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Yang Guanyuhan
527f01449d
[GSOC] feat: Add ALIKED feature extractor and LightGlue matcher with DNN integration #28986 ## PR Description ### Summary Integrate ALIKED and LightGlue into OpenCV's `features` module as native`Feature2D` and `DescriptorMatcher` implementations, enabling end-to-end neural feature matching within OpenCV's ecosystem. --- ### What's included #### New classes - **`cv::ALIKED`** extends `Feature2D` - CNN-based keypoint detection - 128-D descriptor extraction via ONNX Runtime - **`cv::LightGlueMatcher`** extends `DescriptorMatcher` - Deep feature matching with spatial context - Uses keypoints and image sizes during matching --- #### API design - Standard OpenCV patterns: - `detectAndCompute()` - `match()` - `knnMatch()` - Multiple factory methods: - ONNX model path - In-memory model buffer - Pre-loaded `dnn::Net` - `Params` structs use `CV_EXPORTS_W_SIMPLE` for Python/Java bindings support - Optional DNN dependency: - `HAVE_OPENCV_DNN` guards - Stub implementations throw `StsNotImplemented` --- ### Files added | File | Description | |------|-------------| | `src/feature2d_aliked.cpp` | ALIKED implementation | | `src/matchers_lightglue.cpp` | LightGlueMatcher implementation | | `src/aliked_context.hpp` | Shared internal context struct | | `test/test_aliked_lightglue.cpp` | Unit tests (9 test cases) | | `samples/cpp/example_features_aliked_lightglue.cpp` | Demo application | --- ### Files modified - `CMakeLists.txt` - Add `opencv_dnn` as optional dependency - `features.hpp` - Add ALIKED and LightGlueMatcher declarations - `precomp.hpp` - Add DNN include guard --- ### Usage ```cpp // Feature extraction Ptr<ALIKED> aliked = ALIKED::create("aliked-n16rot-top1k-640.onnx"); vector<KeyPoint> kpts; Mat descs; aliked->detectAndCompute(image, Mat(), kpts, descs); // Feature matching Ptr<LightGlueMatcher> lg = LightGlueMatcher::create("aliked_lightglue.onnx"); lg->setPairInfo( kpts1Mat, kpts2Mat, img1.size(), img2.size() ); vector<DMatch> matches; lg->match(descs1, descs2, matches); ```` please refer to samples/cpp/example_features_aliked_lightglue.cpp --- ### Test plan * Build with `BUILD_LIST=features,dnn` * Build without DNN: * Verify stubs compile * Verify `StsNotImplemented` is thrown * Run: * `ctest -R Features2d_ALIKED` * `ctest -R Features2d_LightGlueMatcher` * Run sample application with: * Real images * Real ONNX models * Verify Python/Java bindings compile and work --- ### Related Phase 1 of the "End-to-End AI Feature Extraction and LightGlue Matching Pipeline" GSoC project. Designed to be extensible to: * XFeat * SuperPoint * Other neural feature extractors ### test dependency Depends on the opencv_extra PR adding ALIKED and LightGlue test models: - [opencv_extra PR](https://github.com/opencv/opencv_extra/pull/1366) This PR adds the following ONNX models to `download_models.py`: - `aliked-n16rot-top1k-640.onnx` - `aliked_lightglue.onnx` These models are required for the `features2d` tests in the main OpenCV repository to validate the ALIKED and LightGlue feature extraction and matching pipeline. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake