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author | jaseg <git@jaseg.de> | 2021-06-05 21:22:01 +0200 |
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committer | jaseg <git@jaseg.de> | 2021-06-05 21:22:01 +0200 |
commit | 6685b7587a2d8c147715d89e27b0f3b40883b9f1 (patch) | |
tree | d73f82073aecaa4d6c87f279d30fc29f8a977d62 /svg-flatten/src/nopencv.cpp | |
parent | 3ef3f0223e9662f6c3cc6d213afcd74944399f6b (diff) | |
download | gerbolyze-6685b7587a2d8c147715d89e27b0f3b40883b9f1.tar.gz gerbolyze-6685b7587a2d8c147715d89e27b0f3b40883b9f1.tar.bz2 gerbolyze-6685b7587a2d8c147715d89e27b0f3b40883b9f1.zip |
Fix binary contours vectorizer
Replace teh-chin with ramer-douglas-peucker
Diffstat (limited to 'svg-flatten/src/nopencv.cpp')
-rw-r--r-- | svg-flatten/src/nopencv.cpp | 84 |
1 files changed, 79 insertions, 5 deletions
diff --git a/svg-flatten/src/nopencv.cpp b/svg-flatten/src/nopencv.cpp index 0643b20..121e9e1 100644 --- a/svg-flatten/src/nopencv.cpp +++ b/svg-flatten/src/nopencv.cpp @@ -1,6 +1,7 @@ #include <iostream> #include <iomanip> +#include <stack> #include "nopencv.hpp" @@ -399,6 +400,79 @@ ContourCallback gerbolyze::nopencv::simplify_contours_teh_chin(ContourCallback c }; } +static double dp_eps(double dx, double dy) { + /* Implementation of: + * + * Prasad, Dilip K., et al. "A novel framework for making dominant point detection methods non-parametric." + * Image and Vision Computing 30.11 (2012): 843-859. + * https://core.ac.uk/download/pdf/131287229.pdf + * + * For another implementation, see: + * https://github.com/BobLd/RamerDouglasPeuckerNetV2/blob/master/RamerDouglasPeuckerNetV2.Test/RamerDouglasPeuckerNetV2/RamerDouglasPeucker.cs + */ + double m = dy / dx; + double s = sqrt(pow(dx, 2) + pow(dy, 2)); + double phi = atan(m); + double t_max = 1/s * (fabs(cos(phi)) + fabs(sin(phi))); + double t_max_polynomial = 1 - t_max + pow(t_max, 2); + return s * fmax( + atan(1/s * fabs(sin(phi) + cos(phi)) * t_max_polynomial), + atan(1/s * fabs(sin(phi) - cos(phi)) * t_max_polynomial)); +} + +/* a, b inclusive */ +static array<size_t, 3> dp_step(Polygon_i &poly, size_t a, size_t b) { + + double dx = poly[b][0] - poly[a][0]; + double dy = poly[b][1] - poly[a][1]; + double eps = dp_eps(dx, dy); + + size_t max_idx = 0; + double max_dist = 0; + /* https://en.wikipedia.org/wiki/Distance_from_a_point_to_a_line */ + double dist_ab = sqrt(pow(poly[b][0] - poly[a][0], 2) + pow(poly[b][1] - poly[a][1], 2)); + for (size_t i=a+1; i<b; i++) { + double dist_i = fabs( + (poly[b][0] - poly[a][0]) * (poly[a][1] - poly[i][1]) + - (poly[a][0] - poly[i][0]) * (poly[b][1] - poly[a][1])) + / dist_ab; + if (dist_i > max_dist && dist_i > eps) { + max_dist = dist_i; + max_idx = i; + } + } + + return {a, max_idx, b}; +} + +ContourCallback gerbolyze::nopencv::simplify_contours_douglas_peucker(ContourCallback cb) { + return [&cb](Polygon_i &poly, ContourPolarity cpol) { + + Polygon_i out; + out.push_back(poly[0]); + + stack<array<size_t, 3>> indices; + indices.push(dp_step(poly, 0, poly.size()-1)); + + while (!indices.empty()) { + auto idx = indices.top(); + indices.pop(); /* awesome C++ api let's goooooo */ + + if (idx[1] > 0) { + indices.push(dp_step(poly, idx[0], idx[1])); + + indices.push(dp_step(poly, idx[1], idx[2])); + + } else { + out.push_back(poly[idx[2]]); + } + } + + + cb(out, cpol); + }; +} + double gerbolyze::nopencv::polygon_area(Polygon_i &poly) { double acc = 0; size_t prev = poly.size() - 1; @@ -432,13 +506,13 @@ bool gerbolyze::nopencv::Image<T>::load_memory(const void *buf, size_t len) { } template<typename T> -void gerbolyze::nopencv::Image<T>::binarize() { +void gerbolyze::nopencv::Image<T>::binarize(T threshold) { assert(m_data != nullptr); assert(m_rows > 0 && m_cols > 0); for (int y=0; y<m_rows; y++) { for (int x=0; x<m_cols; x++) { - m_data[y*m_cols + x] = m_data[y*m_cols + x] > 0; + m_data[y*m_cols + x] = m_data[y*m_cols + x] >= threshold; } } } @@ -494,20 +568,20 @@ void gerbolyze::nopencv::Image<uint8_t>::resize(int new_w, int new_h) { template gerbolyze::nopencv::Image<int32_t>::Image(int size_x, int size_y, const int32_t *data); template bool gerbolyze::nopencv::Image<int32_t>::load(const char *filename); template bool gerbolyze::nopencv::Image<int32_t>::load_memory(const void *buf, size_t len); -template void gerbolyze::nopencv::Image<int32_t>::binarize(); +template void gerbolyze::nopencv::Image<int32_t>::binarize(int32_t threshold); template bool gerbolyze::nopencv::Image<int32_t>::stb_to_internal(uint8_t *data); template void gerbolyze::nopencv::Image<int32_t>::blur(int radius); template gerbolyze::nopencv::Image<uint8_t>::Image(int size_x, int size_y, const uint8_t *data); template bool gerbolyze::nopencv::Image<uint8_t>::load(const char *filename); template bool gerbolyze::nopencv::Image<uint8_t>::load_memory(const void *buf, size_t len); -template void gerbolyze::nopencv::Image<uint8_t>::binarize(); +template void gerbolyze::nopencv::Image<uint8_t>::binarize(uint8_t threshold); template bool gerbolyze::nopencv::Image<uint8_t>::stb_to_internal(uint8_t *data); template void gerbolyze::nopencv::Image<uint8_t>::blur(int radius); template gerbolyze::nopencv::Image<float>::Image(int size_x, int size_y, const float *data); template bool gerbolyze::nopencv::Image<float>::load(const char *filename); template bool gerbolyze::nopencv::Image<float>::load_memory(const void *buf, size_t len); -template void gerbolyze::nopencv::Image<float>::binarize(); +template void gerbolyze::nopencv::Image<float>::binarize(float threshold); template bool gerbolyze::nopencv::Image<float>::stb_to_internal(uint8_t *data); template void gerbolyze::nopencv::Image<float>::blur(int radius); |