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better vo samples

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This commit is contained in:
Agrim Rai
2026-06-23 15:14:58 +05:30
parent 65c93e673d
commit a02eb6ad0f
2 changed files with 108 additions and 69 deletions
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samples/slam/visual_odometry.cpp
+57 -37
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@@ -2,7 +2,6 @@
// 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.
// Copyright (C) 2026, BigVision LLC, all rights reserved.
// Third party copyrights are property of their respective owners.
#include <opencv2/slam.hpp>
#include <opencv2/features.hpp>
@@ -12,52 +11,73 @@
using namespace cv;
static const char* ALIKED_MODEL = "/media/user/path/to/models/aliked-n16rot-top1k-640.onnx";
static const char* LIGHTGLUE_MODEL = "/media/user/path/to/models/aliked_lightglue.onnx";
static const char* IMAGES_DIR = "/media/user/path/to/dataset";
static const char* OUTPUT_DIR = "vo_out";
static const char* keys =
"{ help h | | Print help message }"
"{ aliked | <none> | Path to ALIKED ONNX model }"
"{ lightglue | <none> | Path to LightGlue ONNX model }"
"{ images | <none> | Path to directory with input images }"
"{ output | vo_out | Output directory for trajectory and map }"
"{ fx | 718.856 | Camera focal length X }"
"{ fy | 718.856 | Camera focal length Y }"
"{ cx | 607.1928 | Camera principal point X }"
"{ cy | 185.2157 | Camera principal point Y }"
"{ min-parallax | 1.5 | Minimum initialisation parallax in degrees }"
"{ min-points | 50 | Minimum initialisation map points }";
// KITTI-00: fx, fy, cx, cy
static const Matx33d K(718.856, 0., 607.1928,
0., 718.856, 185.2157,
0., 0., 1.);
// k1, k2, p1, p2, k3
static const std::vector<double> DIST = { -0.2811, 0.0723, -0.0003, 0.0001, 0.0 };
static Ptr<Feature2D> makeDetector()
int main(int argc, char** argv)
{
ALIKED::Params p;
p.inputSize = Size(640, 640);
p.engine = dnn::ENGINE_NEW;
return ALIKED::create(ALIKED_MODEL, p);
}
CommandLineParser parser(argc, argv, keys);
parser.about("Monocular visual odometry using ALIKED + LightGlue\n"
" Example: visual_odometry --aliked=aliked.onnx --lightglue=lg.onnx --images=./seq\n");
static Ptr<DescriptorMatcher> makeMatcher()
{
return LightGlueMatcher::create(LIGHTGLUE_MODEL, 0.0f,
dnn::DNN_BACKEND_DEFAULT,
dnn::DNN_TARGET_CPU);
}
if (parser.has("help"))
{
parser.printMessage();
return 0;
}
int main()
{
slam::OdometryParams params;
params.minInitParallaxDeg = 1.5;
params.minInitPoints = 50;
const String alikedPath = parser.get<String>("aliked");
const String lightgluePath = parser.get<String>("lightglue");
const String imagesDir = parser.get<String>("images");
if (!parser.check() || alikedPath == "<none>" || lightgluePath == "<none>" || imagesDir == "<none>")
{
parser.printErrors();
parser.printMessage();
return 1;
}
const String outputDir = parser.get<String>("output");
const Matx33d K(parser.get<double>("fx"), 0., parser.get<double>("cx"),
0., parser.get<double>("fy"), parser.get<double>("cy"),
0., 0., 1.);
ALIKED::Params detParams;
detParams.inputSize = Size(640, 640);
detParams.engine = dnn::ENGINE_NEW;
auto detector = ALIKED::create(alikedPath, detParams);
auto matcher = LightGlueMatcher::create(lightgluePath, 0.0f,
dnn::DNN_BACKEND_DEFAULT,
dnn::DNN_TARGET_CPU);
slam::OdometryParams voParams;
voParams.minInitParallaxDeg = parser.get<double>("min-parallax");
voParams.minInitPoints = parser.get<int>("min-points");
auto vo = slam::VisualOdometry::create(
makeDetector(), makeMatcher(),
IMAGES_DIR, OUTPUT_DIR,
Mat(K), Mat(DIST), params);
detector, matcher,
imagesDir, outputDir,
Mat(K), Mat(), voParams);
const int64 t0 = getTickCount();
const bool ok = vo->run();
const int64 t0 = getTickCount();
const bool ok = vo->run();
const double elapsed = (getTickCount() - t0) / getTickFrequency();
std::cout << "run=" << (ok ? "ok" : "FAILED")
std::cout << "run=" << (ok ? "ok" : "FAILED")
<< " frames=" << vo->getTrajectory().size()
<< " elapsed=" << elapsed << "s\n"
<< "output -> " << OUTPUT_DIR << "\n";
<< "output -> " << outputDir << "\n";
return ok ? 0 : 1;
}