Feat: Add OpenCL support for AKAZE features #28879
Implement OpenCL-accelerated AKAZE feature
detection and descriptor extraction
Benchmarked on RTX 5060 Ti: 1.2x to 3.31x faster
for image sizes from 640x480 to 3840x2160
- Added 8 OpenCL kernels for feature detection and descriptor extraction
- Refactored compute_kcontrast to use OpenCV magnitude() for consistency
- Added comprehensive tests with >95% accuracy vs CPU baseline
### 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
BFMatcher::match() with crossCheck=true previously skipped the OCL
dispatch in knnMatchImpl entirely, falling back to CPU even when UMat
inputs and an OpenCL device were available. This adds
ocl_matchWithCrossCheck() for CV_32FC1 descriptors (e.g. SIFT, SURF):
both the forward and reverse nearest-neighbour passes run on the GPU
via the existing ocl_matchSingle() kernel, then the cross-check filter
runs on the CPU. Only two small index arrays (1×N ints) are downloaded
— the O(N²×D) distance work stays on the device.
The OCL dispatch in knnMatchImpl is also refactored to unify the
Mat/UMat train collection selection before branching on crossCheck.
On a NVIDIA RTX 3060 with SIFT descriptors the OCL path is 6–9×
faster than CPU at 2k–10k features per image. Binary descriptors
(ORB, BRIEF — CV_8U) are unaffected; the existing type guard in
ocl_matchSingle keeps them on the CPU path as before.
Also adds a correctness test (Features2d_BFMatcher_CrossCheck) and an
OCL perf test (BruteForceMatcherFixture/MatchCrossCheck).
features2d: add missing KAZE DIFF_CHARBONNIER support #28324
### Description
This PR fixes the missing implementation for `DIFF_CHARBONNIER` diffusivity type in KAZE feature detector.
### Changes
- Added `charbonnier_diffusivity()` call for `DIFF_CHARBONNIER` type in `Create_Nonlinear_Scale_Space()`
- Added proper error handling for unsupported diffusivity types
### Problem
When using KAZE with `DIFF_CHARBONNIER` diffusivity type, keypoint coordinates were not computed at subpixel level, because the code lacked the specific handling for this diffusivity mode.
### Solution
The `charbonnier_diffusivity()` function already exists in `nldiffusion_functions.cpp`, it just wasn't being called. This PR adds the missing `else if` branch to call it, matching the pattern already implemented in `AKAZEFeatures.cpp`.
Fixes#27134
### Pull Request Readiness Checklist
- [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 copyleft license.
- [x] The PR is proposed to the proper branch.
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
- [ ] The feature is well documented and sample code can be built with the project CMake
Fix ORB inconsistency for masks with values 255 and 1. #26366
### Pull Request Readiness Checklist
The PR fixes : [25974](https://github.com/opencv/opencv/issues/25974)
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
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Support C++20 standard #26590
Close https://github.com/opencv/opencv/issues/26589
Related https://github.com/opencv/opencv_contrib/pull/3842
Related: https://github.com/opencv/opencv/issues/20269
- do not arithmetic enums and ( different enums or floating numeric)
- remove unused variable
### 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
- [x] 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
* different interpolation by double image
* fixing scaling mapping
* fixing a test
* added an option to enable previous interpolation
* added doxygen entries for the new parameter
* ASSERT_TRUE -> ASSERT_EQ
* changed log message when using old upscale mode
Usage of imread(): magic number 0, unchecked result
* docs: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* samples, apps: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* tests: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* doc/py_tutorials: check imread() result
added blob contours to blob detector
* added blob contours
* Fixed Java regression test after new parameter addition to SimpleBlobDetector.
* Added stub implementation of SimpleBlobDetector::getBlobContours to presume source API compatibility.
Fix ORB integer overflow
* set size_t step to fix integer overflow in ptr0 offset
* added issue_537 test
* minor fix tags, points
* added size_t_step and offset to remove mixed unsigned and signed operations
* features2d: update ORB checks
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Fix Single ThresholdBug in Simple Blob Detector
* address bug with using min dist between blobs in blob detector
cast type in comparison and remove docs
address bug with using min dist between blobs in blob detector
use scalar instead of int
address bug with using min dist between blobs in blob detector
* fix namespace and formatting
* 8-bit SIFT descriptors
* use clearer parameter
* update docs
* propagate type info
* overload function for avoiding ABI-break
* bugfix: some values are undefined when CV_SIMD is absent
* Fix trees parsing behavior in hierarchical_clustering_index:
Before, when maxCheck was reached in the first descent of a tree, time was still wasted parsing
the next trees till their best leaf, just to skip the points stored there.
Now we can choose either to keep this behavior, and so we skip parsing other trees after reaching
maxCheck, or we choose to do one descent in each tree, even if in one tree we reach maxCheck.
* Apply the same change to kdtree.
As each leaf contains only 1 point (unlike hierarchical_clustering), difference is visible if trees > maxCheck
* Add the new explore_all_trees parameters to miniflann
* Adapt the FlannBasedMatcher read_write test to the additional search parameter
* Adapt java tests to the additional parameter in SearchParams
* Fix the ABI dumps failure on SearchParams interface change
* Support of ctor calling another ctor of the class is only fully supported from C+11
* Implement ASIFT in C++
* '>>' should be '> >' within a nested template
* add a sample for asift usage
* bugfix empty keypoints cause crash
* simpler initialization for mask
* suppress the number of lines
* correct tex document
* type casting
* add descriptorsize for asift
* smaller testdata for asift
* more smaller test data
* add OpenCV short license header
* Get/Set functions for BRISK parameters, issue #11527.
Allows setting threshold and octaves parameters after creating a brisk object. These parameters do not affect the initial pattern initialization and can be changed later without re-initialization.
* Fix doc parameter name.
* Brisk get/set functions tests. Check for correct value and make tests independent of default parameter values.
* Add dummy implementations for BRISK get/set functions not to break API in case someone has overloaded the Feature2d::BRISK interface. This makes BRISK different from the other detectors/descriptors on the other hand, where get/set functions are pure virtual in the interface.
Primary-H
Anand Mahesh
Murat Raimbekov
Skreg
Alexander Smorkalov
Vincent Rabaud
Kumataro
Maksim Shabunin
Yuriy Chernyshov
Alexander Smorkalov
Vaclav Vavra
Alexander Alekhin
Christoph Rackwitz
Petr Glotov
yuki takehara
Alexander Panov
Danny
Yosshi999
pemmanuelviel
Yosshi999
Tomoaki Teshima
Alexander Alekhin
Dmitry Kurtaev
okriof