PLY mesh support #24961
**Warning:** The PR changes exising API.
Fixes#24960
Connected PR: [#1145@extra](https://github.com/opencv/opencv_extra/pull/1145)
### Changes
* Adds faces loading from and saving to PLY files
* Fixes incorrect PLY loading (see issue)
* Adds per-vertex color loading / saving
### Pull Request Readiness Checklist
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bug fix infinite loop #24987Fixes#24967
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Bugfix to #24967
* started adding support for new types (16f, 16bf, 32u, 64u, 64s) to arithmetic functions
* fixed several tests; refactored and extended sum(), extended inRange().
* extended countNonZero(), mean(), meanStdDev(), minMaxIdx(), norm() and sum() to support new types (F16, BF16, U32, U64, S64)
* put missing CV_DEPTH_MAX to some function dispatcher tables
* extended findnonzero, hasnonzero with the new types support
* extended mixChannels() to support new types
* minor fix
* fixed a few compile errors on Linux and a few failures in core tests
* fixed a few more warnings and test failures
* trying to fix the remaining warnings and test failures. The test `MulTestGPU.MathOpTest` was disabled - not clear whether to set tolerance - it's not bit-exact operation, as possibly assumed by the test, due to the use of scale and possibly limited accuracy of the intermediate floating-point calculations.
* found that in the current snapshot G-API produces incorrect results in Mul, Div and AddWeighted (at least when using OpenCL on Windows x64 or MacOS x64). Disabled the respective tests.
Allow multiple flags with OPENCV_GRADLE_VERBOSE_OPTIONS #24969
### Pull Request Readiness Checklist
Merge with https://github.com/opencv/ci-gha-workflow/pull/144
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
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Patch to opencv_extra has the same branch name.
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Fix bug in ChessBoardDetector::findQuadNeighbors #24779
### Pull Request Readiness Checklist
`corners` and `neighbors` indices means not filling order, but relative position. So, for example if `quad->count = 2`, it doesn't mean that `quad->neighbors[0]` and `quad->neighbors[1]` are filled. And we should should iterate over all four `neighbors`.
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.
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Added offline option for Android builds #24956
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QR codes Structured Append decoding mode #24548
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23245
Merge after https://github.com/opencv/opencv/pull/24299
Current proposal is to use `detectAndDecodeMulti` or `decodeMulti` for structured append mode decoding. 0-th QR code in a sequence gets a full message while the rest of codes will correspond to empty strings.
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.
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- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Modified Java tests to run on Android #24910
To run the tests you need to:
1. Build OpenCV using Android pipeline. For example:
`cmake -DBUILD_TEST=ON -DANDROID=ON -DANDROID_ABI=arm64-v8a -DCMAKE_TOOLCHAIN_FILE=/usr/lib/android-sdk/ndk/25.1.8937393/build/cmake/android.toolchain.cmake -DANDROID_NDK=/usr/lib/android-sdk/ndk/25.1.8937393 -DANDROID_SDK=/usr/lib/android-sdk ../opencv`
`make`
2. Connect Android Phone
3. Run tests:
`cd android_tests`
`./gradlew tests_module:connectedAndroidTest`
Related CI pipeline: https://github.com/opencv/ci-gha-workflow/pull/138
### Pull Request Readiness Checklist
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- [x] The PR is proposed to the proper branch
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Patch to opencv_extra has the same branch name.
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Documentation for Yolo usage in Opencv #24898
This PR introduces documentation for the usage of yolo detection model family in open CV. This is not to be merge before #24691, as the sample will need to be changed.
### Pull Request Readiness Checklist
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G-API: Implement concurrent executor #24845
## Overview
This PR introduces the new G-API executor called `GThreadedExecutor` which can be selected when the `GComputation` is compiled in `serial` mode (a.k.a `GComputation::compile(...)`)
### ThreadPool
`cv::gapi::own::ThreadPool` has been introduced in order to abstract usage of threads in `GThreadedExecutor`.
`ThreadPool` is implemented by using `own::concurrent_bounded_queue`
`ThreadPool` has only as single method `schedule` that will push task into the queue for the further execution.
The **important** notice is that if `Task` executed in `ThreadPool` throws exception - this is `UB`.
### GThreadedExecutor
The `GThreadedExecutor` is mostly copy-paste of `GExecutor`, should we extend `GExecutor` instead?
#### Implementation details
1. Build the dependency graph for `Island` nodes.
2. Store the tasks that don't have dependencies into separate `vector` in order to run them first.
3. at the `GThreadedExecutor::run()` schedule the tasks that don't have dependencies that will schedule their dependents and wait for the completion.
### Pull Request Readiness Checklist
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Vulkan backend for NaryEltwiseLayer in DNN module #24768
We improve Vulkan backend for ``NaryEltwiseLayer`` in DNN module by:
- add a basic framework for Vulkan backend in ``NaryEltwiseLayer``
- add a compute shader for binary forwarding (an imitation of what has been done in native OpenCV backend including broadcasting and eltwise-operation)
- typo fixed:
- Wrong info output in ``context.cpp``
Currently, our implementation (or all layers supporting Vulkan backend) runs pretty slow on discrete GPUs basically due to IO cost in function ``copyToHost``, and we are going to fix that by
- find out the best ``VkMemoryProperty`` for various discrete GPUs
- prevent ``copyToHost`` in middle layers during forwarding, (i.e keep data in GPU memory)
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Co-authored-by: IskXCr <IskXCr@outlook.com>
Raft support added in this sample code #24913
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fix: https://github.com/opencv/opencv/issues/24424 Update DNN Optical Flow sample with RAFT model
I implemented both RAFT and FlowNet v2 leaving it to the user which one he wants to use to estimate the optical flow.
Co-authored-by: Uday Sharma <uday@192.168.1.35>
Alexander Smorkalov
Alexander Smorkalov
Alexander Alekhin
Lollyrana
Rostislav Vasilikhin
Kumataro
Maksym Ivashechkin
Vadim Pisarevsky
eplankin
MaximSmolskiy
Alexander Lyulkov
fengyuentau
Dmitry Kurtaev
ryanking13
alexlyulkov
Abduragim Shtanchaev
Anatoliy Talamanov
Haosonn
uday