* started working on adding 32u, 64u, 64s, bool and 16bf types to OpenCV
* core & imgproc tests seem to pass
* fixed a few compile errors and test failures on macOS x86
* hopefully fixed some compile problems and test failures
* fixed some more warnings and test failures
* trying to fix small deviations in perf_core & perf_imgproc by revering randf_64f to exact version used before
* trying to fix behavior of the new OpenCV with old plugins; there is (quite strong) assumption that video capture would give us frames with depth == CV_8U (0) or CV_16U (2). If depth is > 7 then it means that the plugin is built with the old OpenCV. It needs to be recompiled, of course and then this hack can be removed.
* try to repair the case when target arch does not have FP64 SIMD
* 1. fixed bug in itoa() found by alalek
2. restored ==, !=, > and < univ. intrinsics on ARM32/ARM64.
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
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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Remove legacy nGraph logic #24072
### Pull Request Readiness Checklist
TODO:
- [x] Test with OpenVINO 2021.4 (tested locally)
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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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
### Pull Request Readiness Checklist
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Merge usac to 5.x #24005
### Pull Request Readiness Checklist
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Base branch is PR #23979. Merging PR #23078, 23900 and PR #23806 to 5.x
PReLU with element-wise scales #24056
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24051
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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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: ...
```
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Patch to opencv_extra has the same branch name.
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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.
### Pull Request Readiness Checklist
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G-API: Support DirectML Execution Provider for ONNXRT Backend #24045
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GSoC: Modified PLY reader to support color attribute read/write #23805
* Modified PLY reader to support color attribute read/write
* Fix bugs & Modified OBJ reader for color IO
* Replace with correct test file
* Fix I/O of property [w] in OBJ files
### Pull Request Readiness Checklist
**Merged with https://github.com/opencv/opencv_extra/pull/1075**
[Issue for GSoC 2023](https://github.com/opencv/opencv/issues/23624)
The ply loader in 3D module doesn't support color attribute reading. I modified that to support color attribute reading & writing for the color attribute compression as described in proposal.
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
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Patch to opencv_extra has the same branch name.
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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.
### Pull Request Readiness Checklist
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Fix FLANN python bindings #24028
As a side-effect this patch improves reporting errors by FLANN `get_param`.
resolves#21642
### Pull Request Readiness Checklist
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G-API: Support OpenVINO Execution Provider for ONNXRT Backend #24024
### Pull Request Readiness Checklist
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[TFLite] Pack layer and other fixes for SSD from Keras #24004
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23992
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1076
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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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
### Pull Request Readiness Checklist
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Fix python typing stubs generation for CUDA modules #24022resolves#23946resolves#23945resolvesopencv/opencv-python#871
### Pull Request Readiness Checklist
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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
### Pull Request Readiness Checklist
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Add V4L2_PIX_FMT_Y16_BE pixel format #18498
Address #18495
relates to #23944
### Pull Request Readiness Checklist
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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
### Pull Request Readiness Checklist
related: https://github.com/opencv/opencv/issues/23546#issuecomment-1562894602
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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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
### Pull Request Readiness Checklist
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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.
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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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`
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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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
### Pull Request Readiness Checklist
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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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Although acceptible to Intel CPUs, it's still undefined behaviour according to the C++ standard.
It can be replaced with memcpy, which makes the code simpler, and it generates the same assembly code with gcc and clang with -O2 (verified with godbolt).
Also expanded the test to include other little endian CPUs by testing for __LITTLE_ENDIAN__.
Add AVIF support through libavif. #23596
This is to fix https://github.com/opencv/opencv/issues/19271
Extra: https://github.com/opencv/opencv_extra/pull/1069
### Pull Request Readiness Checklist
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DNN: fix bug for X86 Winograd #23763
Address https://github.com/opencv/opencv/issues/23760
The patch aims to add a runtime check for X86 platform without AVX(2).
### Pull Request Readiness Checklist
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Assertion Fix in Split Layer #23746
### Pull Request Readiness Checklist
This PR fixes issue mentioned in [#23663](https://github.com/opencv/opencv/issues/23663)
Merge with https://github.com/opencv/opencv_extra/pull/1067
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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imgproc: add contour values check to IntelligentScissorsMB tests
Preparation for the #21959 changes as per @asmorkalov's https://github.com/opencv/opencv/pull/21959#issuecomment-1560511500 suggestion.
### Pull Request Readiness Checklist
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[G-API] Implement OpenVINO 2.0 backend #23595
### Pull Request Readiness Checklist
Implemented basic functionality for `OpenVINO` 2.0 G-API backend.
#### Overview
- [x] Implement `Infer` kernel with some of essential configurable parameters + IR/Blob models format support.
- [ ] Implement the rest of kernels: `InferList`, `InferROI`, `Infer2` + other configurable params (e.g reshape)
- [x] Asyncrhonous execution support
- [ ] Remote context support
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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GAPI Fluid SIMD:Add support of new several types for the Merge3
- Support of the new several types was added.
- Fixes for the Split/Merge and ConvertTo issues.
G-API: Integration branch for ONNX & Python-related changes #23597
# Changes overview
## 1. Expose ONNX backend's Normalization and Mean-value parameters in Python
* Since Python G-API bindings rely on `Generic` infer to express Inference, the `Generic` specialization of `onnx::Params` was extended with new methods to control normalization (`/255`) and mean-value; these methods were exposed in the Python bindings
* Found some questionable parts in the existing API which I'd like to review/discuss (see comments)
UPD:
1. Thanks to @TolyaTalamanov normalization inconsistencies have been identified with `squeezenet1.0-9` ONNX model itself; tests using these model were updated to DISABLE normalization and NOT using mean/value.
2. Questionable parts were removed and tests still pass.
### Details (taken from @TolyaTalamanov's comment):
`squeezenet1.0.*onnx` - doesn't require scaling to [0,1] and mean/std because the weights of the first convolution already scaled. ONNX documentation is broken. So the correct approach to use this models is:
1. ONNX: apply preprocessing from the documentation: https://github.com/onnx/models/blob/main/vision/classification/imagenet_preprocess.py#L8-L44 but without normalization step:
```
# DON'T DO IT:
# mean_vec = np.array([0.485, 0.456, 0.406])
# stddev_vec = np.array([0.229, 0.224, 0.225])
# norm_img_data = np.zeros(img_data.shape).astype('float32')
# for i in range(img_data.shape[0]):
# norm_img_data[i,:,:] = (img_data[i,:,:]/255 - mean_vec[i]) / stddev_vec[i]
# # add batch channel
# norm_img_data = norm_img_data.reshape(1, 3, 224, 224).astype('float32')
# return norm_img_data
# INSTEAD
return img_data.reshape(1, 3, 224, 224)
```
2. G-API: Convert image from BGR to RGB and then pass to `apply` as-is with configuring parameters:
```
net = cv.gapi.onnx.params('squeezenet', model_filename)
net.cfgNormalize('data_0', False)
```
**Note**: Results might be difference because `G-API` doesn't apply central crop but just do resize to model resolution.
---
`squeezenet1.1.*onnx` - requires scaling to [0,1] and mean/std - onnx documentation is correct.
1. ONNX: apply preprocessing from the documentation: https://github.com/onnx/models/blob/main/vision/classification/imagenet_preprocess.py#L8-L44
2. G-API: Convert image from BGR to RGB and then pass to `apply` as-is with configuring parameters:
```
net = cv.gapi.onnx.params('squeezenet', model_filename)
net.cfgNormalize('data_0', True) // default
net.cfgMeanStd('data_0', [0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
```
**Note**: Results might be difference because `G-API` doesn't apply central crop but just do resize to model resolution.
## 2. Expose Fluid & kernel package-related functionality in Python
* `cv::gapi::combine()`
* `cv::GKernelPackage::size()` (mainly for testing purposes)
* `cv::gapi::imgproc::fluid::kernels()`
Added a test for the above.
## 3. Fixed issues with Python stateful kernel handling
Fixed error message when `outMeta()` of custom python operation fails.
## 4. Fixed various issues in Python tests
1. `test_gapi_streaming.py` - fixed behavior of Desync test to avoid sporadic issues
2. `test_gapi_infer_onnx.py` - fixed model lookup (it was still using the ONNX Zoo layout but was NOT using the proper env var we use to point to one).
### Pull Request Readiness Checklist
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better accuracy for _rotatedRectangleIntersection() (proposal for #23546) #23690
_rotatedRectangleIntersection() can be (statically) customized to use double instead of float for better accuracy
this is a proposal for experimentation around #23546
for better accuracy, _rotatedRectangleIntersection() could use double. It will still return cv::Point2f list for backward compatibility, but the inner computations are controlled by a typedef
- [X] I agree to contribute to the project under Apache 2 License.
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Re-implement named parameters bindings for Python #23705
Reverted named argument handling from #19156.
Ported new solution from #23224
The port is required to harmonize 4.x -> 5.x merges.
### Pull Request Readiness Checklist
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imgproc: add basic IntelligentScissorsMB performance test #23698
Adding basic performance test that can be used before and after the #21959 changes etc. as per @asmorkalov's https://github.com/opencv/opencv/pull/21959#issuecomment-1565240926 comment.
### Pull Request Readiness Checklist
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Pointer arithmetic overflow is always undefined, whether signed or unsigned.
It warned here:
`Addition of unsigned offset to 0x00017fd31b97 overflowed to 0x00017fd30c97`
Convert the offset to a signed number, so that we can offset either forward or backwards.
In my own use of OpenCV at least, this is the only case of pointer arithmetic overflow.
Import and export np.float16 in Python #23691
### Pull Request Readiness Checklist
* Also, fixes `cv::norm` with `NORM_INF` and `CV_16F`
resolves https://github.com/opencv/opencv/issues/23687
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Python typing stub generation #20370
Add stub generation to `gen2.py`, addressing #14590.
### Pull Request Readiness Checklist
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Python bindings for CV_8UC(n) and other types macros #23679
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23628#issuecomment-1562468327
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Support ONNX operator QLinearSoftmax in dnn #23655
Resolves https://github.com/opencv/opencv/issues/23636.
Merge with https://github.com/opencv/opencv_extra/pull/1064.
This PR maps the QLinearSoftmax (from com.microsoft domain) to SoftmaxInt8 in dnn along with some speed optimization.
Todo:
- [x] support QLinearSoftmax with opset = 13
- [x] add model and test data for QLinearSoftmax with opset = 13
- [x] ensure all models have dims >= 3.
- [x] add the script to generate model and test data
### Pull Request Readiness Checklist
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CV_MAKETYPE Python binding #23674
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23628
```python
import cv2 as cv
t = cv.CV_MAKETYPE(cv.CV_32F, 4)
```
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Fix truncated sentenced in boxPoints documentation #22975#23662Resolves#22975
Completed the sentence as per the suggestion given in the issue #22975
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QRCodeDetector: don't floodFill with outside-of-image seedPoint #23612Fixes#21532.
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/build/build_cuda/3p/opencv/linux-x64/ubuntu22.04/Debug/modules/dnn/src/layers/cpu_kernels/convolution.cpp: In function 'void cv::dnn::packData8(char*&, float*&, int&, int&, int&, const int*, int, int, int)':
/build/build_cuda/3p/opencv/linux-x64/ubuntu22.04/Debug/modules/dnn/src/layers/cpu_kernels/convolution.cpp:448:43: error: 'CONV_NR' was not declared in this scope; did you mean 'CONV_3D'?
448 | vx_store(inpbufC_FP32 + k*CONV_NR, vx_load(inptrInC + k1));
| ^~~~~~~
| CONV_3D
