Fix typos #26038
Fix typos
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Handling I32/I64 data types in G-API ONNX back-end #25817
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Extending G-API onnx::Params to pass arbitrary session options #25791
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Suppress build warnings for GCC14 #25686Close#25674
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Port G-API ONNXRT backend into V2 API #25662
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G-API OV backend requires cv::MediaFrame #24938
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**Background_subtraction demo G-API issue. Update:**
Porting to API20 resulted in an error (both for CPU and NPU):
```
[ERROR] OpenCV(4.9.0-dev) /home/runner/work/open_model_zoo/open_model_zoo/cache/opencv/modules/gapi/src/backends/ov/govbackend.cpp:813: error: (-215: assertion not done ) cv::util::holds_alternative<cv::GMatDesc>(input_meta) in function 'cfgPreProcessing'
```
Adding cv::MediaFrame support to govbackend resulted in the following (tested with CPU):
<img width="941" alt="image" src="https://github.com/opencv/opencv/assets/52502732/3a003d61-bda7-4b1e-9117-3410cda1ba32">
### TODO
- [ ] **As part of the review process [this comment](https://github.com/opencv/opencv/pull/24938#discussion_r1487694043) was addressed which make it impossible to run the demo. I will bring those changes back in a separate PR [support `PartialShape`]**
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G-API: A quick value-initialization support GMat #25055
This PR enables `GMat` objects to be value-initialized in the same way as it was done for `GScalar`s (and, possibly, other types).
- Added some helper methods in backends to distinguish if a certain G-type value initialization is supported or not;
- Added tests, including negative.
Where it is needed:
- Further extension of the OVCV backend (#24379 - will be refreshed soon);
- Further experiments with DNN module;
- Further experiments with "G-API behind UMat" sort of aggregation.
In the current form, PR can be reviewed & merged (@TolyaTalamanov please have a look)
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C-API cleanup: apps, imgproc_c and some constants #25075
Merge with https://github.com/opencv/opencv_contrib/pull/3642
* Removed obsolete apps - traincascade and createsamples (please use older OpenCV versions if you need them). These apps relied heavily on C-API
* removed all mentions of imgproc C-API headers (imgproc_c.h, types_c.h) - they were empty, included core C-API headers
* replaced usage of several C constants with C++ ones (error codes, norm modes, RNG modes, PCA modes, ...) - most part of this PR (split into two parts - all modules and calib+3d - for easier backporting)
* removed imgproc C-API headers (as separate commit, so that other changes could be backported to 4.x)
Most of these changes can be backported to 4.x.
G-API: Lower supported IE backend version #25054
Related to https://github.com/opencv/opencv/issues/25053
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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.
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G-API: Support CoreML Execution Providers for ONNXRT Backend #24068
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G-API: Get input model layout from the IR if possible in OV 2.0 backend #24658
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G-API: Implement inference only mode for OV backend #24584
### Changes overview
Introduced `cv::gapi::wip::ov::benchmark_mode{}` compile argument which if enabled force `OpenVINO` backend to run only inference without populating input and copying back output tensors.
This mode is only relevant for measuring the performance of pure inference without data transfers. Similar approach is using on OpenVINO side in `benchmark_app`: https://github.com/openvinotoolkit/openvino/blob/master/samples/cpp/benchmark_app/benchmark_app.hpp#L134-L139
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G-API: Advanced device selection for ONNX DirectML Execution Provider #24060
### Overview
Extend `cv::gapi::onnx::ep::DirectML` to accept `adapter name` as `ctor` parameter in order to select execution device by `name`.
E.g:
```
pp.cfgAddExecutionProvider(cv::gapi::onnx::ep::DirectML("Intel Graphics"));
```
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* attempt to add 0d/1d mat support to OpenCV
* revised the patch; now 1D mat is treated as 1xN 2D mat rather than Nx1.
* a step towards 'green' tests
* another little step towards 'green' tests
* calib test failures seem to be fixed now
* more fixes _core & _dnn
* another step towards green ci; even 0D mat's (a.k.a. scalars) are now partly supported!
* * fixed strange bug in aruco/charuco detector, not sure why it did not work
* also fixed a few remaining failures (hopefully) in dnn & core
* disabled failing GAPI tests - too complex to dig into this compiler pipeline
* hopefully fixed java tests
* trying to fix some more tests
* quick followup fix
* continue to fix test failures and warnings
* quick followup fix
* trying to fix some more tests
* partly fixed support for 0D/scalar UMat's
* use updated parseReduce() from upstream
* trying to fix the remaining test failures
* fixed [ch]aruco tests in Python
* still trying to fix tests
* revert "fix" in dnn's CUDA tensor
* trying to fix dnn+CUDA test failures
* fixed 1D umat creation
* hopefully fixed remaining cuda test failures
* removed training whitespaces
G-API: Introduce a Queue Source #24178
- Added a new IStreamSource class: in fact, a wrapper over a concurrent queue;
- Added minimal example on how it can be used;
- Extended IStreamSource with optional "halt" interface to break the blocking calls in the emitter threads when required to stop.
- Introduced a QueueInput class which allows to pass the whole graph's input vector at once. In fact it is a thin wrapper atop of individual Queue Sources.
There is a hidden trap found with our type system as described in https://github.com/orgs/g-api-org/discussions/2
While it works even in this form, it should be addressed somewhere in the 5.0 timeframe.
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G-API: Support CUDA & TensoRT Execution Providers for ONNXRT Backend #24059
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Maksim Shabunin
Alexander Smorkalov
ShengYu
lamiayous
Ujjayant Kadian
Kumataro
Daria Mityagina
Yuantao Feng
Dmitry Matveev
Anatoliy Talamanov
Alexander Smorkalov
Anastasiya Pronina
Alexey Smirnov
Liutong HAN
Sean McBrideandAlexander Smorkalov
Vadim Pisarevsky