Added Determinant (Det) layer to new DNN engine #27658
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Added IsInf layer to new DNN engine #27660
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Added IsNan layer to new DNN engine #27661
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This aligns with other virtual method declarations in cap_dshow.hpp
and silences compiler warnings (-Wsuggest-override) while improving
compile-time safety.
Add Alpha matting samples (C++ and Python) #27593
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imgproc: Bilateral filter performance improvement #27433
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Add strict validation for encoding parameters #27621
Close https://github.com/opencv/opencv/issues/27557
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Added Size layer to new DNN engine #27656
Merge with https://github.com/opencv/opencv_extra/pull/1274
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G-API: Implement cfgClampOutputs option to OpenVINO Params #27600
Added the option `cfgClampOutputs` to control where output clamping is performed for OpenVINO models. When enabled, output values are clamped in the PrePostProcessor stage instead of by the device or plugin. This provides a consistent and standardized clamping method across devices, helping to maintain accuracy regardless of device-specific clamping behavior.
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Feat #25150: Pose Graph MST initialization #27423
Implements an MST-based initialisation for pose graphs, as proposed in issue #25150. Both Prim’s and Kruskal’s algorithms were added to the 3D module. These receive a vector of node IDs and a vector of edges (each with source and target IDs and a weight), and return a vector with the resulting edges. These MST implementations treat edges as undirected internally, meaning users only need to provide one direction (A→B or B→A), and duplicates are handled automatically.
Additionally, a new pose graph initialisation method using MST (Prim) was implemented. It constructs the MST over the pose graph, then traverses it to reconstruct node poses. With this, users can call `poseGraph->initializePosesWithMST()` to create an initial solution for the pose graph problem.
A set of test cases validating the implementation was also included.
#### Notes
- The edge weight used in the MST for pose graphs is calculated as:
`weight = || translation || + λ * rotation_angle`,
where λ = 0.485 was determined empirically based on optimiser performance;
- Validated on [Sphere-a](https://lucacarlone.mit.edu/datasets/) pose graph, showing similar convergence behaviour with or without MST initialisation;
- Alternative weight formulas, such as the Mahalanobis distance formula, were also tested, but the current formula yielded better results.
#### Future Work
- Extend testing to more diverse pose graphs (currently limited to [Sphere-a](https://github.com/opencv/opencv_extra/blob/5.x/testdata/cv/rgbd/sphere_bignoise_vertex3.g2o) in opencv_extra)
- Explore adaptive tuning of the λ parameter for broader applicability.
Co-authored-by: @miguel1099
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Cuda 13.0 compatibility #27636
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### Issue
CUDA 13 deprecated some fields, resulting in build failures with CUDA 13. This updates to use the replacement API.
The reference to the deprecated features is here: https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#id6
### Testing
This was testing by building on the following configurations:
OS: Ubuntu 24.04
CUDA: 12.9, 13.0
optimize some drawing with stack allocation #27599
Some drawings can try a stack allocation instead of a std::vector
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Performance tests for writing and reading animations #27605
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related : https://github.com/opencv/opencv/pull/27496
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KleidiCV support on Apple devices #27607
Scope:
- Disabled bitcode generation in iPhone framework by default.
- Enabled KleidiCV build for iPhone.
- Added Github Actions log tags to group per-architecture builds and format logs.
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Changed line 69 from "Remember, we together" to "Remember, together we..."
I saw that this page encouraged us to contribute no matter how small the contribution is so I decided to "shoot my shot" as a beginner developer and fix a small grammatical error. Would be nice if I could be allowed to be recognized as a contributor with my contribution albeit pretty small, hopefully in the future, more meaningful contributions will be made! :)
Alexander Smorkalov
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Alexander Smorkalov
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Kumataro
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