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2026-07-13 12:06:04 +08:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
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// Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
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// this list of conditions and the following disclaimer.
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#include "perf_precomp.hpp"
#include <algorithm>
#include <functional>
namespace opencv_test
{
using namespace perf;
CV_ENUM(Method, RANSAC, LMEDS)
typedef tuple<int, double, Method, size_t> TranslationParams;
typedef TestBaseWithParam<TranslationParams> EstimateTranslation2DPerf;
#define ESTIMATE_PARAMS Combine(Values(1000), Values(0.95), Method::all(), Values(10, 0))
static float rngIn(float from, float to) { return from + (to - from) * (float)theRNG(); }
static cv::Mat rngTranslationMat()
{
double tx = rngIn(-2.f, 2.f);
double ty = rngIn(-2.f, 2.f);
double t[2*3] = { 1.0, 0.0, tx,
0.0, 1.0, ty };
return cv::Mat(2, 3, CV_64F, t).clone();
}
PERF_TEST_P(EstimateTranslation2DPerf, EstimateTranslation2D, ESTIMATE_PARAMS)
{
TranslationParams params = GetParam();
const int n = get<0>(params);
const double confidence = get<1>(params);
const int method = get<2>(params);
const size_t refining = get<3>(params);
//fixed seed so the generated data are deterministic
cv::theRNG().state = 0x12345678;
// ground-truth pure translation
cv::Mat T = rngTranslationMat();
// LMEDS can't handle more than 50% outliers (by design)
int m;
if (method == LMEDS)
m = 3*n/5;
else
m = 2*n/5;
const float shift_outl = 15.f;
const float noise_level = 20.f;
cv::Mat fpts(1, n, CV_32FC2);
cv::Mat tpts(1, n, CV_32FC2);
randu(fpts, 0.f, 100.f);
transform(fpts, tpts, T);
// add outliers to the tail [m, n)
cv::Mat outliers = tpts.colRange(m, n);
outliers.reshape(1) += shift_outl;
cv::Mat noise(outliers.size(), outliers.type());
randu(noise, 0.f, noise_level);
outliers += noise;
cv::Vec2d T_est;
std::vector<uchar> inliers(n);
warmup(inliers, WARMUP_WRITE);
warmup(fpts, WARMUP_READ);
warmup(tpts, WARMUP_READ);
TEST_CYCLE()
{
T_est = estimateTranslation2D(fpts, tpts, inliers, method,
/*ransacReprojThreshold=*/3.0,
/*maxIters=*/2000,
/*confidence=*/confidence,
/*refineIters=*/refining);
}
// Convert to Mat for SANITY_CHECK consistency
cv::Mat T_est_mat = (cv::Mat_<double>(2,1) << T_est[0], T_est[1]);
SANITY_CHECK(T_est_mat, 1e-6);
}
} // namespace opencv_test