/*
* This file is part of gerbolyze, a vector image preprocessing toolchain
* Copyright (C) 2021 Jan Sebastian Götte <gerbolyze@jaseg.de>
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#include <cmath>
#include <string>
#include <iostream>
#include <algorithm>
#include <vector>
#include <regex>
#include "nopencv.hpp"
#include "svg_import_util.h"
#include "vec_core.h"
#include "svg_import_defs.h"
#include "jc_voronoi.h"
using namespace gerbolyze;
using namespace std;
ImageVectorizer *gerbolyze::makeVectorizer(const std::string &name) {
if (name == "poisson-disc")
return new VoronoiVectorizer(POISSON_DISC, /* relax */ true);
else if (name == "hex-grid")
return new VoronoiVectorizer(HEXGRID, /* relax */ false);
else if (name == "square-grid")
return new VoronoiVectorizer(SQUAREGRID, /* relax */ false);
else if (name == "binary-contours")
return new OpenCVContoursVectorizer();
else if (name == "dev-null")
return new DevNullVectorizer();
return nullptr;
}
/* From jcv voronoi README */
static void voronoi_relax_points(const jcv_diagram* diagram, jcv_point* points) {
const jcv_site* sites = jcv_diagram_get_sites(diagram);
for (int i=0; i<diagram->numsites; i++) {
const jcv_site* site = &sites[i];
jcv_point sum = site->p;
int count = 1;
const jcv_graphedge* edge = site->edges;
while (edge) {
sum.x += edge->pos[0].x;
sum.y += edge->pos[0].y;
count++;
edge = edge->next;
}
points[site->index].x = sum.x / count;
points[site->index].y = sum.y / count;
}
}
void gerbolyze::parse_img_meta(const pugi::xml_node &node, double &x, double &y, double &width, double &height) {
/* Read XML node attributes */
x = usvg_double_attr(node, "x", 0.0);
y = usvg_double_attr(node, "y", 0.0);
width = usvg_double_attr(node, "width", 0.0);
height = usvg_double_attr(node, "height", 0.0);
assert (width > 0 && height > 0);
cerr << "image elem: w="<<width<<", h="<<height<<endl;
}
template<typename T> nopencv::Image<T> *img_from_node(const pugi::xml_node &node) {
/* Read image from data:base64... URL */
string img_data = parse_data_iri(node.attribute("xlink:href").value());
if (img_data.empty()) {
cerr << "Warning: Empty or invalid image element with id \"" << node.attribute("id").value() << "\"" << endl;
return nullptr;
}
auto *img = new nopencv::Image<T>();
if (!img->load_memory(img_data.c_str(), img_data.size())) {
cerr << "Warning: Could not decode content of image element with id \"" << node.attribute("id").value() << "\"" << endl;
return nullptr;
}
return img;
}
void gerbolyze::draw_bg_rect(RenderContext &ctx, double width, double height) {
/* For our output to look correct, we have to paint the image's bounding box in black as background for our halftone
* blobs. We cannot simply draw a rect here, though. Instead we have to first intersect the bounding box with the
* clip path we get from the caller.
*
* First, setup the bounding box rectangle in our local px coordinate space. */
ClipperLib::Path rect_path;
for (auto &elem : vector<pair<double, double>> {
{0, 0},
{width, 0},
{width, height},
{0, height}}) {
d2p xf(ctx.mat().doc2phys(d2p{elem.first, elem.second}));
rect_path.push_back({
(ClipperLib::cInt)round(xf[0] * clipper_scale),
(ClipperLib::cInt)round(xf[1] * clipper_scale)
});
}
/* Intersect the bounding box with the caller's clip path */
ClipperLib::Clipper c;
c.AddPath(rect_path, ClipperLib::ptSubject, /* closed */ true);
if (!ctx.clip().empty()) {
c.AddPaths(ctx.clip(), ClipperLib::ptClip, /* closed */ true);
}
ClipperLib::Paths rect_out;
c.StrictlySimple(true);
c.Execute(ClipperLib::ctIntersection, rect_out, ClipperLib::pftNonZero, ClipperLib::pftNonZero);
/* draw into gerber. */
for (const auto &poly : rect_out) {
vector<array<double, 2>> out;
for (const auto &p : poly)
out.push_back(std::array<double, 2>{
((double)p.X) / clipper_scale, ((double)p.Y) / clipper_scale
});
ctx.sink() << GRB_POL_CLEAR << out;
}
}
/* Render image into gerber file.
*
* This function renders an image into a number of vector primitives emulating the images grayscale brightness by
* differently sized vector shaped giving an effect similar to halftone printing used in newspapers.
*
* On a high level, this function does this in four steps:
* 1. It preprocesses the source image at the pixel level. This involves several tasks:
* 1.1. It converts the image to grayscale.
* 1.2. It scales the image up or down to match the given minimum feature size.
* 1.3. It applies a blur depending on the given minimum feature size to prevent aliasing artifacts.
* 2. It randomly spread points across the image using poisson disc sampling. This yields points that have a fairly even
* average distance to each other across the image, and that have a guaranteed minimum distance that depends on
* minimum feature size.
* 3. It calculates a voronoi map based on this set of points and it calculats the polygon shape of each cell of the
* voronoi map.
* 4. It scales each of these voronoi cell polygons to match the input images brightness at the spot covered by this
* cell.
*/
void gerbolyze::VoronoiVectorizer::vectorize_image(RenderContext &ctx, const pugi::xml_node &node, double min_feature_size_px) {
double x, y, width, height;
parse_img_meta(node, x, y, width, height);
nopencv::Image32f *img = img_from_node<float>(node);
if (img == nullptr)
return;
/* Set up target transform using SVG transform and x/y attributes */
RenderContext img_ctx(ctx, xform2d(1, 0, 0, 1, x, y));
cerr << "voronoi vectorizer: local_xf = " << ctx.mat().dbg_str() << endl;
double orig_rows = img->rows();
double orig_cols = img->cols();
double scale_x = (double)width / orig_cols;
double scale_y = (double)height / orig_rows;
double off_x = 0;
double off_y = 0;
handle_aspect_ratio(node.attribute("preserveAspectRatio").value(),
scale_x, scale_y, off_x, off_y, orig_cols, orig_rows);
//cerr << "aspect " << scale_x << ", " << scale_y << " / " << off_x << ", " << off_y << endl;
/* Adjust minimum feature size given in mm and translate into px document units in our local coordinate system. */
min_feature_size_px = img_ctx.mat().doc2phys_dist(min_feature_size_px);
cerr << " min_feature_size_px = " << min_feature_size_px << endl;
draw_bg_rect(img_ctx, width, height);
/* Set up a poisson-disc sampled point "grid" covering the image. Calculate poisson disc parameters from given
* minimum feature size. */
double grayscale_overhead = 0.8; /* fraction of distance between two adjacent cell centers that is reserved for
grayscale interpolation. Larger values -> better grayscale resolution,
larger cells. */
double center_distance = min_feature_size_px * 2.0 * (1.0 / (1.0-grayscale_overhead));
vector<d2p> *grid_centers = get_sampler(m_grid_type)(scale_x * orig_cols, scale_y*orig_rows, center_distance);
//vector<d2p> *grid_centers = sample_poisson_disc(width, height, min_feature_size_px * 2.0 * 2.0);
//vector<d2p> *grid_centers = sample_hexgrid(width, height, center_distance);
//vector<d2p> *grid_centers = sample_squaregrid(width, height, center_distance);
/* Target factor between given min_feature_size and intermediate image pixels,
* i.e. <scale_featuresize_factor> px ^= min_feature_size */
double scale_featuresize_factor = 3.0;
/* TODO: support for preserveAspectRatio attribute */
double px_w = width / min_feature_size_px * scale_featuresize_factor;
double px_h = height / min_feature_size_px * scale_featuresize_factor;
cerr << " px_size = " << px_w << ", " << px_h << endl;
/* Scale intermediate image (step 1.2) to have <scale_featuresize_factor> pixels per min_feature_size. */
cerr << "scaled " << img->cols() << ", " << img->rows() << " -> " << ((int)round(px_w)) << ", " << ((int)round(px_h)) << endl;
img->resize((int)round(px_w), (int)round(px_h));
/* Blur image with a kernel larger than our minimum feature size to avoid aliasing. */
int blur_size = (int)ceil(fmax(img->cols() / width, img->rows() / height) * center_distance);
if (blur_size%2 == 0)
blur_size += 1;
cerr << "blur size " << blur_size << endl;
img->blur(blur_size);
/* Calculate voronoi diagram for the grid generated above. */
jcv_diagram diagram;
memset(&diagram, 0, sizeof(jcv_diagram));
cerr << "adjusted scale " << scale_x << " " << scale_y << endl;
cerr << "voronoi clip rect " << (scale_x * orig_cols) << " " << (scale_y * orig_rows) << endl;
jcv_rect rect {{0.0, 0.0}, {scale_x * orig_cols, scale_y * orig_rows}};
jcv_point *pts = reinterpret_cast<jcv_point *>(grid_centers->data()); /* hackety hack */
jcv_diagram_generate(grid_centers->size(), pts, &rect, 0, &diagram);
/* Relax points, i.e. wiggle them around a little bit to equalize differences between cell sizes a little bit. */
if (m_relax)
voronoi_relax_points(&diagram, pts);
memset(&diagram, 0, sizeof(jcv_diagram));
jcv_diagram_generate(grid_centers->size(), pts, &rect, 0, &diagram);
/* For each voronoi cell calculated above, find the brightness of the blurred image pixel below its center. We do
* not have to average over the entire cell's area here: The blur is doing a good approximation of that while being
* simpler and faster.
*
* We do this step before generating the cell poygons below because we have to look up a cell's neighbor's fill
* factor during gap filling for minimum feature size preservation. */
vector<double> fill_factors(diagram.numsites); /* Factor to be multiplied with site polygon radius to yield target
fill level */
const jcv_site* sites = jcv_diagram_get_sites(&diagram);
int j = 0;
for (int i=0; i<diagram.numsites; i++) {
const jcv_point center = sites[i].p;
double pxd = img->at(
(int)round(center.x / (scale_x * orig_cols / img->cols())),
(int)round(center.y / (scale_y * orig_rows / img->rows()))) / 255.0;
/* FIXME: This is a workaround for a memory corruption bug that happens with the square-grid setting. When using
* square-grid on a fairly small test image, sometimes sites[i].index will be out of bounds here.
*/
if (sites[i].index < (int)fill_factors.size())
fill_factors[sites[i].index] = sqrt(pxd);
}
/* Minimum gap between adjacent scaled site polygons. */
double min_gap_px = min_feature_size_px;
vector<double> adjusted_fill_factors;
adjusted_fill_factors.reserve(32); /* Vector to hold adjusted fill factors for each edge for gap filling */
/* now iterate over all voronoi cells again to generate each cell's scaled polygon halftone blob. */
//cerr << " generating cells " << diagram.numsites << endl;
for (int i=0; i<diagram.numsites; i++) {
const jcv_point center = sites[i].p;
//cerr << " site center " << center.x << ", " << center.y << endl;
double fill_factor_ours = fill_factors[sites[i].index];
/* Do not render halftone blobs that are too small */
if (fill_factor_ours * 0.5 * center_distance < min_gap_px)
continue;
/* Iterate over this cell's edges. For each edge, check the gap that would result between this cell's halftone
* blob and the neighboring cell's halftone blob based on their fill factors. If the gap is too small, either
* widen it by adjusting both fill factors down a bit (for this edge only!), or eliminate it by setting both
* fill factors to 1.0 (again, for this edge only!). */
adjusted_fill_factors.clear();
const jcv_graphedge* e = sites[i].edges;
while (e) {
/* half distance between both neighbors of this edge, i.e. sites[i] and its neighbor. */
/* Note that in a voronoi tesselation, this edge is always halfway between. */
double adjusted_fill_factor = fill_factor_ours;
if (e->neighbor != nullptr) { /* nullptr -> edge is on the voronoi map's border */
double rad = sqrt(pow(center.x - e->neighbor->p.x, 2) + pow(center.y - e->neighbor->p.y, 2)) / 2.0;
double fill_factor_theirs = fill_factors[e->neighbor->index];
double gap_px = (1.0 - fill_factor_ours) * rad + (1.0 - fill_factor_theirs) * rad;
if (gap_px > min_gap_px) {
/* all good. gap is wider than minimum. */
} else if (gap_px > 0.5 * min_gap_px) {
/* gap is narrower than minimum, but more than half of minimum width. */
/* force gap open, distribute adjustment evenly on left/right */
double fill_factor_adjustment = (min_gap_px - gap_px) / 2.0 / rad;
adjusted_fill_factor -= fill_factor_adjustment;
} else {
/* gap is less than half of minimum width. Force gap closed. */
adjusted_fill_factor = 1.0;
}
}
adjusted_fill_factors.push_back(adjusted_fill_factor);
e = e->next;
}
//cerr << " blob: ";
/* Now, generate the actual halftone blob polygon */
ClipperLib::Path cell_path;
double last_fill_factor = adjusted_fill_factors.back();
e = sites[i].edges;
j = 0;
while (e) {
double fill_factor = adjusted_fill_factors[j];
if (last_fill_factor != fill_factor) {
/* Fill factor was adjusted since last edge, so generate one extra point so we have a nice radial
* "step". */
d2p p = img_ctx.mat().doc2phys(d2p{
off_x + center.x + (e->pos[0].x - center.x) * fill_factor,
off_y + center.y + (e->pos[0].y - center.y) * fill_factor
});
//cerr << " - <" << p[0] << ", " << p[1] << ">";
cell_path.push_back({
(ClipperLib::cInt)round(p[0] * clipper_scale),
(ClipperLib::cInt)round(p[1] * clipper_scale)
});
}
/* Emit endpoint of current edge */
d2p p = img_ctx.mat().doc2phys(d2p{
off_x + center.x + (e->pos[1].x - center.x) * fill_factor,
off_y + center.y + (e->pos[1].y - center.y) * fill_factor
});
//cerr << " - [" << p[0] << ", " << p[1] << "]";
cell_path.push_back({
(ClipperLib::cInt)round(p[0] * clipper_scale),
(ClipperLib::cInt)round(p[1] * clipper_scale)
});
j += 1;
last_fill_factor = fill_factor;
e = e->next;
}
//cerr << endl;
/* Now, clip the halftone blob generated above against the given clip path. We do this individually for each
* blob since this way is *much* faster than throwing a million blobs at once at poor clipper. */
ClipperLib::Paths polys;
ClipperLib::Clipper c;
c.AddPath(cell_path, ClipperLib::ptSubject, /* closed */ true);
if (!img_ctx.clip().empty()) {
c.AddPaths(img_ctx.clip(), ClipperLib::ptClip, /* closed */ true);
}
c.StrictlySimple(true);
c.Execute(ClipperLib::ctIntersection, polys, ClipperLib::pftNonZero, ClipperLib::pftNonZero);
/* Export halftone blob to gerber. */
for (const auto &poly : polys) {
vector<array<double, 2>> out;
for (const auto &p : poly)
out.push_back(std::array<double, 2>{
((double)p.X) / clipper_scale, ((double)p.Y) / clipper_scale
});
img_ctx.sink() << GRB_POL_DARK << out;
}
}
jcv_diagram_free( &diagram );
delete grid_centers;
delete img;
}
void gerbolyze::handle_aspect_ratio(string spec, double &scale_x, double &scale_y, double &off_x, double &off_y, double cols, double rows) {
if (spec.empty()) {
spec = "xMidYMid meet";
}
auto idx = spec.find(" ");
string par_align = spec;
string par_meet = "meet";
if (idx != string::npos) {
par_align = spec.substr(0, idx);
par_meet = spec.substr(idx+1);
}
if (par_align != "none") {
double scale = scale_x;
if (par_meet == "slice") {
scale = std::max(scale_x, scale_y);
} else {
scale = std::min(scale_x, scale_y);
}
std::regex reg("x(Min|Mid|Max)Y(Min|Mid|Max)");
std::smatch match;
off_x = (scale_x - scale) * cols;
off_y = (scale_y - scale) * rows;
if (std::regex_match(par_align, match, reg)) {
assert (match.size() == 3);
if (match[1].str() == "Min") {
off_x = 0;
} else if (match[1].str() == "Mid") {
off_x *= 0.5;
}
if (match[2].str() == "Min") {
off_y = 0;
} else if (match[2].str() == "Mid") {
off_y *= 0.5;
}
} else {
cerr << "Invalid preserveAspectRatio meetOrSlice value \"" << par_align << "\"" << endl;
off_x *= 0.5;
off_y *= 0.5;
}
scale_x = scale_y = scale;
}
}
void gerbolyze::OpenCVContoursVectorizer::vectorize_image(RenderContext &ctx, const pugi::xml_node &node, double min_feature_size_px) {
(void) min_feature_size_px; /* unused by this vectorizer */
double x, y, width, height;
parse_img_meta(node, x, y, width, height);
nopencv::Image32 *img = img_from_node<int32_t>(node);
if (img == nullptr)
return;
/* Set up target transform using SVG transform and x/y attributes */
RenderContext img_ctx(ctx, xform2d(1, 0, 0, 1, x, y));
double scale_x = (double)width / (double)img->cols();
double scale_y = (double)height / (double)img->rows();
double off_x = 0;
double off_y = 0;
handle_aspect_ratio(node.attribute("preserveAspectRatio").value(),
scale_x, scale_y, off_x, off_y, img->cols(), img->rows());
draw_bg_rect(img_ctx, width, height);
img->binarize(128);
nopencv::find_contours(*img,
nopencv::simplify_contours_douglas_peucker(
[&img_ctx, off_x, off_y, scale_x, scale_y](Polygon_i& poly, nopencv::ContourPolarity pol) {
if (pol == nopencv::CP_HOLE) {
std::reverse(poly.begin(), poly.end());
img_ctx.sink() << GRB_POL_CLEAR;
} else {
img_ctx.sink() << GRB_POL_DARK;
}
ClipperLib::Path out;
for (const auto &p : poly) {
d2p q = img_ctx.mat().doc2phys(d2p{
off_x + (double)p[0] * scale_x,
off_y + (double)p[1] * scale_y
});
out.push_back({
(ClipperLib::cInt)round(q[0] * clipper_scale),
(ClipperLib::cInt)round(q[1] * clipper_scale)
});
}
ClipperLib::Clipper c;
c.AddPath(out, ClipperLib::ptSubject, /* closed */ true);
if (!img_ctx.clip().empty()) {
c.AddPaths(img_ctx.clip(), ClipperLib::ptClip, /* closed */ true);
}
c.StrictlySimple(true);
ClipperLib::Paths polys;
c.Execute(ClipperLib::ctIntersection, polys, ClipperLib::pftNonZero, ClipperLib::pftNonZero);
/* Draw into gerber. */
for (const auto &poly : polys) {
vector<array<double, 2>> out;
for (const auto &p : poly)
out.push_back(std::array<double, 2>{
((double)p.X) / clipper_scale, ((double)p.Y) / clipper_scale
});
img_ctx.sink() << out;
}
}));
}
gerbolyze::VectorizerSelectorizer::VectorizerSelectorizer(const string default_vectorizer, const string defs)
: m_default(default_vectorizer) {
istringstream foo(defs);
string elem;
while (std::getline(foo, elem, ',')) {
size_t pos = elem.find_first_of("=");
if (pos == string::npos) {
cerr << "Error parsing vectorizer selection string at element \"" << elem << "\"" << endl;
continue;
}
const string parsed_id = elem.substr(0, pos);
const string mapping = elem.substr(pos+1);
m_map[parsed_id] = mapping;
}
/*
cerr << "parsed " << m_map.size() << " vectorizers" << endl;
for (auto &elem : m_map) {
cerr << " " << elem.first << " -> " << elem.second << endl;
}
*/
}
ImageVectorizer *gerbolyze::VectorizerSelectorizer::select(const pugi::xml_node &img) {
const string id = img.attribute("id").value();
// cerr << "selecting vectorizer for image \"" << id << "\"" << endl;
if (m_map.count(id) > 0) {
// cerr << " -> found" << endl;
return makeVectorizer(m_map[id]);
}
// cerr << " -> default" << endl;
return makeVectorizer(m_default);
}