// 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 "test_precomp.hpp"

namespace opencv_test { namespace {

//helps to temporarily change the number of threads and restore it back after the scope
struct CvNThreadScope{
    int nprev;
    CvNThreadScope(int n){
        nprev=cv::getNumThreads();
        cv::setNumThreads(n);
    }
    ~CvNThreadScope(){
        cv::setNumThreads(nprev);
    }
};

// Order-independent contour-set comparison
static bool trucoContoursMatch(const vector<vector<Point>>& cont1, const vector<vector<Point>>& cont2)
{
        //order senstive hash
    auto Hash=[](const std::vector<cv::Point>& contour) {
        // FNV-1a 64-bit hash constants
        constexpr uint64_t FNV_OFFSET = 1469598103934665603ULL;
        constexpr uint64_t FNV_PRIME  = 1099511628211ULL;

        uint64_t hash = FNV_OFFSET;

        // Mix in the size so that contours with different lengths
        // but same prefix produce different hashes
        uint64_t size = static_cast<uint64_t>(contour.size());
        for (int i = 0; i < 8; ++i) {
            hash ^= (size >> (i * 8)) & 0xFF;
            hash *= FNV_PRIME;
        }

        // Mix in each point's x and y coordinates byte by byte
        for (const cv::Point& p : contour) {
            uint32_t x = static_cast<uint32_t>(p.x);
            uint32_t y = static_cast<uint32_t>(p.y);

            for (int i = 0; i < 4; ++i) {
                hash ^= (x >> (i * 8)) & 0xFF;
                hash *= FNV_PRIME;
            }
            for (int i = 0; i < 4; ++i) {
                hash ^= (y >> (i * 8)) & 0xFF;
                hash *= FNV_PRIME;
            }
        }
        return hash;
    };
    std::set<uint64> hashes1,hashes2;
    for(auto &contour:cont1){
        hashes1.insert( Hash(contour));
    }
    for(auto &contour:cont2){
        hashes2.insert( Hash(contour));
    }

    for(auto &h1:hashes1){//element in cont and not in cont2
        if( hashes2.find(h1) ==hashes2.end()) return false;
    }
    return true;
}

typedef testing::TestWithParam<ContourApproximationModes> Imgproc_FindTRUContours;

TEST_P(Imgproc_FindTRUContours, nthreads_consistency)
{
    ContourApproximationModes method = GetParam();
    const Size sz(1000, 1000);
    RNG& rng = TS::ptr()->get_rng();
    Mat noise(sz, CV_8UC1);
    cvtest::randUni(rng, noise, 0, 255);
    Mat blurred;
    boxFilter(noise, blurred, CV_8U, Size(5, 5));
    Mat img;
    cv::threshold(blurred, img, 128, 255, THRESH_BINARY);

    vector<vector<Point>> ref_contours;
    vector<vector<Point>> ref_contours_m0;
    {
        CvNThreadScope nt(1);
        findContours(img, ref_contours, RETR_LIST, method);
    }

    std::vector<int> thread_counts;
    for(int i=2;i<40;i++) thread_counts.push_back(i);
    for (int t : thread_counts)
    {
        SCOPED_TRACE(cv::format("nthreads=%d method=%d", t, (int)method));
        CvNThreadScope nt(t);
        vector<vector<Point>> contours;
        findContours(img, contours, RETR_LIST, method); //will use TRUCO because NOT using hierarchy AND RETR_LIST
        auto match=trucoContoursMatch(ref_contours, contours);
        EXPECT_TRUE(match);
    }
}

TEST_P(Imgproc_FindTRUContours, circles_vs_standard)
{
    ContourApproximationModes method = GetParam();
    const Size sz(4000, 4000);
    const int ITER = cvtest::debugLevel >= 10?100:10;
    const int NUM_CIRCLES = 250;
    RNG& rng = TS::ptr()->get_rng();

    for (int iter = 0; iter < ITER; ++iter)
    {
        SCOPED_TRACE(cv::format("iter=%d method=%d", iter, (int)method));
        Mat img(sz, CV_8UC1, Scalar::all(0));
        for (int i = 0; i < NUM_CIRCLES; ++i)
        {
            Point center(rng.uniform(50, sz.width  - 50),
                         rng.uniform(50, sz.height - 50));
            int radius = rng.uniform(10, 150);
            circle(img, center, radius, Scalar::all(255), FILLED);
        }
        Mat binary;
        adaptiveThreshold(img, binary, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 11, 0);

        vector<vector<Point>> ref_contours;
        vector<Vec4i> hierarchy;
        findContours(binary, ref_contours, hierarchy, RETR_LIST, method); //will call suzuki abe because using hierarchy
        EXPECT_TRUE(!hierarchy.empty());
        vector<vector<Point>> truco_contours;
        findContours(binary, truco_contours, RETR_LIST, method);
        EXPECT_TRUE(trucoContoursMatch(ref_contours, truco_contours)); //will use TRUCO because NOT using hierarchy AND RETR_LIST
    }
}

TEST_P(Imgproc_FindTRUContours, noise_threshold)
{
    ContourApproximationModes method = GetParam();
    const Size sz(1500, 1500);
    RNG& rng = TS::ptr()->get_rng();
    const int levels[] = {86, 128, 170};
    const int ITER = 2;

    std::vector<int> thread_counts;
    for(int i=2; i<40; i+=3) thread_counts.push_back(i);
    for(int i=0; i<ITER; i++)
    {
        for (int level : levels)
        {
            SCOPED_TRACE(cv::format("level=%d method=%d", level, (int)method));
            Mat noise(sz, CV_8UC1);
            cvtest::randUni(rng, noise, 0, 255);
            Mat blurred;
            boxFilter(noise, blurred, CV_8U, Size(5, 5));
            Mat binary;
            cv::threshold(blurred, binary, level, 255, THRESH_BINARY);

            vector<vector<Point>> ref_contours;
            vector<Vec4i> hierarchy;
            findContours(binary, ref_contours, hierarchy, RETR_LIST, method);//will call suzuki&abe because using hierarchy
            EXPECT_TRUE(!hierarchy.empty());
            for(auto nt: thread_counts){
                CvNThreadScope ts(nt);
                vector<vector<Point>> truco_contours;
                findContours(binary, truco_contours,  RETR_LIST, method);//will call TRUCO abe because NOT using hierarchy
                EXPECT_TRUE(trucoContoursMatch(ref_contours, truco_contours));
            }
        }
    }
}

TEST_P(Imgproc_FindTRUContours, nested_rectangles)
{
    ContourApproximationModes method = GetParam();
    const int DIM = 1500;
    const Size sz(DIM, DIM);
    const int NUM = 25;
    Mat img(sz, CV_8UC1, Scalar::all(0));
    Rect rect(1, 1, DIM - 2, DIM - 2);
    for (int i = 0; i < NUM; ++i)
    {
        rectangle(img, rect, Scalar::all(255));
        rect.x      += 10;
        rect.y      += 10;
        rect.width  -= 20;
        rect.height -= 20;
        if (rect.width <= 0 || rect.height <= 0)
            break;
    }

    vector<vector<Point>> ref_contours;
    vector<Vec4i> hierarchy;
    findContours(img, ref_contours, hierarchy, RETR_LIST, method);//will call suzuki abe because using hierarchy
    EXPECT_TRUE(!hierarchy.empty());

    vector<vector<Point>> truco_contours;
    findContours(img, truco_contours, RETR_LIST, method);//will use TRUCO because NOT using hierarchy AND RETR_LIST

    EXPECT_TRUE(trucoContoursMatch(ref_contours, truco_contours));
}

TEST_P(Imgproc_FindTRUContours, mixed_figures)
{
    ContourApproximationModes method = GetParam();
    const Size sz(1800, 1600);
    RNG& rng = TS::ptr()->get_rng();
    const int ITER = cvtest::debugLevel >= 10?100:10;


    for (int iter = 0; iter < ITER; ++iter)
    {
        SCOPED_TRACE(cv::format("iter=%d method=%d", iter, (int)method));
        Mat img(sz, CV_8UC1, Scalar::all(0));
        for (int i = 0; i < 5; ++i)
        {
            Rect r(rng.uniform(10, sz.width / 2),
                   rng.uniform(10, sz.height / 2),
                   rng.uniform(20, 100),
                   rng.uniform(20, 100));
            r &= Rect(0, 0, sz.width - 1, sz.height - 1);
            rectangle(img, r, Scalar::all(255), FILLED);
        }
        for (int i = 0; i < 5; ++i)
        {
            Point center(rng.uniform(50, sz.width  - 50),
                         rng.uniform(50, sz.height - 50));
            int radius = rng.uniform(10, 50);
            circle(img, center, radius, Scalar::all(255), FILLED);
        }
        for (int i = 0; i < 3; ++i)
        {
            Point pts[3];
            for (auto& p : pts)
                p = Point(rng.uniform(10, sz.width - 10),
                          rng.uniform(10, sz.height - 10));
            const Point* ppts = pts;
            int npts = 3;
            fillPoly(img, &ppts, &npts, 1, Scalar::all(255));
        }
        vector<vector<Point>> ref_contours;
        vector<Vec4i> hierarchy;
        findContours(img, ref_contours, hierarchy, RETR_LIST, method);//will call suzuki abe because using hierarchy
        EXPECT_TRUE(!hierarchy.empty());
        vector<vector<Point>> truco_contours;
        findContours(img, truco_contours, RETR_LIST, method);//will use TRUCO because NOT using hierarchy AND RETR_LIST

        EXPECT_TRUE(trucoContoursMatch(ref_contours, truco_contours));
    }
}

INSTANTIATE_TEST_CASE_P(Imgproc, Imgproc_FindTRUContours,
    testing::Values(CHAIN_APPROX_NONE,CHAIN_APPROX_SIMPLE, CHAIN_APPROX_TC89_L1, CHAIN_APPROX_TC89_KCOS));

}} // namespace