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authorChris Loer <chris.loer@gmail.com>2017-07-07 13:31:53 -0700
committerChris Loer <chris.loer@mapbox.com>2017-12-11 10:43:00 -0800
commit730054276ed6a5dc7ba9d19765b8457a818854f7 (patch)
tree5cae03006130df6e61c8fbf1321aa49c6ca97e61 /src/mbgl/util
parent4f31b07d091018f552341de58b4f2ae4f0f42597 (diff)
downloadqtlocation-mapboxgl-730054276ed6a5dc7ba9d19765b8457a818854f7.tar.gz
[core] C++ port of TinySDF
Diffstat (limited to 'src/mbgl/util')
-rw-r--r--src/mbgl/util/tiny_sdf.cpp105
-rw-r--r--src/mbgl/util/tiny_sdf.hpp20
2 files changed, 125 insertions, 0 deletions
diff --git a/src/mbgl/util/tiny_sdf.cpp b/src/mbgl/util/tiny_sdf.cpp
new file mode 100644
index 0000000000..60839357d5
--- /dev/null
+++ b/src/mbgl/util/tiny_sdf.cpp
@@ -0,0 +1,105 @@
+#include <mbgl/util/tiny_sdf.hpp>
+
+#include <mbgl/util/math.hpp>
+
+#include <algorithm>
+
+namespace mbgl {
+namespace util {
+
+namespace tinysdf {
+
+static const double INF = 1e20;
+
+// 1D squared distance transform
+void edt1d(std::vector<double>& f,
+ std::vector<double>& d,
+ std::vector<int16_t>& v,
+ std::vector<double>& z,
+ uint32_t n) {
+ v[0] = 0;
+ z[0] = -INF;
+ z[1] = +INF;
+
+ for (uint32_t q = 1, k = 0; q < n; q++) {
+ double s = ((f[q] + q * q) - (f[v[k]] + v[k] * v[k])) / (2 * q - 2 * v[k]);
+ while (s <= z[k]) {
+ k--;
+ s = ((f[q] + q * q) - (f[v[k]] + v[k] * v[k])) / (2 * q - 2 * v[k]);
+ }
+ k++;
+ v[k] = q;
+ z[k] = s;
+ z[k + 1] = +INF;
+ }
+
+ for (uint32_t q = 0, k = 0; q < n; q++) {
+ while (z[k + 1] < q) k++;
+ d[q] = (q - v[k]) * (q - v[k]) + f[v[k]];
+ }
+}
+
+
+// 2D Euclidean distance transform by Felzenszwalb & Huttenlocher https://cs.brown.edu/~pff/dt/
+void edt(std::vector<double>& data,
+ uint32_t width,
+ uint32_t height,
+ std::vector<double>& f,
+ std::vector<double>& d,
+ std::vector<int16_t>& v,
+ std::vector<double>& z) {
+ for (uint32_t x = 0; x < width; x++) {
+ for (uint32_t y = 0; y < height; y++) {
+ f[y] = data[y * width + x];
+ }
+ edt1d(f, d, v, z, height);
+ for (uint32_t y = 0; y < height; y++) {
+ data[y * width + x] = d[y];
+ }
+ }
+ for (uint32_t y = 0; y < height; y++) {
+ for (uint32_t x = 0; x < width; x++) {
+ f[x] = data[y * width + x];
+ }
+ edt1d(f, d, v, z, width);
+ for (uint32_t x = 0; x < width; x++) {
+ data[y * width + x] = std::sqrt(d[x]);
+ }
+ }
+}
+
+} // namespace tinysdf
+
+AlphaImage transformRasterToSDF(const AlphaImage& rasterInput, double radius, double cutoff) {
+ uint32_t size = rasterInput.size.width * rasterInput.size.height;
+ uint32_t maxDimension = std::max(rasterInput.size.width, rasterInput.size.height);
+
+ AlphaImage sdf(rasterInput.size);
+
+ // temporary arrays for the distance transform
+ std::vector<double> gridOuter(size);
+ std::vector<double> gridInner(size);
+ std::vector<double> f(maxDimension);
+ std::vector<double> d(maxDimension);
+ std::vector<double> z(maxDimension + 1);
+ std::vector<int16_t> v(maxDimension);
+
+ for (uint32_t i = 0; i < size; i++) {
+ double a = double(rasterInput.data[i]) / 255; // alpha value
+ gridOuter[i] = a == 1.0 ? 0.0 : a == 0.0 ? tinysdf::INF : std::pow(std::max(0.0, 0.5 - a), 2.0);
+ gridInner[i] = a == 1.0 ? tinysdf::INF : a == 0.0 ? 0.0 : std::pow(std::max(0.0, a - 0.5), 2.0);
+ }
+
+ tinysdf::edt(gridOuter, rasterInput.size.width, rasterInput.size.height, f, d, v, z);
+ tinysdf::edt(gridInner, rasterInput.size.width, rasterInput.size.height, f, d, v, z);
+
+ for (uint32_t i = 0; i < size; i++) {
+ double distance = gridOuter[i] - gridInner[i];
+ sdf.data[i] = std::max(0l, std::min(255l, std::lround(255.0 - 255.0 * (distance / radius + cutoff))));
+ }
+
+ return sdf;
+}
+
+} // namespace util
+} // namespace mbgl
diff --git a/src/mbgl/util/tiny_sdf.hpp b/src/mbgl/util/tiny_sdf.hpp
new file mode 100644
index 0000000000..33c9280cbd
--- /dev/null
+++ b/src/mbgl/util/tiny_sdf.hpp
@@ -0,0 +1,20 @@
+#pragma once
+
+#include <mbgl/util/image.hpp>
+
+namespace mbgl {
+namespace util {
+
+/*
+ C++ port of https://github.com/mapbox/tiny-sdf, which is in turn based on the
+ Felzenszwalb/Huttenlocher distance transform paper (https://cs.brown.edu/~pff/papers/dt-final.pdf).
+ Note there exists an alternative C++ implementation from the paper’s authors at
+ https://cs.brown.edu/~pff/dt/, which this implementation is not based on.
+
+ Takes an alpha channel raster input and transforms it into an alpha channel
+ Signed Distance Field (SDF) output of the same dimensions.
+*/
+AlphaImage transformRasterToSDF(const AlphaImage& rasterInput, double radius, double cutoff);
+
+} // namespace util
+} // namespace mbgl