Fixed bug when generating identical fanouts
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// Example 13 — Debug Cell-Shading Pipeline with Tiled Debug Canvas
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//
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// An improved cell-shading pipeline where every processing node performs
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// exactly one OpenCV operation. A variadic DebugCanvas<N> node tiles N
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// cv::Mat inputs into a single debug window, making each pipeline stage
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// visible side-by-side at runtime.
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//
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// Improvements over example 12:
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// - Bilateral filter before quantisation (edge-preserving smoothing):
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// flattens colour regions without softening object edges
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// - Dilated edge mask for bolder black outlines
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// - 6-level quantisation for richer tonal detail
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//
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// Topology (auto-fanouts inserted by make_network):
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//
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// [capture]──┬──> [bilateral]──> [quant]──┬──> [comp]──> [debug:0 result]
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// │ └──> [debug:1 quantised]
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// ├──> [to_gray]──> [blur]──> [canny]──┬──> [dilate]──> [comp]
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// │ └──> [debug:2 edges]
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// └──> [debug:3 original]
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//
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// make_network detects the 3-way fan from [capture], the 2-way fan from
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// [quant], and the 2-way fan from [canny], inserting FanoutNode instances
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// automatically.
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#include <kpn/kpn.hpp>
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#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/videoio.hpp>
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#include <algorithm>
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#include <chrono>
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#include <cmath>
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#include <iostream>
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#include <string>
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#include <thread>
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#include <type_traits>
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#include <vector>
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// ── Synthetic source for environments without a webcam ───────────────────────
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static cv::Mat make_gradient(int W, int H) {
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cv::Mat xr(H, W, CV_8UC1), yg(H, W, CV_8UC1), b(H, W, CV_8UC1, cv::Scalar(128));
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for (int x = 0; x < W; ++x) xr.col(x).setTo(x * 255 / W);
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for (int y = 0; y < H; ++y) yg.row(y).setTo(y * 255 / H);
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cv::Mat channels[3] = {b, yg, xr};
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cv::Mat grad;
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cv::merge(channels, 3, grad);
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return grad;
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}
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// ── Pipeline nodes — one cv:: call per function ───────────────────────────────
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static cv::Mat capture() {
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constexpr int W = 640, H = 480;
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static cv::VideoCapture cap;
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static bool opened = false;
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if (!opened) {
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opened = true;
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cap.open(0, cv::CAP_V4L2);
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if (cap.isOpened()) {
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cap.set(cv::CAP_PROP_FRAME_WIDTH, W);
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cap.set(cv::CAP_PROP_FRAME_HEIGHT, H);
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} else {
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std::cerr << "[capture] no webcam — using synthetic animated pattern\n";
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}
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}
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cv::Mat frame;
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if (cap.isOpened()) {
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auto t0 = std::chrono::steady_clock::now();
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cap >> frame;
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auto elapsed = std::chrono::steady_clock::now() - t0;
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if (elapsed < std::chrono::milliseconds(20))
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std::this_thread::sleep_for(std::chrono::milliseconds(33) - elapsed);
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if (frame.empty()) frame = cv::Mat::zeros(H, W, CV_8UC3);
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} else {
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static int tick = 0;
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static cv::Mat grad = make_gradient(W, H);
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++tick;
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frame = grad.clone();
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int r = 150 + (tick % 80) * 4;
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cv::circle(frame, {W/2, H/2}, r, {255, 200, 0}, -1);
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cv::circle(frame, {W/2, H/2}, r / 2, { 0, 128, 255}, -1);
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cv::circle(frame, {W*2/5, H*2/5}, r / 3, {200, 0, 200}, -1);
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std::this_thread::sleep_for(std::chrono::milliseconds(33));
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}
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return frame.clone();
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}
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// Edge-preserving smooth: flattens colour within regions while keeping sharp
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// boundaries — much better than Gaussian blur as a pre-quantisation step.
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static cv::Mat bilateral_filter(cv::Mat bgr) {
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cv::Mat out;
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cv::bilateralFilter(bgr, out, 5, 75, 75);
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return out;
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}
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// Snap each channel to N discrete tonal levels.
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static cv::Mat quantise(cv::Mat bgr) {
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constexpr int levels = 6;
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constexpr double step = 256.0 / levels;
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static const cv::Mat lut = []() {
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cv::Mat l(1, 256, CV_8UC1);
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for (int i = 0; i < 256; ++i)
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l.at<uchar>(i) = cv::saturate_cast<uchar>(
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std::floor(i / step) * step + step / 2.0);
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return l;
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}();
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cv::Mat out;
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cv::LUT(bgr, lut, out);
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return out;
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}
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// BGR → greyscale; the edge path works on the original (not bilateral-filtered)
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// frame so that fine edge detail is preserved.
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static cv::Mat to_gray(cv::Mat bgr) {
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cv::Mat gray;
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cv::cvtColor(bgr, gray, cv::COLOR_BGR2GRAY);
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return gray;
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}
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// Suppress high-frequency noise before the Canny detector.
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static cv::Mat gaussian_blur(cv::Mat gray) {
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cv::Mat out;
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cv::GaussianBlur(gray, out, {5, 5}, 0);
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return out;
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}
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// Detect strong edges; returns a binary mask (CV_8UC1).
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static cv::Mat canny_edges(cv::Mat blurred) {
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cv::Mat out;
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cv::Canny(blurred, out, 50, 150);
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return out;
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}
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// Widen the edge mask for bolder cartoon outlines.
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static cv::Mat dilate_edges(cv::Mat edges) {
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static const cv::Mat kernel = cv::getStructuringElement(cv::MORPH_RECT, {3, 3});
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cv::Mat out;
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cv::dilate(edges, out, kernel);
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return out;
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}
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// Burn black outlines into the quantised colour image.
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static cv::Mat composite(cv::Mat quantised, cv::Mat thick_edges) {
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cv::Mat result = quantised.clone();
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result.setTo(cv::Scalar(0, 0, 0), thick_edges);
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return result;
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}
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// ── DebugCanvas<N> ────────────────────────────────────────────────────────────
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//
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// Variadic MainThreadNode that accepts N cv::Mat inputs (any mix of BGR and
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// greyscale) and tiles them into one debug window arranged as a
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// ceil(sqrt(N)) × ceil(N/cols) grid.
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//
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// Template trick: MatArg<I> aliases cv::Mat for all I, so the pack expansion
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// MatArg<0>, MatArg<1>, ..., MatArg<N-1>
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// produces exactly N cv::Mat arguments — enough to drive the MainThreadNode
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// base without manually spelling out the type N times.
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template<std::size_t>
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using MatArg = cv::Mat;
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template<std::size_t N>
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class DebugCanvas;
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template<std::size_t N, typename Seq = std::make_index_sequence<N>>
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struct DebugCanvasBase;
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template<std::size_t N, std::size_t... Is>
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struct DebugCanvasBase<N, std::index_sequence<Is...>> {
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using type = kpn::MainThreadNode<DebugCanvas<N>, kpn::in<>, MatArg<Is>...>;
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};
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template<std::size_t N>
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class DebugCanvas : public DebugCanvasBase<N>::type {
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using Base = typename DebugCanvasBase<N>::type;
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public:
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static constexpr std::string_view label() { return "debug_canvas"; }
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static constexpr std::size_t unique_tag = 0;
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explicit DebugCanvas(std::vector<std::string> slot_labels = {},
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std::size_t fifo_cap = 4)
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: Base(fifo_cap), labels_(std::move(slot_labels))
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{
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cv::namedWindow("Debug Canvas", cv::WINDOW_NORMAL);
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cv::resizeWindow("Debug Canvas", cols() * CW, rows() * CH);
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}
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~DebugCanvas() { cv::destroyWindow("Debug Canvas"); }
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// Called by MainThreadNode::step() with exactly N cv::Mat arguments.
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template<typename... Ms>
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bool operator()(Ms&&... mats) {
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static_assert(sizeof...(Ms) == N, "DebugCanvas: wrong number of inputs");
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std::vector<cv::Mat> imgs;
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imgs.reserve(N);
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(imgs.push_back(to_bgr(std::forward<Ms>(mats))), ...);
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cv::imshow("Debug Canvas", tile(imgs));
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int key = cv::waitKey(1);
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if (key == 'q' || key == 27) return false;
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try { return cv::getWindowProperty("Debug Canvas", cv::WND_PROP_VISIBLE) >= 1; }
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catch (const cv::Exception&) { return false; }
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}
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private:
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static constexpr int CW = 640, CH = 480;
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static int cols() { return std::max(1, (int)std::ceil(std::sqrt((double)N))); }
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static int rows() { return ((int)N + cols() - 1) / cols(); }
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std::vector<std::string> labels_;
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static cv::Mat to_bgr(const cv::Mat& m) {
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if (m.channels() == 1) {
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cv::Mat bgr;
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cv::cvtColor(m, bgr, cv::COLOR_GRAY2BGR);
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return bgr;
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}
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return m;
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}
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cv::Mat tile(const std::vector<cv::Mat>& imgs) const {
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const int c = cols(), r = rows();
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cv::Mat canvas(r * CH, c * CW, CV_8UC3, cv::Scalar(30, 30, 30));
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for (int i = 0; i < (int)imgs.size(); ++i) {
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if (imgs[i].empty()) continue;
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cv::Mat cell = canvas(cv::Rect((i % c) * CW, (i / c) * CH, CW, CH));
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cv::Mat resized;
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cv::resize(imgs[i], resized, {CW, CH});
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resized.copyTo(cell);
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if (i < (int)labels_.size() && !labels_[i].empty())
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cv::putText(cell, labels_[i], {8, 36},
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cv::FONT_HERSHEY_SIMPLEX, 1.0, {0, 255, 255}, 2,
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cv::LINE_AA);
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}
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return canvas;
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}
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};
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// ── main ──────────────────────────────────────────────────────────────────────
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int main() {
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using namespace kpn;
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auto src = make_node<capture, "capture" >(4);
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auto bilateral= make_node<bilateral_filter, "bilateral" >(4);
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auto quant = make_node<quantise, "quant" >(4);
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auto gray = make_node<to_gray, "to_gray" >(4);
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auto blur = make_node<gaussian_blur, "blur" >(4);
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auto canny = make_node<canny_edges, "canny" >(4);
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auto dilate = make_node<dilate_edges, "dilate" >(4);
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auto comp = make_node<composite, "comp" >(4);
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DebugCanvas<4> debug({"result", "quantised", "edges", "original"});
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// make_network auto-inserts FanoutNode instances wherever a source port
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// feeds more than one consumer:
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// capture → 3-way fanout (bilateral, to_gray, debug[3])
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// quant → 2-way fanout (comp, debug[1])
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// canny → 2-way fanout (dilate, debug[2])
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auto net = make_network(
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edge(src.output<0>(), bilateral.input<0>()), // frame → bilateral
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edge(src.output<0>(), gray.input<0>()), // frame → to_gray
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edge(src.output<0>(), debug.input<3>()), // frame → debug[3] original
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edge(bilateral.output<0>(), quant.input<0>()), // smooth → quant
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edge(quant.output<0>(), comp.input<0>()), // quant → comp
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edge(quant.output<0>(), debug.input<1>()), // quant → debug[1] quantised
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edge(gray.output<0>(), blur.input<0>()), // gray → blur
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edge(blur.output<0>(), canny.input<0>()), // blurred→ canny
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edge(canny.output<0>(), dilate.input<0>()), // edges → dilate
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edge(canny.output<0>(), debug.input<2>()), // edges → debug[2] edges
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edge(dilate.output<0>(), comp.input<1>()), // thick → comp
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edge(comp.output<0>(), debug.input<0>()) // result → debug[0] result
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);
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std::cout << "Debug cell-shading pipeline running — press 'q' to stop.\n";
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std::cout << "Canvas: [0] result [1] quantised [2] edges [3] original\n";
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net.start();
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while (debug.step())
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cv::waitKey(8);
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net.stop();
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return 0;
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}
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