return (*elem & MASK8_RIGHT) != 0; |
||||
} |
||||
static inline void setRightFlag(schar* elem, const schar*, schar nbd) |
||||
{ |
||||
*elem = nbd | MASK8_RIGHT; |
||||
} |
||||
static inline void setNewFlag(schar* elem, const schar*, schar nbd) |
||||
{ |
||||
*elem = nbd; |
||||
} |
||||
}; |
||||
|
||||
static const int MASK_RIGHT = 0x80000000; // 100..000
|
||||
static const int MASK_NEW = 0x40000000; // 010..000
|
||||
static const int MASK_FLAGS = 0xC0000000; // right + new
|
||||
static const int MASK_VAL = 0x3FFFFFFF; // ~flags - pixel label
|
||||
|
||||
template <> |
||||
struct Trait<int> |
||||
{ |
||||
static inline bool checkValue(const int* elem, const int* elem0) |
||||
{ |
||||
return (*elem & MASK_VAL) == (*elem0 & MASK_VAL); |
||||
} |
||||
static inline bool isVal(const int* elem, const int* elem0) |
||||
{ |
||||
return *elem == (*elem0 & MASK_VAL); |
||||
} |
||||
static inline bool isRight(const int* elem, const int* elem0) |
||||
{ |
||||
return (*elem & MASK_RIGHT) == (*elem0 & MASK8_RIGHT); |
||||
} |
||||
static inline void setRightFlag(int* elem, const int* elem0, int) |
||||
{ |
||||
*elem = (*elem0 & MASK_VAL) | MASK_NEW | MASK_RIGHT; |
||||
} |
||||
static inline void setNewFlag(int* elem, const int* elem0, int) |
||||
{ |
||||
*elem = (*elem0 & MASK_VAL) | MASK_NEW; |
||||
} |
||||
}; |
||||
|
||||
} // namespace
|
||||
|
||||
|
||||
//==============================================================================
|
||||
|
||||
|
||||
namespace { |
||||
|
||||
template <typename T> |
||||
static bool icvTraceContour(Mat& image, const Point& start, const Point& end, bool isHole) |
||||
{ |
||||
const T* stop_ptr = image.ptr<T>(end.y, end.x); |
||||
const size_t step = image.step1(); |
||||
const T *i0 = image.ptr<T>(start.y, start.x), *i1, *i3, *i4 = NULL; |
||||
const schar s_end = isHole ? 0 : 4; |
||||
|
||||
schar s = s_end; |
||||
do |
||||
{ |
||||
s = (s - 1) & 7; |
||||
i1 = i0 + getDelta(s, step); |
||||
} |
||||
while (!Trait<T>::checkValue(i1, i0) && s != s_end); |
||||
|
||||
i3 = i0; |
||||
|
||||
// check single pixel domain
|
||||
if (s != s_end) |
||||
{ |
||||
// follow border
|
||||
for (;;) |
||||
{ |
||||
CV_Assert(i3 != NULL); |
||||
s = clamp_direction(s); |
||||
while (s < MAX_SIZE - 1) |
||||
{ |
||||
++s; |
||||
i4 = i3 + getDelta(s, step); |
||||
CV_Assert(i4 != NULL); |
||||
if (Trait<T>::checkValue(i4, i0)) |
||||
break; |
||||
} |
||||
|
||||
if (i3 == stop_ptr) |
||||
{ |
||||
if (!Trait<T>::isRight(i3, i0)) |
||||
{ |
||||
// it's the only contour
|
||||
return true; |
||||
} |
||||
|
||||
// check if this is the last contour
|
||||
// encountered during a raster scan
|
||||
const T* i5; |
||||
schar t = s; |
||||
while (true) |
||||
{ |
||||
t = (t - 1) & 7; |
||||
i5 = i3 + getDelta(t, step); |
||||
if (*i5 != 0) |
||||
break; |
||||
if (t == 0) |
||||
return true; |
||||
} |
||||
} |
||||
|
||||
if ((i4 == i0 && i3 == i1)) |
||||
break; |
||||
|
||||
i3 = i4; |
||||
s = (s + 4) & 7; |
||||
} // end of border following loop
|
||||
} |
||||
else |
||||
{ |
||||
return i3 == stop_ptr; |
||||
} |
||||
|
||||
return false; |
||||
} |
||||
|
||||
template <typename T> |
||||
static void icvFetchContourEx(Mat& image, |
||||
const Point& start, |
||||
T nbd, |
||||
Contour& res_contour, |
||||
const bool isDirect) |
||||
{ |
||||
const size_t step = image.step1(); |
||||
T *i0 = image.ptr<T>(start.y, start.x), *i1, *i3, *i4 = NULL; |
||||
|
||||
Point pt = res_contour.origin; |
||||
|
||||
cv::Rect rect(pt.x, pt.y, pt.x, pt.y); |
||||
|
||||
schar s_end = res_contour.isHole ? 0 : 4; |
||||
schar s = s_end; |
||||
do |
||||
{ |
||||
s = (s - 1) & 7; |
||||
i1 = i0 + getDelta(s, step); |
||||
} |
||||
while (!Trait<T>::checkValue(i1, i0) && s != s_end); |
||||
|
||||
if (s == s_end) |
||||
{ |
||||
Trait<T>::setRightFlag(i0, i0, nbd); |
||||
if (!res_contour.isChain) |
||||
{ |
||||
res_contour.pts.push_back(pt); |
||||
} |
||||
} |
||||
else |
||||
{ |
||||
i3 = i0; |
||||
schar prev_s = s ^ 4; |
||||
|
||||
// follow border
|
||||
for (;;) |
||||
{ |
||||
s_end = s; |
||||
s = clamp_direction(s); |
||||
while (s < MAX_SIZE - 1) |
||||
{ |
||||
++s; |
||||
i4 = i3 + getDelta(s, step); |
||||
CV_Assert(i4 != NULL); |
||||
if (Trait<T>::checkValue(i4, i0)) |
||||
break; |
||||
} |
||||
s &= 7; |
||||
|
||||
// check "right" bound
|
||||
if ((unsigned)(s - 1) < (unsigned)s_end) |
||||
{ |
||||
Trait<T>::setRightFlag(i3, i0, nbd); |
||||
} |
||||
else if (Trait<T>::isVal(i3, i0)) |
||||
{ |
||||
Trait<T>::setNewFlag(i3, i0, nbd); |
||||
} |
||||
|
||||
if (res_contour.isChain) |
||||
{ |
||||
res_contour.codes.push_back(s); |
||||
} |
||||
else if (s != prev_s || isDirect) |
||||
{ |
||||
res_contour.pts.push_back(pt); |
||||
} |
||||
|
||||
if (s != prev_s) |
||||
{ |
||||
// update bounds
|
||||
if (pt.x < rect.x) |
||||
rect.x = pt.x; |
||||
else if (pt.x > rect.width) |
||||
rect.width = pt.x; |
||||
|
||||
if (pt.y < rect.y) |
||||
rect.y = pt.y; |
||||
else if (pt.y > rect.height) |
||||
rect.height = pt.y; |
||||
} |
||||
|
||||
prev_s = s; |
||||
pt += chainCodeDeltas[s]; |
||||
|
||||
if (i4 == i0 && i3 == i1) |
||||
break; |
||||
|
||||
i3 = i4; |
||||
s = (s + 4) & 7; |
||||
} |
||||
} |
||||
rect.width -= rect.x - 1; |
||||
rect.height -= rect.y - 1; |
||||
res_contour.brect = rect; |
||||
} |
||||
|
||||
} // namespace
|
||||
|
||||
|
||||
//==============================================================================
|
||||
|
||||
//
|
||||
// Raster->Chain Tree (Suzuki algorithms)
|
||||
//
|
||||
|
||||
// Structure that is used for sequential retrieving contours from the image.
|
||||
// It supports both hierarchical and plane variants of Suzuki algorithm.
|
||||
struct ContourScanner_ |
||||
{ |
||||
Mat image; |
||||
Point offset; // ROI offset: coordinates, added to each contour point
|
||||
Point pt; // current scanner position
|
||||
Point lnbd; // position of the last met contour
|
||||
schar nbd; // current mark val
|
||||
int approx_method1; // approx method when tracing
|
||||
int approx_method2; // final approx method
|
||||
int mode; |
||||
CTree tree; |
||||
array<int, 128> ctable; |
||||
|
||||
public: |
||||
ContourScanner_() {} |
||||
~ContourScanner_() {} |
||||
inline bool isInt() const |
||||
{ |
||||
return (this->mode == CV_RETR_FLOODFILL); |
||||
} |
||||
inline bool isSimple() const |
||||
{ |
||||
return (this->mode == RETR_EXTERNAL || this->mode == RETR_LIST); |
||||
} |
||||
|
||||
CNode& makeContour(schar& nbd_, const bool is_hole, const int x, const int y); |
||||
bool contourScan(const int prev, int& p, Point& last_pos, const int x, const int y); |
||||
int findFirstBoundingContour(const Point& last_pos, const int y, const int lval, int par); |
||||
int findNextX(int x, int y, int& prev, int& p); |
||||
bool findNext(); |
||||
|
||||
static shared_ptr<ContourScanner_> create(Mat img, int mode, int method, Point offset); |
||||
}; // class ContourScanner_
|
||||
|
||||
typedef shared_ptr<ContourScanner_> ContourScanner; |
||||
|
||||
|
||||
shared_ptr<ContourScanner_> ContourScanner_::create(Mat img, int mode, int method, Point offset) |
||||
{ |
||||
if (mode == RETR_CCOMP && img.type() == CV_32SC1) |
||||
mode = RETR_FLOODFILL; |
||||
|
||||
if (mode == RETR_FLOODFILL) |
||||
CV_CheckTypeEQ(img.type(), CV_32SC1, "RETR_FLOODFILL mode supports only CV_32SC1 images"); |
||||
else |
||||
CV_CheckTypeEQ(img.type(), |
||||
CV_8UC1, |
||||
"Modes other than RETR_FLOODFILL and RETR_CCOMP support only CV_8UC1 " |
||||
"images"); |
||||
|
||||
CV_Check(mode, |
||||
mode == RETR_EXTERNAL || mode == RETR_LIST || mode == RETR_CCOMP || |
||||
mode == RETR_TREE || mode == RETR_FLOODFILL, |
||||
"Wrong extraction mode"); |
||||
|
||||
CV_Check(method, |
||||
method == 0 || method == CHAIN_APPROX_NONE || method == CHAIN_APPROX_SIMPLE || |
||||
method == CHAIN_APPROX_TC89_L1 || method == CHAIN_APPROX_TC89_KCOS, |
||||
"Wrong approximation method"); |
||||
|
||||
Size size = img.size(); |
||||
CV_Assert(size.height >= 1); |
||||
|
||||
shared_ptr<ContourScanner_> scanner = make_shared<ContourScanner_>(); |
||||
scanner->image = img; |
||||
scanner->mode = mode; |
||||
scanner->offset = offset; |
||||
scanner->pt = Point(1, 1); |
||||
scanner->lnbd = Point(0, 1); |
||||
scanner->nbd = 2; |
||||
CNode& root = scanner->tree.newElem(); |
||||
CV_Assert(root.self() == 0); |
||||
root.body.isHole = true; |
||||
root.body.brect = Rect(Point(0, 0), size); |
||||
scanner->ctable.fill(-1); |
||||
scanner->approx_method2 = scanner->approx_method1 = method; |
||||
if (method == CV_CHAIN_APPROX_TC89_L1 || method == CV_CHAIN_APPROX_TC89_KCOS) |
||||
scanner->approx_method1 = CV_CHAIN_CODE; |
||||
return scanner; |
||||
} |
||||
|
||||
CNode& ContourScanner_::makeContour(schar& nbd_, const bool is_hole, const int x, const int y) |
||||
{ |
||||
const bool isChain = (this->approx_method1 == CV_CHAIN_CODE); // TODO: get rid of old constant
|
||||
const bool isDirect = (this->approx_method1 == CHAIN_APPROX_NONE); |
||||
|
||||
const Point start_pt(x - (is_hole ? 1 : 0), y); |
||||
|
||||
CNode& res = tree.newElem(); |
||||
if (isChain) |
||||
res.body.codes.reserve(200); |
||||
else |
||||
res.body.pts.reserve(200); |
||||
res.body.isHole = is_hole; |
||||
res.body.isChain = isChain; |
||||
res.body.origin = start_pt + offset; |
||||
if (isSimple()) |
||||
{ |
||||
icvFetchContourEx<schar>(this->image, start_pt, MASK8_NEW, res.body, isDirect); |
||||
} |
||||
else |
||||
{ |
||||
schar lval; |
||||
if (isInt()) |
||||
{ |
||||
const int start_val = this->image.at<int>(start_pt); |
||||
lval = start_val & MASK8_LVAL; |
||||
icvFetchContourEx<int>(this->image, start_pt, 0, res.body, isDirect); |
||||
} |
||||
else |
||||
{ |
||||
lval = nbd_; |
||||
// change nbd
|
||||
nbd_ = (nbd_ + 1) & MASK8_LVAL; |
||||
if (nbd_ == 0) |
||||
nbd_ = MASK8_BLACK | MASK8_NEW; |
||||
icvFetchContourEx<schar>(this->image, start_pt, lval, res.body, isDirect); |
||||
} |
||||
res.body.brect.x -= this->offset.x; |
||||
res.body.brect.y -= this->offset.y; |
||||
res.ctable_next = this->ctable[lval]; |
||||
this->ctable[lval] = res.self(); |
||||
} |
||||
const Point prev_origin = res.body.origin; |
||||
res.body.origin = start_pt; |
||||
if (this->approx_method1 != this->approx_method2) |
||||
{ |
||||
CV_Assert(res.body.isChain); |
||||
res.body.pts = approximateChainTC89(res.body.codes, prev_origin, this->approx_method2); |
||||
res.body.isChain = false; |
||||
} |
||||
return res; |
||||
} |
||||
|
||||
bool ContourScanner_::contourScan(const int prev, int& p, Point& last_pos, const int x, const int y) |
||||
{ |
||||
bool is_hole = false; |
||||
|
||||
/* if not external contour */ |
||||
if (isInt()) |
||||
{ |
||||
if (!(((prev & MASK_FLAGS) != 0 || prev == 0) && (p & MASK_FLAGS) == 0)) |
||||
{ |
||||
if ((prev & MASK_FLAGS) != 0 || ((p & MASK_FLAGS) != 0)) |
||||
return false; |
||||
|
||||
if (prev & MASK_FLAGS) |
||||
{ |
||||
last_pos.x = x - 1; |
||||
} |
||||
is_hole = true; |
||||
} |
||||
} |
||||
else |
||||
{ |
||||
if (!(prev == 0 && p == 1)) |
||||
{ |
||||
if (p != 0 || prev < 1) |
||||
return false; |
||||
|
||||
if (prev & MASK8_FLAGS) |
||||
{ |
||||
last_pos.x = x - 1; |
||||
} |
||||
is_hole = true; |
||||
} |
||||
} |
||||
|
||||
if (mode == RETR_EXTERNAL && (is_hole || this->image.at<schar>(last_pos) > 0)) |
||||
{ |
||||
return false; |
||||
} |
||||
|
||||
/* find contour parent */ |
||||
int main_parent = -1; |
||||
if (isSimple() || (!is_hole && (mode == CV_RETR_CCOMP || mode == CV_RETR_FLOODFILL)) || |
||||
last_pos.x <= 0) |
||||
{ |
||||
main_parent = 0; |
||||
} |
||||
else |
||||
{ |
||||
int lval; |
||||
if (isInt()) |
||||
lval = this->image.at<int>(last_pos.y, last_pos.x) & MASK8_LVAL; |
||||
else |
||||
lval = this->image.at<schar>(last_pos.y, last_pos.x) & MASK8_LVAL; |
||||
|
||||
main_parent = findFirstBoundingContour(last_pos, y, lval, main_parent); |
||||
|
||||
// if current contour is a hole and previous contour is a hole or
|
||||
// current contour is external and previous contour is external then
|
||||
// the parent of the contour is the parent of the previous contour else
|
||||
// the parent is the previous contour itself.
|
||||
{ |
||||
CNode& main_parent_elem = tree.elem(main_parent); |
||||
if (main_parent_elem.body.isHole == is_hole) |
||||
{ |
||||
if (main_parent_elem.parent != -1) |
||||
{ |
||||
main_parent = main_parent_elem.parent; |
||||
} |
||||
else |
||||
{ |
||||
main_parent = 0; |
||||
} |
||||
} |
||||
} |
||||
|
||||
// hole flag of the parent must differ from the flag of the contour
|
||||
{ |
||||
CNode& main_parent_elem = tree.elem(main_parent); |
||||
CV_Assert(main_parent_elem.body.isHole != is_hole); |
||||
} |
||||
} |
||||
|
||||
last_pos.x = x - (is_hole ? 1 : 0); |
||||
|
||||
schar nbd_ = this->nbd; |
||||
CNode& new_contour = makeContour(nbd_, is_hole, x, y); |
||||
if (new_contour.parent == -1) |
||||
{ |
||||
tree.addChild(main_parent, new_contour.self()); |
||||
} |
||||
this->pt.x = !isInt() ? (x + 1) : (x + 1 - (is_hole ? 1 : 0)); |
||||
this->pt.y = y; |
||||
this->nbd = nbd_; |
||||
return true; |
||||
} |
||||
|
||||
int ContourScanner_::findFirstBoundingContour(const Point& last_pos, |
||||
const int y, |
||||
const int lval, |
||||
int par) |
||||
{ |
||||
const Point end_point(last_pos.x, y); |
||||
int res = par; |
||||
int cur = ctable[lval]; |
||||
while (cur != -1) |
||||
{ |
||||
CNode& cur_elem = tree.elem(cur); |
||||
if (((last_pos.x - cur_elem.body.brect.x) < cur_elem.body.brect.width) && |
||||
((last_pos.y - cur_elem.body.brect.y) < cur_elem.body.brect.height)) |
||||
{ |
||||
if (res != -1) |
||||
{ |
||||
CNode& res_elem = tree.elem(res); |
||||
const Point origin = res_elem.body.origin; |
||||
const bool isHole = res_elem.body.isHole; |
||||
if (isInt()) |
||||
{ |
||||
if (icvTraceContour<int>(this->image, origin, end_point, isHole)) |
||||
break; |
||||
} |
||||
else |
||||
{ |
||||
if (icvTraceContour<schar>(this->image, origin, end_point, isHole)) |
||||
break; |
||||
} |
||||
} |
||||
res = cur; |
||||
} |
||||
cur = cur_elem.ctable_next; |
||||
} |
||||
return res; |
||||
} |
||||
|
||||
int ContourScanner_::findNextX(int x, int y, int& prev, int& p) |
||||
{ |
||||
const int width = this->image.size().width - 1; |
||||
if (isInt()) |
||||
{ |
||||
for (; x < width && |
||||
((p = this->image.at<int>(y, x)) == prev || (p & MASK_VAL) == (prev & MASK_VAL)); |
||||
x++) |
||||
prev = p; |
||||
} |
||||
else |
||||
{ |
||||
#if (CV_SIMD || CV_SIMD_SCALABLE) |
||||
if ((p = this->image.at<schar>(y, x)) != prev) |
||||
{ |
||||
return x; |
||||
} |
||||
else |
||||
{ |
||||
v_uint8 v_prev = vx_setall_u8((uchar)prev); |
||||
for (; x <= width - VTraits<v_uint8>::vlanes(); x += VTraits<v_uint8>::vlanes()) |
||||
{ |
||||
v_uint8 vmask = (v_ne(vx_load(this->image.ptr<uchar>(y, x)), v_prev)); |
||||
if (v_check_any(vmask)) |
||||
{ |
||||
x += v_scan_forward(vmask); |
||||
p = this->image.at<schar>(y, x); |
||||
return x; |
||||
} |
||||
} |
||||
} |
||||
#endif |
||||
for (; x < width && (p = this->image.at<schar>(y, x)) == prev; x++) |
||||
; |
||||
} |
||||
return x; |
||||
} |
||||
|
||||
bool ContourScanner_::findNext() |
||||
{ |
||||
int x = this->pt.x; |
||||
int y = this->pt.y; |
||||
int width = this->image.size().width - 1; |
||||
int height = this->image.size().height - 1; |
||||
Point last_pos = this->lnbd; |
||||
int prev = isInt() ? this->image.at<int>(y, x - 1) : this->image.at<schar>(y, x - 1); |
||||
|
||||
for (; y < height; y++) |
||||
{ |
||||
int p = 0; |
||||
for (; x < width; x++) |
||||
{ |
||||
x = findNextX(x, y, prev, p); |
||||
if (x >= width) |
||||
break; |
||||
if (contourScan(prev, p, last_pos, x, y)) |
||||
{ |
||||
this->lnbd = last_pos; |
||||
return true; |
||||
} |
||||
else |
||||
{ |
||||
prev = p; |
||||
if ((isInt() && (prev & MASK_FLAGS)) || (!isInt() && (prev & MASK8_FLAGS))) |
||||
{ |
||||
last_pos.x = x; |
||||
} |
||||
} |
||||
} |
||||
last_pos = Point(0, y + 1); |
||||
x = 1; |
||||
prev = 0; |
||||
} |
||||
|
||||
return false; |
||||
} |
||||
|
||||
//==============================================================================
|
||||
|
||||
void cv::findContours(InputArray _image, |
||||
OutputArrayOfArrays _contours, |
||||
OutputArray _hierarchy, |
||||
int mode, |
||||
int method, |
||||
Point offset) |
||||
{ |
||||
CV_INSTRUMENT_REGION(); |
||||
|
||||
// TODO: remove this block in future
|
||||
if (method == 5 /*CV_LINK_RUNS*/) |
||||
{ |
||||
CV_LOG_ONCE_WARNING(NULL, |
||||
"LINK_RUNS mode has been extracted to separate function: " |
||||
"cv::findContoursLinkRuns. " |
||||
"Calling through cv::findContours will be removed in future."); |
||||
CV_CheckTrue(!_hierarchy.needed() || mode == RETR_CCOMP, |
||||
"LINK_RUNS mode supports only simplified hierarchy output (mode=RETR_CCOMP)"); |
||||
findContoursLinkRuns(_image, _contours, _hierarchy); |
||||
return; |
||||
} |
||||
|
||||
// TODO: need enum value, need way to return contour starting points with chain codes
|
||||
if (method == 0 /*CV_CHAIN_CODE*/) |
||||
{ |
||||
CV_LOG_ONCE_WARNING(NULL, |
||||
"Chain code output is an experimental feature and might change in " |
||||
"future!"); |
||||
} |
||||
|
||||
// Sanity check: output must be of type vector<vector<Point>>
|
||||
CV_Assert((_contours.kind() == _InputArray::STD_VECTOR_VECTOR) || |
||||
(_contours.kind() == _InputArray::STD_VECTOR_MAT) || |
||||
(_contours.kind() == _InputArray::STD_VECTOR_UMAT)); |
||||
|
||||
const int res_type = (method == 0 /*CV_CHAIN_CODE*/) ? CV_8SC1 : CV_32SC2; |
||||
if (!_contours.empty()) |
||||
{ |
||||
CV_CheckTypeEQ(_contours.type(), |
||||
res_type, |
||||
"Contours must have type CV_8SC1 (chain code) or CV_32SC2 (other methods)"); |
||||
} |
||||
|
||||
if (_hierarchy.needed()) |
||||
_hierarchy.clear(); |
||||
|
||||
// preprocess
|
||||
Mat image; |
||||
copyMakeBorder(_image, image, 1, 1, 1, 1, BORDER_CONSTANT | BORDER_ISOLATED, Scalar(0)); |
||||
if (image.type() != CV_32SC1) |
||||
threshold(image, image, 0, 1, THRESH_BINARY); |
||||
|
||||
// find contours
|
||||
ContourScanner scanner = ContourScanner_::create(image, mode, method, offset + Point(-1, -1)); |
||||
while (scanner->findNext()) |
||||
{ |
||||
} |
||||
|
||||
contourTreeToResults(scanner->tree, res_type, _contours, _hierarchy); |
||||
} |
||||
|
||||
void cv::findContours(InputArray _image, |
||||
OutputArrayOfArrays _contours, |
||||
int mode, |
||||
int method, |
||||
Point offset) |
||||
{ |
||||
CV_INSTRUMENT_REGION(); |
||||
findContours(_image, _contours, noArray(), mode, method, offset); |
||||
} |
||||
@ -0,0 +1,606 @@ |
||||
// This file is part of OpenCV project.
|
||||
// It is subject to the license terms in the LICENSE file found in the top-level directory
|
||||
// of this distribution and at http://opencv.org/license.html
|
||||
|
||||
#include "opencv2/imgproc/types_c.h" |
||||
#include "test_precomp.hpp" |
||||
#include "opencv2/ts/ocl_test.hpp" |
||||
#include "opencv2/imgproc/detail/legacy.hpp" |
||||
|
||||
#define CHECK_OLD 1 |
||||
|
||||
namespace opencv_test { namespace { |
||||
|
||||
// debug function
|
||||
template <typename T> |
||||
inline static void print_pts(const T& c) |
||||
{ |
||||
for (const auto& one_pt : c) |
||||
{ |
||||
cout << one_pt << " "; |
||||
} |
||||
cout << endl; |
||||
} |
||||
|
||||
// debug function
|
||||
template <typename T> |
||||
inline static void print_pts_2(vector<T>& cs) |
||||
{ |
||||
int cnt = 0; |
||||
cout << "Contours:" << endl; |
||||
for (const auto& one_c : cs) |
||||
{ |
||||
cout << cnt++ << " : "; |
||||
print_pts(one_c); |
||||
} |
||||
}; |
||||
|
||||
// draw 1-2 px blob with orientation defined by 'kind'
|
||||
template <typename T> |
||||
inline static void drawSmallContour(Mat& img, Point pt, int kind, int color_) |
||||
{ |
||||
const T color = static_cast<T>(color_); |
||||
img.at<T>(pt) = color; |
||||
switch (kind) |
||||
{ |
||||
case 1: img.at<T>(pt + Point(1, 0)) = color; break; |
||||
case 2: img.at<T>(pt + Point(1, -1)) = color; break; |
||||
case 3: img.at<T>(pt + Point(0, -1)) = color; break; |
||||
case 4: img.at<T>(pt + Point(-1, -1)) = color; break; |
||||
case 5: img.at<T>(pt + Point(-1, 0)) = color; break; |
||||
case 6: img.at<T>(pt + Point(-1, 1)) = color; break; |
||||
case 7: img.at<T>(pt + Point(0, 1)) = color; break; |
||||
case 8: img.at<T>(pt + Point(1, 1)) = color; break; |
||||
default: break; |
||||
} |
||||
} |
||||
|
||||
inline static void drawContours(Mat& img, |
||||
const vector<vector<Point>>& contours, |
||||
const Scalar& color = Scalar::all(255)) |
||||
{ |
||||
for (const auto& contour : contours) |
||||
{ |
||||
for (size_t n = 0, end = contour.size(); n < end; ++n) |
||||
{ |
||||
size_t m = n + 1; |
||||
if (n == end - 1) |
||||
m = 0; |
||||
line(img, contour[m], contour[n], color, 1, LINE_8); |
||||
} |
||||
} |
||||
} |
||||
|
||||
//==================================================================================================
|
||||
|
||||
// Test parameters - mode + method
|
||||
typedef testing::TestWithParam<tuple<int, int>> Imgproc_FindContours_Modes1; |
||||
|
||||
|
||||
// Draw random rectangle and find contours
|
||||
//
|
||||
TEST_P(Imgproc_FindContours_Modes1, rectangle) |
||||
{ |
||||
const int mode = get<0>(GetParam()); |
||||
const int method = get<1>(GetParam()); |
||||
|
||||
const size_t ITER = 100; |
||||
RNG rng = TS::ptr()->get_rng(); |
||||
|
||||
for (size_t i = 0; i < ITER; ++i) |
||||
{ |
||||
SCOPED_TRACE(cv::format("i=%zu", i)); |
||||
const Size sz(rng.uniform(640, 1920), rng.uniform(480, 1080)); |
||||
Mat img(sz, CV_8UC1, Scalar::all(0)); |
||||
Mat img32s(sz, CV_32SC1, Scalar::all(0)); |
||||
const Rect r(Point(rng.uniform(1, sz.width / 2 - 1), rng.uniform(1, sz.height / 2)), |
||||
Point(rng.uniform(sz.width / 2 - 1, sz.width - 1), |
||||
rng.uniform(sz.height / 2 - 1, sz.height - 1))); |
||||
rectangle(img, r, Scalar::all(255)); |
||||
rectangle(img32s, r, Scalar::all(255), FILLED); |
||||
|
||||
const vector<Point> ext_ref {r.tl(), |
||||
r.tl() + Point(0, r.height - 1), |
||||
r.br() + Point(-1, -1), |
||||
r.tl() + Point(r.width - 1, 0)}; |
||||
const vector<Point> int_ref {ext_ref[0] + Point(0, 1), |
||||
ext_ref[0] + Point(1, 0), |
||||
ext_ref[3] + Point(-1, 0), |
||||
ext_ref[3] + Point(0, 1), |
||||
ext_ref[2] + Point(0, -1), |
||||
ext_ref[2] + Point(-1, 0), |
||||
ext_ref[1] + Point(1, 0), |
||||
ext_ref[1] + Point(0, -1)}; |
||||
const size_t ext_perimeter = r.width * 2 + r.height * 2; |
||||
const size_t int_perimeter = ext_perimeter - 4; |
||||
|
||||
vector<vector<Point>> contours; |
||||
vector<vector<schar>> chains; |
||||
vector<Vec4i> hierarchy; |
||||
|
||||
// run functionn
|
||||
if (mode == RETR_FLOODFILL) |
||||
if (method == 0) |
||||
findContours(img32s, chains, hierarchy, mode, method); |
||||
else |
||||
findContours(img32s, contours, hierarchy, mode, method); |
||||
else if (method == 0) |
||||
findContours(img, chains, hierarchy, mode, method); |
||||
else |
||||
findContours(img, contours, hierarchy, mode, method); |
||||
|
||||
// verify results
|
||||
if (mode == RETR_EXTERNAL) |
||||
{ |
||||
if (method == 0) |
||||
{ |
||||
ASSERT_EQ(1U, chains.size()); |
||||
} |
||||
else |
||||
{ |
||||
ASSERT_EQ(1U, contours.size()); |
||||
if (method == CHAIN_APPROX_NONE) |
||||
{ |
||||
EXPECT_EQ(int_perimeter, contours[0].size()); |
||||
} |
||||
else if (method == CHAIN_APPROX_SIMPLE) |
||||
{ |
||||
EXPECT_MAT_NEAR(Mat(ext_ref), Mat(contours[0]), 0); |
||||
} |
||||
} |
||||
} |
||||
else |
||||
{ |
||||
if (method == 0) |
||||
{ |
||||
ASSERT_EQ(2U, chains.size()); |
||||
} |
||||
else |
||||
{ |
||||
ASSERT_EQ(2U, contours.size()); |
||||
if (mode == RETR_LIST) |
||||
{ |
||||
if (method == CHAIN_APPROX_NONE) |
||||
{ |
||||
EXPECT_EQ(int_perimeter - 4, contours[0].size()); |
||||
EXPECT_EQ(int_perimeter, contours[1].size()); |
||||
} |
||||
else if (method == CHAIN_APPROX_SIMPLE) |
||||
{ |
||||
EXPECT_MAT_NEAR(Mat(int_ref), Mat(contours[0]), 0); |
||||
EXPECT_MAT_NEAR(Mat(ext_ref), Mat(contours[1]), 0); |
||||
} |
||||
} |
||||
else if (mode == RETR_CCOMP || mode == RETR_TREE) |
||||
{ |
||||
if (method == CHAIN_APPROX_NONE) |
||||
{ |
||||
EXPECT_EQ(int_perimeter, contours[0].size()); |
||||
EXPECT_EQ(int_perimeter - 4, contours[1].size()); |
||||
} |
||||
else if (method == CHAIN_APPROX_SIMPLE) |
||||
{ |
||||
EXPECT_MAT_NEAR(Mat(ext_ref), Mat(contours[0]), 0); |
||||
EXPECT_MAT_NEAR(Mat(int_ref), Mat(contours[1]), 0); |
||||
} |
||||
} |
||||
else if (mode == RETR_FLOODFILL) |
||||
{ |
||||
if (method == CHAIN_APPROX_NONE) |
||||
{ |
||||
EXPECT_EQ(int_perimeter + 4, contours[0].size()); |
||||
} |
||||
else if (method == CHAIN_APPROX_SIMPLE) |
||||
{ |
||||
EXPECT_EQ(int_ref.size(), contours[0].size()); |
||||
EXPECT_MAT_NEAR(Mat(ext_ref), Mat(contours[1]), 0); |
||||
} |
||||
} |
||||
} |
||||
} |
||||
|
||||
#if CHECK_OLD |
||||
if (method != 0) // old doesn't support chain codes
|
||||
{ |
||||
if (mode != RETR_FLOODFILL) |
||||
{ |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours.size(), contours_o.size()); |
||||
for (size_t j = 0; j < contours.size(); ++j) |
||||
{ |
||||
SCOPED_TRACE(format("contour %zu", j)); |
||||
EXPECT_MAT_NEAR(Mat(contours[j]), Mat(contours_o[j]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy), Mat(hierarchy_o), 0); |
||||
} |
||||
else |
||||
{ |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img32s, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours.size(), contours_o.size()); |
||||
for (size_t j = 0; j < contours.size(); ++j) |
||||
{ |
||||
SCOPED_TRACE(format("contour %zu", j)); |
||||
EXPECT_MAT_NEAR(Mat(contours[j]), Mat(contours_o[j]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy), Mat(hierarchy_o), 0); |
||||
} |
||||
} |
||||
#endif |
||||
} |
||||
} |
||||
|
||||
|
||||
// Draw many small 1-2px blobs and find contours
|
||||
//
|
||||
TEST_P(Imgproc_FindContours_Modes1, small) |
||||
{ |
||||
const int mode = get<0>(GetParam()); |
||||
const int method = get<1>(GetParam()); |
||||
|
||||
const size_t DIM = 1000; |
||||
const Size sz(DIM, DIM); |
||||
const int num = (DIM / 10) * (DIM / 10); // number of 10x10 squares
|
||||
|
||||
Mat img(sz, CV_8UC1, Scalar::all(0)); |
||||
Mat img32s(sz, CV_32SC1, Scalar::all(0)); |
||||
vector<Point> pts; |
||||
int extra_contours_32s = 0; |
||||
for (int j = 0; j < num; ++j) |
||||
{ |
||||
const int kind = j % 9; |
||||
Point pt {(j % 100) * 10 + 4, (j / 100) * 10 + 4}; |
||||
drawSmallContour<uchar>(img, pt, kind, 255); |
||||
drawSmallContour<int>(img32s, pt, kind, j + 1); |
||||
pts.push_back(pt); |
||||
// NOTE: for some reason these small diagonal contours (NW, SE)
|
||||
// result in 2 external contours for FLOODFILL mode
|
||||
if (kind == 8 || kind == 4) |
||||
++extra_contours_32s; |
||||
} |
||||
{ |
||||
vector<vector<Point>> contours; |
||||
vector<vector<schar>> chains; |
||||
vector<Vec4i> hierarchy; |
||||
|
||||
if (mode == RETR_FLOODFILL) |
||||
{ |
||||
if (method == 0) |
||||
{ |
||||
findContours(img32s, chains, hierarchy, mode, method); |
||||
ASSERT_EQ(pts.size() * 2 + extra_contours_32s, chains.size()); |
||||
} |
||||
else |
||||
{ |
||||
findContours(img32s, contours, hierarchy, mode, method); |
||||
ASSERT_EQ(pts.size() * 2 + extra_contours_32s, contours.size()); |
||||
#if CHECK_OLD |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img32s, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours.size(), contours_o.size()); |
||||
for (size_t i = 0; i < contours.size(); ++i) |
||||
{ |
||||
SCOPED_TRACE(format("contour %zu", i)); |
||||
EXPECT_MAT_NEAR(Mat(contours[i]), Mat(contours_o[i]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy), Mat(hierarchy_o), 0); |
||||
#endif |
||||
} |
||||
} |
||||
else |
||||
{ |
||||
if (method == 0) |
||||
{ |
||||
findContours(img, chains, hierarchy, mode, method); |
||||
ASSERT_EQ(pts.size(), chains.size()); |
||||
} |
||||
else |
||||
{ |
||||
findContours(img, contours, hierarchy, mode, method); |
||||
ASSERT_EQ(pts.size(), contours.size()); |
||||
#if CHECK_OLD |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours.size(), contours_o.size()); |
||||
for (size_t i = 0; i < contours.size(); ++i) |
||||
{ |
||||
SCOPED_TRACE(format("contour %zu", i)); |
||||
EXPECT_MAT_NEAR(Mat(contours[i]), Mat(contours_o[i]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy), Mat(hierarchy_o), 0); |
||||
#endif |
||||
} |
||||
} |
||||
} |
||||
} |
||||
|
||||
|
||||
// Draw many nested rectangles and find contours
|
||||
//
|
||||
TEST_P(Imgproc_FindContours_Modes1, deep) |
||||
{ |
||||
const int mode = get<0>(GetParam()); |
||||
const int method = get<1>(GetParam()); |
||||
|
||||
const size_t DIM = 1000; |
||||
const Size sz(DIM, DIM); |
||||
const size_t NUM = 249U; |
||||
Mat img(sz, CV_8UC1, Scalar::all(0)); |
||||
Mat img32s(sz, CV_32SC1, Scalar::all(0)); |
||||
Rect rect(1, 1, 998, 998); |
||||
for (size_t i = 0; i < NUM; ++i) |
||||
{ |
||||
rectangle(img, rect, Scalar::all(255)); |
||||
rectangle(img32s, rect, Scalar::all((double)i + 1), FILLED); |
||||
rect.x += 2; |
||||
rect.y += 2; |
||||
rect.width -= 4; |
||||
rect.height -= 4; |
||||
} |
||||
{ |
||||
vector<vector<Point>> contours {{{0, 0}, {1, 1}}}; |
||||
vector<vector<schar>> chains {{1, 2, 3}}; |
||||
vector<Vec4i> hierarchy; |
||||
|
||||
if (mode == RETR_FLOODFILL) |
||||
{ |
||||
if (method == 0) |
||||
{ |
||||
findContours(img32s, chains, hierarchy, mode, method); |
||||
ASSERT_EQ(2 * NUM, chains.size()); |
||||
} |
||||
else |
||||
{ |
||||
findContours(img32s, contours, hierarchy, mode, method); |
||||
ASSERT_EQ(2 * NUM, contours.size()); |
||||
#if CHECK_OLD |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img32s, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours.size(), contours_o.size()); |
||||
for (size_t i = 0; i < contours.size(); ++i) |
||||
{ |
||||
SCOPED_TRACE(format("contour %zu", i)); |
||||
EXPECT_MAT_NEAR(Mat(contours[i]), Mat(contours_o[i]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy), Mat(hierarchy_o), 0); |
||||
#endif |
||||
} |
||||
} |
||||
else |
||||
{ |
||||
const size_t expected_count = (mode == RETR_EXTERNAL) ? 1U : 2 * NUM; |
||||
if (method == 0) |
||||
{ |
||||
findContours(img, chains, hierarchy, mode, method); |
||||
ASSERT_EQ(expected_count, chains.size()); |
||||
} |
||||
else |
||||
{ |
||||
findContours(img, contours, hierarchy, mode, method); |
||||
ASSERT_EQ(expected_count, contours.size()); |
||||
#if CHECK_OLD |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours.size(), contours_o.size()); |
||||
for (size_t i = 0; i < contours.size(); ++i) |
||||
{ |
||||
SCOPED_TRACE(format("contour %zu", i)); |
||||
EXPECT_MAT_NEAR(Mat(contours[i]), Mat(contours_o[i]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy), Mat(hierarchy_o), 0); |
||||
#endif |
||||
} |
||||
} |
||||
} |
||||
} |
||||
|
||||
INSTANTIATE_TEST_CASE_P( |
||||
, |
||||
Imgproc_FindContours_Modes1, |
||||
testing::Combine( |
||||
testing::Values(RETR_EXTERNAL, RETR_LIST, RETR_CCOMP, RETR_TREE, RETR_FLOODFILL), |
||||
testing::Values(0, |
||||
CHAIN_APPROX_NONE, |
||||
CHAIN_APPROX_SIMPLE, |
||||
CHAIN_APPROX_TC89_L1, |
||||
CHAIN_APPROX_TC89_KCOS))); |
||||
|
||||
//==================================================================================================
|
||||
|
||||
typedef testing::TestWithParam<tuple<int, int>> Imgproc_FindContours_Modes2; |
||||
|
||||
// Very approximate backport of an old accuracy test
|
||||
//
|
||||
TEST_P(Imgproc_FindContours_Modes2, new_accuracy) |
||||
{ |
||||
const int mode = get<0>(GetParam()); |
||||
const int method = get<1>(GetParam()); |
||||
|
||||
RNG& rng = TS::ptr()->get_rng(); |
||||
const int blob_count = rng.uniform(1, 10); |
||||
const Size sz(rng.uniform(640, 1920), rng.uniform(480, 1080)); |
||||
const int blob_sz = 50; |
||||
|
||||
// prepare image
|
||||
Mat img(sz, CV_8UC1, Scalar::all(0)); |
||||
vector<RotatedRect> rects; |
||||
for (int i = 0; i < blob_count; ++i) |
||||
{ |
||||
const Point2f center((float)rng.uniform(blob_sz, sz.width - blob_sz), |
||||
(float)rng.uniform(blob_sz, sz.height - blob_sz)); |
||||
const Size2f rsize((float)rng.uniform(1, blob_sz), (float)rng.uniform(1, blob_sz)); |
||||
RotatedRect rect(center, rsize, rng.uniform(0.f, 180.f)); |
||||
rects.push_back(rect); |
||||
ellipse(img, rect, Scalar::all(100), FILLED); |
||||
} |
||||
|
||||
// draw contours manually
|
||||
Mat cont_img(sz, CV_8UC1, Scalar::all(0)); |
||||
for (int y = 1; y < sz.height - 1; ++y) |
||||
{ |
||||
for (int x = 1; x < sz.width - 1; ++x) |
||||
{ |
||||
if (img.at<uchar>(y, x) != 0 && |
||||
((img.at<uchar>(y - 1, x) == 0) || (img.at<uchar>(y + 1, x) == 0) || |
||||
(img.at<uchar>(y, x + 1) == 0) || (img.at<uchar>(y, x - 1) == 0))) |
||||
{ |
||||
cont_img.at<uchar>(y, x) = 255; |
||||
} |
||||
} |
||||
} |
||||
|
||||
// find contours
|
||||
vector<vector<Point>> contours; |
||||
vector<Vec4i> hierarchy; |
||||
findContours(img, contours, hierarchy, mode, method); |
||||
|
||||
// 0 < contours <= rects
|
||||
EXPECT_GT(contours.size(), 0U); |
||||
EXPECT_GE(rects.size(), contours.size()); |
||||
|
||||
// draw contours
|
||||
Mat res_img(sz, CV_8UC1, Scalar::all(0)); |
||||
drawContours(res_img, contours); |
||||
|
||||
// compare resulting drawn contours with manually drawn contours
|
||||
const double diff1 = cvtest::norm(cont_img, res_img, NORM_L1) / 255; |
||||
|
||||
if (method == CHAIN_APPROX_NONE || method == CHAIN_APPROX_SIMPLE) |
||||
{ |
||||
EXPECT_EQ(0., diff1); |
||||
} |
||||
#if CHECK_OLD |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours(img, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours_o.size(), contours.size()); |
||||
for (size_t i = 0; i < contours_o.size(); ++i) |
||||
{ |
||||
SCOPED_TRACE(format("contour = %zu", i)); |
||||
EXPECT_MAT_NEAR(Mat(contours_o[i]), Mat(contours[i]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy_o), Mat(hierarchy), 0); |
||||
#endif |
||||
} |
||||
|
||||
TEST_P(Imgproc_FindContours_Modes2, approx) |
||||
{ |
||||
const int mode = get<0>(GetParam()); |
||||
const int method = get<1>(GetParam()); |
||||
|
||||
const Size sz {500, 500}; |
||||
Mat img = Mat::zeros(sz, CV_8UC1); |
||||
|
||||
for (int c = 0; c < 4; ++c) |
||||
{ |
||||
if (c != 0) |
||||
{ |
||||
// noise + filter + threshold
|
||||
RNG& rng = TS::ptr()->get_rng(); |
||||
cvtest::randUni(rng, img, 0, 255); |
||||
|
||||
Mat fimg; |
||||
boxFilter(img, fimg, CV_8U, Size(5, 5)); |
||||
|
||||
Mat timg; |
||||
const int level = 44 + c * 42; |
||||
// 'level' goes through:
|
||||
// 86 - some black speckles on white
|
||||
// 128 - 50/50 black/white
|
||||
// 170 - some white speckles on black
|
||||
cv::threshold(fimg, timg, level, 255, THRESH_BINARY); |
||||
} |
||||
else |
||||
{ |
||||
// circle with cut
|
||||
const Point center {250, 250}; |
||||
const int r {20}; |
||||
const Point cut {r, r}; |
||||
circle(img, center, r, Scalar(255), FILLED); |
||||
rectangle(img, center, center + cut, Scalar(0), FILLED); |
||||
} |
||||
|
||||
vector<vector<Point>> contours; |
||||
vector<Vec4i> hierarchy; |
||||
findContours(img, contours, hierarchy, mode, method); |
||||
|
||||
#if CHECK_OLD |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img, contours_o, hierarchy_o, mode, method); |
||||
ASSERT_EQ(contours_o.size(), contours.size()); |
||||
for (size_t i = 0; i < contours_o.size(); ++i) |
||||
{ |
||||
SCOPED_TRACE(format("c = %d, contour = %zu", c, i)); |
||||
EXPECT_MAT_NEAR(Mat(contours_o[i]), Mat(contours[i]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy_o), Mat(hierarchy), 0); |
||||
#endif |
||||
// TODO: check something
|
||||
} |
||||
} |
||||
|
||||
// TODO: offset test
|
||||
|
||||
// no RETR_FLOODFILL - no CV_32S input images
|
||||
INSTANTIATE_TEST_CASE_P( |
||||
, |
||||
Imgproc_FindContours_Modes2, |
||||
testing::Combine(testing::Values(RETR_EXTERNAL, RETR_LIST, RETR_CCOMP, RETR_TREE), |
||||
testing::Values(CHAIN_APPROX_NONE, |
||||
CHAIN_APPROX_SIMPLE, |
||||
CHAIN_APPROX_TC89_L1, |
||||
CHAIN_APPROX_TC89_KCOS))); |
||||
|
||||
TEST(Imgproc_FindContours, link_runs) |
||||
{ |
||||
const Size sz {500, 500}; |
||||
Mat img = Mat::zeros(sz, CV_8UC1); |
||||
|
||||
// noise + filter + threshold
|
||||
RNG& rng = TS::ptr()->get_rng(); |
||||
cvtest::randUni(rng, img, 0, 255); |
||||
|
||||
Mat fimg; |
||||
boxFilter(img, fimg, CV_8U, Size(5, 5)); |
||||
|
||||
const int level = 135; |
||||
cv::threshold(fimg, img, level, 255, THRESH_BINARY); |
||||
|
||||
vector<vector<Point>> contours; |
||||
vector<Vec4i> hierarchy; |
||||
findContoursLinkRuns(img, contours, hierarchy); |
||||
|
||||
if (cvtest::debugLevel >= 10) |
||||
{ |
||||
print_pts_2(contours); |
||||
|
||||
Mat res = Mat::zeros(sz, CV_8UC1); |
||||
drawContours(res, contours); |
||||
imshow("res", res); |
||||
imshow("img", img); |
||||
waitKey(0); |
||||
} |
||||
|
||||
#if CHECK_OLD |
||||
vector<vector<Point>> contours_o; |
||||
vector<Vec4i> hierarchy_o; |
||||
findContours_legacy(img, contours_o, hierarchy_o, 0, 5); // CV_LINK_RUNS method
|
||||
ASSERT_EQ(contours_o.size(), contours.size()); |
||||
for (size_t i = 0; i < contours_o.size(); ++i) |
||||
{ |
||||
SCOPED_TRACE(format("contour = %zu", i)); |
||||
EXPECT_MAT_NEAR(Mat(contours_o[i]), Mat(contours[i]), 0); |
||||
} |
||||
EXPECT_MAT_NEAR(Mat(hierarchy_o), Mat(hierarchy), 0); |
||||
#endif |
||||
} |
||||
|
||||
}} // namespace opencv_test
|
||||
Loading…
Reference in new issue