cleanupFinal

samples/CMakeLists.txt

@@ -23,6 +23,7 @@ endif()
 add_subdirectory(cpp)
 add_subdirectory(java/tutorial_code)
 add_subdirectory(dnn)
+add_subdirectory(slam)
 add_subdirectory(gpu)
 add_subdirectory(tapi)
 add_subdirectory(opencl)
@@ -124,6 +125,7 @@ if(WIN32)
   add_subdirectory(directx)
 endif()
 add_subdirectory(dnn)
+add_subdirectory(slam)
 # add_subdirectory(gpu)
 add_subdirectory(opencl)
 add_subdirectory(sycl)

samples/slam/CMakeLists.txt

@@ -0,0 +1,22 @@
+ocv_install_example_src(slam *.cpp *.hpp CMakeLists.txt)
+
+set(OPENCV_SLAM_SAMPLES_REQUIRED_DEPS
+  opencv_core
+  opencv_dnn
+  opencv_features
+  opencv_slam)
+ocv_check_dependencies(${OPENCV_SLAM_SAMPLES_REQUIRED_DEPS})
+
+if(NOT BUILD_EXAMPLES OR NOT OCV_DEPENDENCIES_FOUND)
+  return()
+endif()
+
+project(slam_samples)
+ocv_include_modules_recurse(${OPENCV_SLAM_SAMPLES_REQUIRED_DEPS})
+include_directories("${CMAKE_CURRENT_SOURCE_DIR}/../dnn")
+
+file(GLOB_RECURSE slam_samples RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *.cpp)
+foreach(sample_filename ${slam_samples})
+  ocv_define_sample(tgt ${sample_filename} slam)
+  ocv_target_link_libraries(${tgt} PRIVATE ${OPENCV_LINKER_LIBS} ${OPENCV_SLAM_SAMPLES_REQUIRED_DEPS})
+endforeach()

samples/slam/visual_odometry.cpp

@@ -0,0 +1,63 @@
+// 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.
+// 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>
+#include <opencv2/dnn.hpp>
+#include <opencv2/core.hpp>
+#include <iostream>
+
+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";
+
+// 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()
+{
+    ALIKED::Params p;
+    p.inputSize = Size(640, 640);
+    p.engine    = dnn::ENGINE_NEW;
+    return ALIKED::create(ALIKED_MODEL, p);
+}
+
+static Ptr<DescriptorMatcher> makeMatcher()
+{
+    return LightGlueMatcher::create(LIGHTGLUE_MODEL, 0.0f,
+                                    dnn::DNN_BACKEND_DEFAULT,
+                                    dnn::DNN_TARGET_CPU);
+}
+
+int main()
+{
+    slam::OdometryParams params;
+    params.minInitParallaxDeg = 1.5;
+    params.minInitPoints      = 50;
+
+    auto vo = slam::VisualOdometry::create(
+        makeDetector(), makeMatcher(),
+        IMAGES_DIR, OUTPUT_DIR,
+        Mat(K), Mat(DIST), params);
+
+    const int64 t0      = getTickCount();
+    const bool  ok      = vo->run();
+    const double elapsed = (getTickCount() - t0) / getTickFrequency();
+
+    std::cout << "run=" << (ok ? "ok" : "FAILED")
+              << "  frames=" << vo->getTrajectory().size()
+              << "  elapsed=" << elapsed << "s\n"
+              << "output -> " << OUTPUT_DIR << "\n";
+    return ok ? 0 : 1;
+}

samples/slam/visual_odometry.py

@@ -0,0 +1,56 @@
+'''
+Monocular visual odometry with cv.slam.VisualOdometry (ALIKED + LightGlue).
+'''
+
+import time
+import numpy as np
+import cv2 as cv
+
+ALIKED_MODEL    = '/media/user/path/to/models/aliked-n16rot-top1k-640.onnx'
+LIGHTGLUE_MODEL = '/media/user/path/to/models/aliked_lightglue.onnx'
+IMAGES_DIR      = '/media/user/path/to/dataset'
+OUTPUT_DIR      = 'vo_out'
+
+# KITTI-00: fx, fy, cx, cy
+K = np.array([[718.856, 0.,      607.1928],
+              [0.,      718.856, 185.2157],
+              [0.,      0.,      1.      ]], dtype=np.float64)
+
+# k1, k2, p1, p2, k3
+DIST = np.array([-0.2811, 0.0723, -0.0003, 0.0001, 0.0], dtype=np.float64)
+
+
+def make_detector():
+    p = cv.ALIKED.Params()
+    p.inputSize = (640, 640)
+    p.engine    = cv.dnn.ENGINE_NEW
+    return cv.ALIKED.create(ALIKED_MODEL, p)
+
+
+def make_matcher():
+    return cv.LightGlueMatcher.create(
+        LIGHTGLUE_MODEL, 0.0,
+        cv.dnn.DNN_BACKEND_DEFAULT,
+        cv.dnn.DNN_TARGET_CPU)
+
+
+def main():
+    params = cv.slam.OdometryParams()
+    params.minInitParallaxDeg = 1.5
+    params.minInitPoints      = 50
+
+    vo = cv.slam.VisualOdometry.create(
+        make_detector(), make_matcher(),
+        IMAGES_DIR, OUTPUT_DIR,
+        K, DIST, params)
+
+    t0 = time.perf_counter()
+    ok = vo.run()
+    elapsed = time.perf_counter() - t0
+
+    print(f"run={'ok' if ok else 'FAILED'}  frames={len(vo.getTrajectory())}  elapsed={elapsed:.2f}s")
+    print(f"output -> {OUTPUT_DIR}")
+
+
+if __name__ == '__main__':
+    main()