Modify the outputVideoFormat after changing the output format in MSMF backend #24142
After changing the output format, need to modify the outputVideoFormat, otherwise the outputVideoFormat is always CV_CAP_MODE_BGR, and an error will occur when converting the format in retrieveVideoFrame(), and will always enter "case CV_CAP_MODE_BGR:" process.
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Co-authored-by: 李龙 <lilong@sobey.com>
Use ngraph::Output in OpenVINO backend wrapper #24196
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24102
* Use `ngraph::Output<ngraph::Node>>` insead of `std::shared_ptr<ngraph::Node>` as a backend wrapper. It lets access to multi-output nodes: 588ddf1b18/modules/dnn/src/net_openvino.cpp (L501-L504)
* All layers can be customizable with OpenVINO >= 2022.1. nGraph reference code used for default layer implementation does not required CPU plugin also (might be tested by commenting CPU plugin at `/opt/intel/openvino/runtime/lib/intel64/plugins.xml`).
* Correct inference if only intermediate blobs requested.
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Properly preserve chi_table license as mandated by BSD-3-Clause #24204
Amend reference to online hosted file with the full license quotation as mandated by the original license.
Fix distanceTransform for inputs with large step and height #24214
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23895
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Minor optimization of two lines intersection #24216
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Not significant, but we can reduce number of multiplications while compute two lines intersection. Both methods are used heavily in their modules.
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The address sanitizer highlighted this issue in our code base. It
looks like the code is currently grabbing a pointer to a temporary
object and then performing operations on it.
I printed some information right before the asan crash:
eigensolver address: 0x7f0ad95032f0
eigensolver size: 4528
eig_vecs_ ptr: 0x7f0ad95045e0
eig_vecs_ offset: 4848
This shows that `eig_vecs_` points past the end of `eigensolver`. In
other words, it points at the temporary object created by the
`eigensolver.eigenvectors()` call.
Compare the docs for `.eigenvalues()`:
https://eigen.tuxfamily.org/dox/classEigen_1_1EigenSolver.html#a0f507ad7ab14797882f474ca8f2773e7
to the docs for `.eigenvectors()`:
https://eigen.tuxfamily.org/dox/classEigen_1_1EigenSolver.html#a66288022802172e3ee059283b26201d7
The difference in return types is interesting. `.eigenvalues()`
returns a reference. But `.eigenvectors()` returns a matrix.
This patch here fixes the problem by saving the temporary object and
then grabbing a pointer into it.
This is a curated snippet of the original asan failure:
==12==ERROR: AddressSanitizer: stack-use-after-scope on address 0x7fc633704640 at pc 0x7fc64f7f1593 bp 0x7ffe8875fc90 sp 0x7ffe8875fc88
READ of size 8 at 0x7fc633704640 thread T0
#0 0x7fc64f7f1592 in cv::usac::EssentialMinimalSolverStewenius5ptsImpl::estimate(std::__1::vector<int, std::__1::allocator<int> > const&, std::__1::vector<cv::Mat, std::__1::allocator<cv::Mat> >&) const /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/essential_solver.cpp:181:48
#1 0x7fc64f915d92 in cv::usac::EssentialEstimatorImpl::estimateModels(std::__1::vector<int, std::__1::allocator<int> > const&, std::__1::vector<cv::Mat, std::__1::allocator<cv::Mat> >&) const /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/estimator.cpp:110:46
#2 0x7fc64fa74fb0 in cv::usac::Ransac::run(cv::Ptr<cv::usac::RansacOutput>&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/ransac_solvers.cpp:152:58
#3 0x7fc64fa6cd8e in cv::usac::run(cv::Ptr<cv::usac::Model const> const&, cv::_InputArray const&, cv::_InputArray const&, int, cv::Ptr<cv::usac::RansacOutput>&, cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/ransac_solvers.cpp:1010:16
#4 0x7fc64fa6fb46 in cv::usac::findEssentialMat(cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, int, double, double, cv::_OutputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/ransac_solvers.cpp:527:9
#5 0x7fc64f3b5522 in cv::findEssentialMat(cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, int, double, double, int, cv::_OutputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/five-point.cpp:437:16
#6 0x7fc64f3b7e00 in cv::findEssentialMat(cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, int, double, double, cv::_OutputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/five-point.cpp:486:12
...
Address 0x7fc633704640 is located in stack of thread T0 at offset 17984 in frame
#0 0x7fc64f7ed4ff in cv::usac::EssentialMinimalSolverStewenius5ptsImpl::estimate(std::__1::vector<int, std::__1::allocator<int> > const&, std::__1::vector<cv::Mat, std::__1::allocator<cv::Mat> >&) const /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/essential_solver.cpp:36
This frame has 63 object(s):
[32, 56) 'coefficients' (line 38)
[96, 384) 'ee' (line 55)
...
[13040, 17568) 'eigensolver' (line 142)
[17824, 17840) 'ref.tmp518' (line 143)
[17856, 17872) 'ref.tmp523' (line 144)
[17888, 19488) 'ref.tmp524' (line 144) <== Memory access at offset 17984 is inside this variable
[19616, 19640) 'ref.tmp532' (line 169)
...
The crash report says that we're accessing a temporary object from
line 144 when we shouldn't be. Line 144 looks like this:
https://github.com/opencv/opencv/blob/4.6.0/modules/calib3d/src/usac/essential_solver.cpp#L144
const auto * const eig_vecs_ = (double *) eigensolver.eigenvectors().real().data();
We are using version 4.6.0 for this, but the problem is present on the
4.x branch.
Note that I am dropping the .real() call here. I think that is safe because
of the code further down (line 277 in the most recent version):
const int eig_i = 20 * i + 12; // eigen stores imaginary values too
The code appears to expect to have to skip doubles for the imaginary parts
of the complex numbers.
Admittedly, I couldn't find a test case that exercised this code path to
validate correctness.
Fix crash in ap3p #23607
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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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* add broadcast_to with tests
* change name
* fix test
* fix implicit type conversion
* replace type of shape with InputArray
* add perf test
* add perf tests which takes care of axis
* v2 from ficus expand
* rename to broadcast
* use randu in place of declare
* doc improvement; smaller scale in perf
* capture get_index by reference
If building with -mcpu=native or any other setting which implies the current
CPU has FP16 but with intrinsics disabled, we mistakenly try to use it even
though convolution.hpp conditionally defines it correctly based on whether
we should *use it*. convolution.cpp on the other hand was mismatched and
trying to use it if the CPU supported it, even if not enabled in the build
system.
Make the guards match.
Bug: https://bugs.gentoo.org/913031
Signed-off-by: Sam James <sam@gentoo.org>
Skip test on SkipTestException at fixture's constructor
* Skip test on SkipTestException at fixture's constructor
* Add warning supression
* Skip Python tests if no test file found
* Skip instances of test fixture with exception at SetUpTestCase
* Skip test with exception at SetUp method
* Try remove warning disable
* Add CV_NORETURN
* Remove FAIL assertion
* Use findDataFile to throw Skip exception
* Throw exception conditionally
* core:add OPENCV_IPP_MEAN/MINMAX/SUM option to enable IPP optimizations
* fix: to use guard HAVE_IPP and ocv_append_source_file_compile_definitions() macro.
* support OPENCV_IPP_ENABLE_ALL
* add document for OPENCV_IPP_ENABLE_ALL
* fix OPENCV_IPP_ENABLE_ALL comment
Fixed an off-by-1 buffer resize, the space for the null termination was forgotten.
Prefer snprintf, which can never overflow (if given the right size).
In one case I cheated and used strcpy, because I cannot figure out the buffer size at that point in the code.
OCL_FP16 MatMul with large batch
* Workaround FP16 MatMul with large batch
* Fix OCL reinitialization
* Higher thresholds for INT8 quantization
* Try fix gemm_buffer_NT for half (columns)
* Fix GEMM by rows
* Add batch dimension to InnerProduct layer test
* Fix Test_ONNX_conformance.Layer_Test/test_basic_conv_with_padding
* Batch 16
* Replace all vload4
* Version suffix for MobileNetSSD_deploy Caffe model
Rewrite Universal Intrinsic code by using new API: Core module. #23980
The goal of this PR is to match and modify all SIMD code blocks guarded by `CV_SIMD` macro in the `opencv/modules/core` folder and rewrite them by using the new Universal Intrinsic API.
The patch is almost auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter), related PR #23885.
Most of the files have been rewritten, but I marked this PR as draft because, the `CV_SIMD` macro also exists in the following files, and the reasons why they are not rewrited are:
1. ~~code design for fixed-size SIMD (v_int16x8, v_float32x4, etc.), need to manually rewrite.~~ Rewrited
- ./modules/core/src/stat.simd.hpp
- ./modules/core/src/matrix_transform.cpp
- ./modules/core/src/matmul.simd.hpp
2. Vector types are wrapped in other class/struct, that are not supported by the compiler in variable-length backends. Can not be rewrited directly.
- ./modules/core/src/mathfuncs_core.simd.hpp
```cpp
struct v_atan_f32
{
explicit v_atan_f32(const float& scale)
{
...
}
v_float32 compute(const v_float32& y, const v_float32& x)
{
...
}
...
v_float32 val90; // sizeless type can not used in a class
v_float32 val180;
v_float32 val360;
v_float32 s;
};
```
3. The API interface does not support/does not match
- ./modules/core/src/norm.cpp
Use `v_popcount`, ~~waiting for #23966~~ Fixed
- ./modules/core/src/has_non_zero.simd.hpp
Use illegal Universal Intrinsic API: For float type, there is no logical operation `|`. Further discussion needed
```cpp
/** @brief Bitwise OR
Only for integer types. */
template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> operator|(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n>& operator|=(v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
```
```cpp
#if CV_SIMD
typedef v_float32 v_type;
const v_type v_zero = vx_setzero_f32();
constexpr const int unrollCount = 8;
int step = v_type::nlanes * unrollCount;
int len0 = len & -step;
const float* srcSimdEnd = src+len0;
int countSIMD = static_cast<int>((srcSimdEnd-src)/step);
while(!res && countSIMD--)
{
v_type v0 = vx_load(src);
src += v_type::nlanes;
v_type v1 = vx_load(src);
src += v_type::nlanes;
....
src += v_type::nlanes;
v0 |= v1; //Illegal ?
....
//res = v_check_any(((v0 | v4) != v_zero));//beware : (NaN != 0) returns "false" since != is mapped to _CMP_NEQ_OQ and not _CMP_NEQ_UQ
res = !v_check_all(((v0 | v4) == v_zero));
}
v_cleanup();
#endif
```
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dnn: cleanup of tengine backend #24122🚀 Cleanup for OpenCV 5.0. Tengine backend is added for convolution layer speedup on ARM CPUs, but it is not maintained and the convolution layer on our default backend has reached similar performance to that of Tengine.
Tengine backend related PRs:
- https://github.com/opencv/opencv/pull/16724
- https://github.com/opencv/opencv/pull/18323
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Invalid memory access fix for ONNX split layer parser #24076#24101
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TFLite models on different backends (tests and improvements) #24039
### Pull Request Readiness Checklist
* MaxUnpooling with OpenVINO
* Fully connected with transposed inputs/weights with OpenVINO
* Enable backends tests for TFLite (related to https://github.com/opencv/opencv/issues/23992#issuecomment-1640691722)
* Increase existing tests thresholds
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Resolve uncovered CUDA dnn layer #24080
### Pull Request Readiness Checklist
* Gelu activation layer on CUDA
* Try to relax GEMM from ONNX
resolves https://github.com/opencv/opencv/issues/24064
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Remove legacy nGraph logic #24072
### Pull Request Readiness Checklist
TODO:
- [x] Test with OpenVINO 2021.4 (tested locally)
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DetectionOutput layer on OpenVINO without limitations #24069
### Pull Request Readiness Checklist
required for https://github.com/opencv/opencv/pull/23987
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G-API: Support CUDA & TensoRT Execution Providers for ONNXRT Backend #24059
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PReLU with element-wise scales #24056
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24051
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Update opencv dnn to support cann version >=6.3 #23936
1.modify the search path of "libopsproto.so" in OpenCVFindCANN.cmake
2.add the search path of "libgraph_base.so" in OpenCVFindCANN.cmake
3.automatic check Ascend socVersion,and test on Ascend310/Ascend310B/Ascend910B well
Python typing refinement for dnn_registerLayer/dnn_unregisterLayer functions #24066
This patch introduces typings generation for `dnn_registerLayer`/`dnn_unregisterLayer` manually defined in [`cv2/modules/dnn/misc/python/pyopencv_dnn.hpp`](https://github.com/opencv/opencv/blob/4.x/modules/dnn/misc/python/pyopencv_dnn.hpp)
Updates:
- Add `LayerProtocol` to `cv2/dnn/__init__.pyi`:
```python
class LayerProtocol(Protocol):
def __init__(
self, params: dict[str, DictValue],
blobs: typing.Sequence[cv2.typing.MatLike]
) -> None: ...
def getMemoryShapes(
self, inputs: typing.Sequence[typing.Sequence[int]]
) -> typing.Sequence[typing.Sequence[int]]: ...
def forward(
self, inputs: typing.Sequence[cv2.typing.MatLike]
) -> typing.Sequence[cv2.typing.MatLike]: ...
```
- Add `dnn_registerLayer` function to `cv2/__init__.pyi`:
```python
def dnn_registerLayer(layerTypeName: str,
layerClass: typing.Type[LayerProtocol]) -> None: ...
```
- Add `dnn_unregisterLayer` function to `cv2/__init__.pyi`:
```python
def dnn_unregisterLayer(layerTypeName: str) -> None: ...
```
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Fix harmless ASAN error. #24042
For an empty radius, &v[0] would be accessed (though the called functions would not use it due to v.size() being 0). Also add checks for emptyness and fix the first element checks, in case we get INT_MAX to compare to.
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G-API: Support DirectML Execution Provider for ONNXRT Backend #24045
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feat: add cuda_Stream and cuda_GpuMat to simple types mapping #24029
This patch fixes usage of `cuda::Stream` in function arguments.
Affected modules: `cudacodec`:
[`using namespace cuda`](9dfe233020/modules/cudacodec/include/opencv2/cudacodec.hpp (L62)) in public `cudacodec.hpp` header can be removed after merge of the patch.
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Fix FLANN python bindings #24028
As a side-effect this patch improves reporting errors by FLANN `get_param`.
resolves#21642
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G-API: Support OpenVINO Execution Provider for ONNXRT Backend #24024
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[TFLite] Pack layer and other fixes for SSD from Keras #24004
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resolves https://github.com/opencv/opencv/issues/23992
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1076
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Details here: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=58006
runtime error: call to function (unknown) through pointer to incorrect function type 'void (*)(const unsigned char **, const int *, unsigned char **, const int *, int, int)'
Python typing magic constants #24023
This patch adds typing stubs generation for `__all__` and `__version__` constants.
Introduced `__all__` is intentionally empty for all generated modules stubs.
Type hints won't work for star imports
resolves#23950
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Fix python typing stubs generation for CUDA modules #24022resolves#23946resolves#23945resolvesopencv/opencv-python#871
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C++20 made it invalid to use simple-template-ids for constructors and destructors: https://eel.is/c++draft/diff.cpp17.class#2
GCC 11 and later throw an error on this, with the unhelpful message `expected unqualified-id before ')' token`. This PR fixes the problem.
DNN: optimize the speed of general Depth-wise #23952
Try to solve the issue: https://github.com/opencv/opencv/issues/23941
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Add V4L2_PIX_FMT_Y16_BE pixel format #18498
Address #18495
relates to #23944
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- [ ] Test using Melexis MLX90640
Fix imgwarp at borders when transparent. #23922
I believe this is a proper fix to #23562
The PR #23754 overwrites data while that should not be the case with transparent data. The original test is failing because points at the border do not get computed because they do not have 4 neighbors to be computed. Still ,we can approximate their computation with whatever neighbors that are available.
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Fix checkSignature not thread safe for AVIF. #23943
A common decoder cannot be shared with checkSignature which is used like a static function (on a static ist of decoders).
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Adds missing typing stubs:
- Matrix depths: `CV_8U`, `CV_8S` and etc.
- Matrix type constants: `CV_8UC1`, `CV_32FC3` and etc.
- Matrix type factory functions: `CV_*(channels) -> int` and `CV_MAKETYPE`
Fixing typos in usac #23900
Just read and correct some typos in `usac`
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G-API: Fix async inference for OpenVINO backend #23884
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dnn: disable warning when loading a fp16 model #23853
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Add charuco board check #23647
Added charuco board checking to avoid detection of incorrect board.
Fixes#23517
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Fix detect diamonds api #23848
`detectDiamonds` cannot be called from python, reproducer:
```
import numpy as np
import cv2 as cv
detector = cv.aruco.CharucoDetector(
cv.aruco.CharucoBoard(
(3, 3), 200.0, 100.0,
cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_250)
)
)
image = np.zeros((640, 480, 1), dtype=np.uint8)
res = detector.detectDiamonds(image)
print(res)
```
The error in `detectDiamonds` API fixed by replacing `InputOutputArrayOfArrays markerIds` with `InputOutputArray markerIds`.
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Python binding for RotatedRect #23702
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related: https://github.com/opencv/opencv/issues/23546#issuecomment-1562894602
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G-API: Fix incorrect OpaqueKind for Kernel outputs #23843
### Pull Request Readiness Checklist
#### Overview
The PR is going to fix several problems:
1. Major: `GKernel` doesn't hold `kind` for its outputs. Since `GModelBuilder` traverse graph from outputs to inputs once it reaches any output of the operation it will use its `kind` to create `Data` meta for all operation outputs. Since it essential for `python` to know `GTypeInfo` (which is `shape` and `kind`) it will be confused.
Consider this operation:
```
@cv.gapi.op('custom.square_mean', in_types=[cv.GArray.Int], out_types=[cv.GOpaque.Float, cv.GArray.Int])
class GSquareMean:
@staticmethod
def outMeta(desc):
return cv.empty_gopaque_desc(), cv.empty_array_desc()
```
Even though `GOpaque` is `Float`, corresponding metadata might have `Int` kind because it might be taken from `cv.GArray.Int`
so it will be a problem if one of the outputs of these operation is graph output because python will cast it to the wrong type based on `Data` meta.
2. Minor: Some of the OpenVINO `IR`'s doesn't any layout information for input. It's usually true only for `IRv10` but since `OpenVINO 2.0` need this information to correctly configure resize we need to put default layout if there no such assigned in `ov::Model`.
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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G-API: Implement InferROI, InferList, InferList2 for OpenVINO backend #23799
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G-API: Align IE Backend with the latest OpenVINO version #23796
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Fix distransform to work with large images #22798
This attempts to fix the following bug which was caused by storing squares of large integers into 32-bit floating point variables:
https://github.com/opencv/opencv/issues/22732
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Export enums ALL_CAPS version to typing stub files #23816
- Export ALL_CAPS versions alongside from normal names for enum constants, since both versions are available in runtime
- Change enum names entries comments to documentary strings
Before patch
```python
RMat_Access_R: int
RMat_Access_W: int
RMat_Access = int # One of [R, W]
```
After patch
```python
RMat_Access_R: int
RMAT_ACCESS_R: int
RMat_Access_W: int
RMAT_ACCESS_W: int
RMat_Access = int
"""One of [RMat_Access_R, RMAT_ACCESS_R, RMat_Access_W, RMAT_ACCESS_W]"""
```
Resolves: #23776
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Build Java without ANT #23724
### Pull Request Readiness Checklist
Enables a path of building Java bindings without ANT
* Able to build OpenCV JAR and Docs without ANT
```
-- Java:
-- ant: NO
-- JNI: /usr/lib/jvm/default-java/include /usr/lib/jvm/default-java/include/linux /usr/lib/jvm/default-java/include
-- Java wrappers: YES
-- Java tests: NO
```
* Possible to build OpenCV JAR without ANT but tests still require ANT
**Merge with**: https://github.com/opencv/opencv_contrib/pull/3502
Notes:
- Use `OPENCV_JAVA_IGNORE_ANT=1` to force "Java" flow for building Java bindings
- Java tests still require Apache ANT
- JAR doesn't include `.java` source code files.
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Keep inliers for linear remap with BORDER_TRANSPARENT #23754
Address https://github.com/opencv/opencv/issues/23562
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23562
I do think that this is a bug because with `INTER_CUBIC + BORDER_TRANSPARENT` the last column and row are preserved. So same should be done for `INTER_LINEAR`
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Update USAC #23078
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added Aruco MIP dictionaries #23785
added Aruco MIP dictionaries: DICT_ARUCO_MIP_16h3, DICT_ARUCO_MIP_25h7, DICT_ARUCO_MIP_36h12 from [Aruco.js](https://github.com/damianofalcioni/js-aruco2), converted in opencv format using https://github.com/damianofalcioni/js-aruco2/blob/master/src/dictionaries/utils/dic2opencv.js
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G-API: Expose explicit preprocessing for IE Backend #23786
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G-API: Refine Semantic Segmentation Demo #23766
### Overview
* Supported demo working with camera id (e.g `--input=0`)
* Supported 3d output segmentation models (e.g `deeplabv3`)
* Supported `desync` execution
* Supported higher camera resolution
* Changed the color map to pascal voc (https://cloud.githubusercontent.com/assets/4503207/17803328/1006ca80-65f6-11e6-9ff6-36b7ef5b9ac6.png)
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