Animated PNG Support #25715
Continues https://github.com/opencv/opencv/pull/25608
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AndroidMediaNdkCapture pixel format enhancement #26656
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Open VideoCapture from data stream #25584
### Pull Request Readiness Checklist
Add VideoCapture option to read a raw binary video data from `std::streambuf`.
There are multiple motivations:
1. Avoid disk file creation in case of video already in memory (received by network or from database).
2. Streaming mode. Frames decoding starts during sequential file transfer by chunks.
Suppoted backends:
* FFmpeg
* MSMF (no streaming mode)
Supporter interfaces:
* C++ (std::streambuf)
* Python (io.BufferedIOBase)
resolves https://github.com/opencv/opencv/issues/24400
- [x] test h264
- [x] test IP camera like approach with no metadata but key frame only?
- [x] C API plugin
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Use size_t when calculating size of all_points #26650Closes: #26642
Asan log
```
=================================================================
==41401==ERROR: AddressSanitizer: heap-buffer-overflow on address 0x7fc55a02a3fc at pc 0x7fc58e304131 bp 0x7ffd54787b00 sp 0x7ffd54787af8
WRITE of size 4 at 0x7fc55a02a3fc thread T0
#0 0x7fc58e304130 in cv::QRDetectMulti::checkSets(std::vector<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > >, std::allocator<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > > > >&, std::vector<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > >, std::allocator<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > > > >&, std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > >&) /home/fanta/source/opencv/modules/objdetect/src/qrcode.cpp:3726
#1 0x7fc58e3054b0 in cv::QRDetectMulti::localization() /home/fanta/source/opencv/modules/objdetect/src/qrcode.cpp:3829
#2 0x7fc58e308020 in cv::ImplContour::detectMulti(cv::_InputArray const&, cv::_OutputArray const&) const /home/fanta/source/opencv/modules/objdetect/src/qrcode.cpp:3987
#3 0x7fc58e30b5b1 in cv::ImplContour::detectAndDecodeMulti(cv::_InputArray const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > >&, cv::_OutputArray const&, cv::_OutputArray const&) const /home/fanta/source/opencv/modules/objdetect/src/qrcode.cpp:4176
#4 0x7fc58e28922f in cv::GraphicalCodeDetector::detectAndDecodeMulti(cv::_InputArray const&, std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > >&, cv::_OutputArray const&, cv::_OutputArray const&) const /home/fanta/source/opencv/modules/objdetect/src/graphical_code_detector.cpp:42
#5 0x5954e8 in Body /home/fanta/source/opencv/modules/objdetect/test/test_qrcode.cpp:48
#6 0x594fc0 in TestBody /home/fanta/source/opencv/modules/objdetect/test/test_qrcode.cpp:42
#7 0x67ee6a in void testing::internal::HandleSehExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:3919
#8 0x6734a4 in void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:3955
#9 0x641fe8 in testing::Test::Run() /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:3993
#10 0x6431ac in testing::TestInfo::Run() /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:4169
#11 0x643d15 in testing::TestCase::Run() /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:4287
#12 0x659ff3 in testing::internal::UnitTestImpl::RunAllTests() /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:6662
#13 0x681205 in bool testing::internal::HandleSehExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:3919
#14 0x675127 in bool testing::internal::HandleExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:3955
#15 0x65734c in testing::UnitTest::Run() /home/fanta/source/opencv/modules/ts/src/ts_gtest.cpp:6271
#16 0x5907f0 in RUN_ALL_TESTS() /home/fanta/source/opencv/modules/ts/include/opencv2/ts/ts_gtest.h:22240
#17 0x590cdd in main (/home/fanta/source/opencv-build-4.x-clang/bin/opencv_test_objdetect+0x590cdd) (BuildId: a9363fc788d57c48225fc0559ac9199d07d415db)
#18 0x7fc58ab242ad in __libc_start_call_main (/lib64/libc.so.6+0x2a2ad) (BuildId: 03f1631dc9760d3e30311fe62e15cc4baaa89db7)
#19 0x7fc58ab24378 in __libc_start_main@@GLIBC_2.34 (/lib64/libc.so.6+0x2a378) (BuildId: 03f1631dc9760d3e30311fe62e15cc4baaa89db7)
#20 0x417014 in _start ../sysdeps/x86_64/start.S:115
0x7fc55a02a3fc is located 0 bytes after 2938510332-byte region [0x7fc4aadc8800,0x7fc55a02a3fc)
allocated by thread T0 here:
#0 0x7fc58e590298 in operator new(unsigned long) (/lib64/libasan.so.8+0xfd298) (BuildId: da72ee674d801ced58193987786b90646d94ff8d)
#1 0x7fc58e34d010 in std::__new_allocator<cv::Vec<int, 3> >::allocate(unsigned long, void const*) /usr/include/c++/14/bits/new_allocator.h:151
SUMMARY: AddressSanitizer: heap-buffer-overflow /home/fanta/source/opencv/modules/objdetect/src/qrcode.cpp:3726 in cv::QRDetectMulti::checkSets(std::vector<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > >, std::allocator<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > > > >&, std::vector<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > >, std::allocator<std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > > > >&, std::vector<cv::Point_<float>, std::allocator<cv::Point_<float> > >&)
Shadow bytes around the buggy address:
0x7fc55a02a100: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
0x7fc55a02a180: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
0x7fc55a02a200: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
0x7fc55a02a280: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
0x7fc55a02a300: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
=>0x7fc55a02a380: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00[04]
0x7fc55a02a400: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x7fc55a02a480: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x7fc55a02a500: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x7fc55a02a580: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x7fc55a02a600: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
Shadow byte legend (one shadow byte represents 8 application bytes):
Addressable: 00
Partially addressable: 01 02 03 04 05 06 07
Heap left redzone: fa
Freed heap region: fd
Stack left redzone: f1
Stack mid redzone: f2
Stack right redzone: f3
Stack after return: f5
Stack use after scope: f8
Global redzone: f9
Global init order: f6
Poisoned by user: f7
Container overflow: fc
Array cookie: ac
Intra object redzone: bb
ASan internal: fe
Left alloca redzone: ca
Right alloca redzone: cb
==41401==ABORTING
```
`(true_points_group[i].size()` is 1794 and `(true_points_group[i].size() - 2 ) * (true_points_group[i].size() - 1) * true_points_group[i].size())` is 5764222464 which overflows `int`
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Faster implementation of blobFromImages for cpu nchw output #26127
Faster implementation of blobFromImage and blobFromImages for
HWC cv::Mat images -> NCHW cv::Mat
case
Running time on my pc in ms:
**blobFromImage**
```
image size old new speed-up
32x32x3 0.008 0.002 4.0x
64x64x3 0.021 0.009 2.3x
128x128x3 0.164 0.037 4.4x
256x256x3 0.728 0.158 4.6x
512x512x3 3.310 0.628 5.2x
1024x1024x3 14.503 3.124 4.6x
2048x2048x3 61.647 28.049 2.2x
```
**blobFromImages**
```
image size old new speed-up
16x32x32x3 0.122 0.041 3.0x
16x64x64x3 0.790 0.165 4.8x
16x128x128x3 3.313 0.652 5.1x
16x256x256x3 13.495 3.127 4.3x
16x512x512x3 58.795 28.127 2.1x
16x1024x1024x3 251.135 121.955 2.1x
16x2048x2048x3 1023.570 487.188 2.1x
```
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Animated WebP Support #25608
related issues #24855#22569
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V4l default image size #25500
Added ability to set default image width and height for V4L capture. This is required for cameras that does not support 640x480 resolution because otherwise V4L capture cannot be opened and failed with "Pixel format of incoming image is unsupported by OpenCV" and then with "can't open camera by index" message. Because of the videoio architecture it is not possible to insert actions between CvCaptureCAM_V4L::CvCaptureCAM_V4L and CvCaptureCAM_V4L::open so the only way I found is to use environment variables to preselect the resolution.
Related bug report is [#25499](https://github.com/opencv/opencv/issues/25499)
Maybe (but not confirmed) this is also related to [#24551](https://github.com/opencv/opencv/issues/24551)
This fix was made and verified in my local environment: capture board AVMATRIX VC42, Ubuntu 20, NVidia Jetson Orin.
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Fix VideoCapture fails to read single image with digits in name #26637
### Pull Request Readiness Checklist
Fix#26457
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js: fix generation of "const const" in code #26640
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Android camera feature enhancements #26627
Closes https://github.com/opencv/opencv/issues/24687
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More convenient GpuMatND constructor #26472Closes#26471
For convenience, GpuMatND can now accept a step.size() equal to size.size(), as long as the last step is equal to elemSize()
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Switch calibration.cpp to C++ #26490
The CvLevMarq code has to be kept in order to keep the same accuracy (the C++ solver is not as good).
There are two ways to review this PR: by comparing to the old code, or by checking what is different from the 5.x version (which is the first commit).
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Support C++20 standard #26590
Close https://github.com/opencv/opencv/issues/26589
Related https://github.com/opencv/opencv_contrib/pull/3842
Related: https://github.com/opencv/opencv/issues/20269
- do not arithmetic enums and ( different enums or floating numeric)
- remove unused variable
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Previously, the yoloPostProcessing function assumed that the number of classes (nc) was fixed at 80. This caused incorrect behavior when a different number of classes was specified, leading to mismatched output shapes.
This update modifies the code to use the provided `nc` value dynamically, ensuring that the output shapes are correctly calculated based on the specified number of classes. This prevents issues when `nc` is not equal to 80 and allows for greater flexibility in model configurations.
Fix#25812: Add error handling for invalid nu parameter in SVM NU_SVC #26587
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Updated trackbar callback function and improved documentation #26524
This Fixes#26467
Description:
This pull request improve the OpenCV documentation regarding the Trackbar functionality. The current documentation does not provide clear guidance on certain aspects, such as handling the value pointer deprecation and utilizing callback arguments in C. This update addresses those gaps and provides an updated example for better clarity.
Changes:
Updated Documentation:
Clarified the usage of the value pointer and explained how to pass an initial value, since the value pointer is deprecated.
Added more detailed explanations about callback arguments in C, ensuring that users understand how to access and use them in Trackbar callbacks.
Added a note on how to properly handle initial value passing without relying on the deprecated value pointer.
Updated Tutorial Example:
Renamed and used callback function parameters to make them more understandable.
Included a demonstration on how to utilize userdata in the callback function.
Additional Notes:
Removed reliance on the value pointer for updating trackbar values. Users are now encouraged to use other mechanisms as per the current implementation to avoid the runtime warning.
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An upcoming change in Protobuf will change the return types of various
methods like Descriptor::name() and Message::GetTypeName() from const
std::string& or std::string to absl::string_view. This CL fixes users
of those methods to work both before and after the change.
[GSoC] Add GIF decode and encode for imgcodecs #25691
this is related to #24855
we add gif support for `imread`, `imreadmulti`, `imwrite` and `imwritemulti`
opencv_extra: https://github.com/opencv/opencv_extra/pull/1203
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Missing include directories needed for wayland-util and xkbcommon #26563
See: #26561
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Emscripten build fixes#26537
- Corrects typo in Emscripten-only intrinsics header (Fixes https://github.com/opencv/opencv/issues/26536)
- Updates deprecated intrinsic title (as per LLVM final intrinsic name).
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HAL added for absdiff(array, scalar) + related fixes#26459
### This PR changes
* HAL for `absdiff` when one of arguments is a scalar, including multichannel arrays and scalars
* several channels support for HAL `addScalar`
* proper data type check for `addScalar` when one of arguments is a scalar
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The new C++ code is copy/pasted from OpenCV5:
- functions initIntrinsicParams2D, subMatrix (the first 160 lines)
- function prepareDistCoeffs
- the different asserts
Not all the API/code is ported to C++ yet to ease the review.
HAL added for add(array, scalar) #25624
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int64 data type support for FileStorage. 1d and empty Mat with exact dimensions #26434
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Port of https://github.com/opencv/opencv/pull/26399 to 4.x branch
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Backport C++ stereo/stereo_geom.cpp:5.x to calib3d/stereo_geom.cpp:4.x #26437
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Use LMUL=2 in the RISC-V Vector (RVV) backend of Universal Intrinsic. #26318
The modification of this patch involves the RVV backend of Universal Intrinsic, replacing `LMUL=1` with `LMUL=2`.
Now each Universal Intrinsic type actually corresponds to two RVV vector registers, and each Intrinsic function also operates two vector registers. Considering that algorithms written using Universal Intrinsic usually do not use the maximum number of registers, this can help the RVV backend utilize more register resources without modifying the algorithm implementation
This patch is generally beneficial in performance.
We compiled OpenCV with `Clang-19.1.1` and `GCC-14.2.0` , ran it on `CanMV-k230` and `Banana-Pi F3`. Then we have four scenarios on combinations of compilers and devices. In `opencv_perf_core`, there are 3363 cases, of which:
- 901 (26.8%) cases achieved more than `5%` performance improvement in all four scenarios, and the average speedup of these test cases (compared to scalar) increased from `3.35x` to `4.35x`
- 75 (2.2%) cases had more than `5%` performance loss in all four scenarios, indicating that these cases are better with `LMUL=1` instead of `LMUL=2`. This involves `Mat_Transform`, `hasNonZero`, `KMeans`, `meanStdDev`, `merge` and `norm2`. Among them, `Mat_Transform` only has performance degradation in a few cases (`8UC3`), and the actual execution time of `hasNonZero` is so short that it can be ignored. For `KMeans`, `meanStdDev`, `merge` and `norm2`, we should be able to use the HAL to optimize/restore their performance. (In fact, we have already done this for `merge` #26216 )
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imgcodecs: implement imencodemulti() #26211Close#26207
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G-API: Introduce level optimization flag for ONNXRT backend #26293
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Use border value in ipp version of warp affine #26313
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Proposed solution for the issue 26297 #26298closes#26297
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Add support for v_sin and v_cos (Sine and Cosine) #25892
This PR aims to implement `v_sincos(v_float16 x)`, `v_sincos(v_float32 x)` and `v_sincos(v_float64 x)`.
Merged after https://github.com/opencv/opencv/pull/25891 and https://github.com/opencv/opencv/pull/26023
**NOTE:**
Also, the patch changes already added `v_exp`, `v_log` and `v_erf` to pass parameters by reference instead of by value, to match API of other universal intrinsics.
TODO:
- [x] double and half float precision
- [x] tests for them
- [x] doc to explain the implementation
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- Implemented a new `create` method in `FaceRecognizerSF` to allow model and configuration loading from memory buffers (std::vector<uchar>), similar to the existing functionality in `FaceDetectorYN`.
- Updated `face_recognize.cpp` with a new constructor in `FaceRecognizerSFImpl` that supports buffer-based loading for both model weights and network configuration.
- Ensured compatibility with both file-based and buffer-based model loading by maintaining consistent backend and target settings across both constructors.
- This change improves flexibility, allowing FaceRecognizerSF to be instantiated from memory buffers, which is useful for dynamic model loading scenarios such as embedded systems or applications where models are loaded in-memory.
Update Documentation #26260
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Update intrin_wasm.hpp #25909
See https://github.com/microsoft/vcpkg/issues/33443 for some build context when using
```vcpkg install opencv4:wasm32-emscripten```
`__EMSCRIPTEN_major__`, `__EMSCRIPTEN_minor__` and `__EMSCRIPTEN_tiny__` in `emsdk` >= 3.1.4 are in a header, as opposed to command line.
We could potentially be more aggressive with how I'm checking this property; let me know if I should make the change.
It should also be suggested that `-msimd128` is auto-included in the associated portfile for opencv, but that's a separate issue. Someone let me know if I should also make that change as well.
Special thanks to https://github.com/youar for supporting this work; please inform if applying a copyright-header is appropriate attribution.
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core: C-API cleanup: RNG algorithms in core(4.x) #26259
- replace CV_RAND_UNI and NORMAL to cv::RNG::UNIFORM and cv::RNG::NORMAL.
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* use 2 parms for now to identify the error
* Revert "use 2 parms for now to identify the error"
This reverts commit 86faf993a7.
* replace += with =
* add v_log ref
* refactor intrin_math code
* Add include guard to `intrin_math.hpp` to prevent multiple inclusions
* rename VX to V; make fp64 impl in neon be optional
* add v_setall, v_setzero for all backends; rewrite the intrin_math
* fix error on rvv_scalable
* let v_erf use v_exp_default_32f function
* 1. replaced 'v_setzero(VecType dummy)' with 'v_setzero_<VecType>()'
2. replaced 'v_setall(LaneType x, VecType dummy)' with 'v_setall_<VecType>(LaneType x)'
3. added tests for the new v_setzero_<> and v_setall_<>.
* gcc does not seem to like static_assert in functions even when they are not used
* trying to fix compile errors in Debug mode on Linux
---------
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
Mirror most recent changes from https://github.com/terzakig/sqpnp/pull/24
- rank revealing QR in nullspace computation
- sqrt-free Cholesky (i.e., L*D*Lt) in the SQP solution
- replaced divisions with multiplications by inverses
- simplified checks in computeRowAndNullspace()
- removed unnecessary negations
- broke some dependency chains with parentheses
- minor other changes
HAL interface for Sharr derivatives needed for Lukas-Kanade algorithm #26163
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Documentation update for imagecodecs #26152
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Added HAL interface for Lukas-Kanade optical flow #26143
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Documentation update for minMaxLoc #25785Fixes#25784
Update documentation for minMaxLoc to be more specific about when multi-channel images are and are not supported.
Testing:
Built documentation locally to check that updates were incorporated correctly.
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Replace operators with wrapper functions on universal intrinsics backends #26109
This PR aims to replace the operators(logic, arithmetic, bit) with wrapper functions(v_add, v_eq, v_and...)
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Add size() to CUDA PtrStepSz #26042
According to [cppreference.com compiler support table](https://en.cppreference.com/w/cpp/compiler_support/17), `nvcc` supports `[[nodiscard]]` from version 11.
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Related: https://github.com/opencv/opencv/pull/25659
Added more data types to OCL flip() and rotate() perf tests #26115
Connected PR with updated sanity data: https://github.com/opencv/opencv_extra/pull/1206
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Avoid uninitialized value read in resize. #26084
When there is no point falling right, an hypothetical value is computed (but unused) using an uninitialized ofst. This triggers warnings in the sanitizers.
Including those values in the for loops is also possible but messy when SIMD is involved.
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Remove the redundant codes of cv::convertMaps and mRGBA2RGBA<uchar> #26071
(1) cv::convertMaps: the branch [else if( m1type == CV_32FC2 && dstm1type == CV_16SC2 ) if( nninterpolate )] is unreachable,
as the condition is satisfied in lines 1959 to 1961, calculated in advance and return directly.
(2) mRGBA2RGBA<uchar>: dst[0], dst[1], dst[2] and dst[3] is calculated repeatedly. Introduced in https://github.com/opencv/opencv/pull/13440
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Update test_tiff.cpp #26093
related #22090
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Added offset for HAL as ofs2idx expects 1-based index #26080
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DNN(ONNX): Enabled several OpenCL conformance tests #26053
The tests also work in 5.x
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Fixed the simd bugs of iPow8u and iPow16u #26061
Add the following cases in opencv_perf_core:
* OCL_PowFixture_iPow.iPow/0, where GetParam() = (640x480, 8UC1)
* OCL_PowFixture_iPow.iPow/2, where GetParam() = (640x480, 16UC1)
iPow8u and iPow16u failed to call to simd accelerating while executing.
Fix the bug by changing the input type of iPow_SIMD function.
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Einsum buffer allocation fix#26059
This PR fixed buffer allocation issue in Einsum layer that causes segmentation fault on 32bit platforms. Related issue #26008
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Imgproc: use double to determine whether the corners points are within src #26022close#26016
Related https://github.com/opencv/opencv_contrib/pull/3778
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Split Javascript white-list to support contrib modules #25986
Single whitelist converted to several per-module json files. They are concatenated automatically and can be overriden by user config.
Related to https://github.com/opencv/opencv/pull/25656
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Increase neighbors search radius for corners in ChessBoardDetector:findQuadNeighbors #26014
I didn't do everything right the way I wanted at #25991. I forgot that `edge_len` is edge **squared** length as well as `thresh_scale` is threshold for **squared** scale. So, I wanted to increase scale by `sqrt(2)` times (idea is to use quad diagonal instead of quad side) and therefore `thresh_scale` should be equal to `sqrt(2)^2 = 2`.
And refactor variables names to explicitly indicate that they are squared, so that no one else falls into this trap
I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```
PR increases detected chessboards number by `1/2%`:
```
cell_img_size = 100 (default)
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.941667 13560 14400 0.596726
Total detected time: 136.68963200000007 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.952083 13710 14400 0.595984
Total detected time: 136.55770600000014 sec
----------------------------------------------------------------------------------------------------------------------------------------------
cell_img_size = 10
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.579167 8340 14400 4.198448
Total detected time: 2.535998999999999 sec
after
category detected chessboard total detected chessboard total chessboard average detected error
all 0.591389 8516 14400 4.155250
Total detected time: 2.700832999999997 sec
```
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dnn: add ONNX TopK #23279
Merge with https://github.com/opencv/opencv_extra/pull/1200
Partially fixes#22890 and #20258
To-do:
- [x] TopK forward impl
- [x] add tests
- [x] support Opset 1 & 10 if possible
- [ ] ~Support other backends~ (TopK has two outputs, which is not supported by other backends, such as openvino)
Perf:
M1 (time in millisecond)
| input shape | axis | dnn | ort |
| --------------- | ---- | ---- | ---- |
| (1000, 100) | 0 | 1.68 | 4.07 |
| (1000, 100) K5 | 0 | 1.13 | 0.12 |
| (1000, 100) | 1 | 0.96 | 0.77 |
| (100, 100, 100) | 0 | 10.00 | 31.13 |
| (100, 100, 100) | 1 | 7.33 | 9.17 |
| (100, 100, 100) | 2 | 7.52 | 9.48 |
M2 (time in milisecond)
| input shape | axis | dnn | ort |
| --------------- | ---- | ---- | ---- |
| (1000, 100) | 0 | 0.76 | 2.44 |
| (1000, 100) K5 | 0 | 0.68 | 0.07 |
| (1000, 100) | 1 | 0.41 | 0.50 |
| (100, 100, 100) | 0 | 4.83 | 17.52|
| (100, 100, 100) | 1 | 3.60 | 5.08 |
| (100, 100, 100) | 2 | 3.73 | 5.10 |
ONNXRuntime performance testing script: https://gist.github.com/fengyuentau/a119f94fd16721ec9974b8c7b0a45d4c
### Pull Request Readiness Checklist
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Correct Bayer2Gray u8 SIMD #25968
SIMD version of CV_DESCALE is not correct. It should be implemented using v_dotprod.
What's more, the stop condition of vector operation should be `bayer < bayer_end - 14` because we just need to make sure result is safely stored into `dst`.
Closes: https://github.com/opencv/opencv/issues/25823
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Unified build.gradle files into one template #26009
Issue #24686
### Pull Request Readiness Checklist
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Fix typos #26038
Fix typos
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imgproc: add specific error code when cvtColor is used on an image with an invalid number of channels #25981close#25971
### Pull Request Readiness Checklist
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Add support for QNX #25832
Build and test instruction for QNX:
https://github.com/chachoi-world/qnx-ports/blob/main/opencv/README.md
### Pull Request Readiness Checklist
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pyrDown: offset HAL added, IPP removed #25970Resolves#25976
### Changes
* HAL added for offset support so that border pixels can be fetched from outside of the image ROI (see `BORDER_ISOLATED` parameter)
* IPP removed since there is `pyrUp` instead of `pyrDown` and there's no easy way to fix this other than rewriting it from scratch
* replaced old C call by modern `cv::pyrDown`
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Added xxxApprox overloads for YUV color conversions in HAL and AlgorithmHint to cvtColor #25932
The xxxApprox to implement HAL functions with less bits for arithmetic of FP.
The hint was introduced in #25792 and #25911
### Pull Request Readiness Checklist
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Improve corners matching in ChessBoardDetector::NeighborsFinder::findCornerNeighbor #25991
### Pull Request Readiness Checklist
Idea was mentioned in `Section III-B. New Heuristic for Quadrangle Linking` of `Rufli, Martin & Scaramuzza, Davide & Siegwart, Roland. (2008). Automatic Detection of Checkerboards on Blurred and Distorted Images. 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS. 3121-3126. 10.1109/IROS.2008.4650703` (https://rpg.ifi.uzh.ch/docs/IROS08_scaramuzza_b.pdf):
```
* For each candidate pair, focus on the quadrangles they belong to and draw two straight lines passing through the midsections of the respective quadrangle edges (see Fig. 6).
* If the candidate corner and the source corner are on the same side of every of the four straight lines drawn this way (this corresponds to the yellow shaded area in Fig. 6), then the corners are successfully matched.
```
By improving corners matching, we can increase the search radius (`thresh_scale`).
I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```
PR increases detected chessboards number by `3/7%`:
```
cell_img_size = 100 (default)
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.910417 13110 14400 0.599746
Total detected time: 147.50906700000002 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.941667 13560 14400 0.596726
Total detected time: 136.68963200000007 sec
----------------------------------------------------------------------------------------------------------------------------------------------
cell_img_size = 10
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.539792 7773 14400 4.208237
Total detected time: 2.668964 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.579167 8340 14400 4.198448
Total detected time: 2.535998999999999 sec
```
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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Patch to opencv_extra has the same branch name.
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Current code using CMAKE_SOURCE_DIR and it works well if opencv is standalone CMake project,
but in case of building OpenCV as part of a larger CMake project (e.g. one that includes
opencv and opencv_contrib) this path is incorrect, unlike OpenCV_SOURCE_DIR
To be on par with `cv::Mat`, let's add `cv::cuda::GpuMat::getStdAllocator()`
This is useful anyway, because when a user wants to use custom allocators, he might want to resort to the standard default allocator behaviour, not some other allocator that could have been set by `setDefaultAllocator()`
[GSoC] dnn: Blockwise quantization support #25644
This PR introduces blockwise quantization in DNN allowing the parsing of ONNX models quantized in blockwise style. In particular it modifies the `Quantize` and `Dequantize` operations. The related PR opencv/opencv_extra#1181 contains the test data.
Additional notes:
- The original quantization issue has been fixed. Previously, for 1D scale and zero-point, the operation applied was $y = int8(x/s - z)$ instead of $y = int8(x/s + z)$. Note that the operation was already correctly implemented when the scale and zero-point were scalars. The previous implementation failed the ONNX test cases, but now all have passed successfully. [Reference](https://github.com/onnx/onnx/blob/main/docs/Operators.md#QuantizeLinear)
- the function `block_repeat` broadcasts scale and zero-point to the input shape. It repeats all the elements of a given axis n times. This function generalizes the behavior of `repeat` from the core module which is defined just for 2 axis assuming `Mat` has 2 dimensions. If appropriate and useful, you might consider moving `block_repeat` to the core module.
- Now, the scale and zero-point can be taken as layer inputs. This increases the ONNX layers' coverage and enables us to run the ONNX test cases (previously disabled) being fully compliant with ONNX standards. Since they are now supported, I have enabled the test cases for: `test_dequantizelinear`, `test_dequantizelinear_axis`, `test_dequantizelinear_blocked`, `test_quantizelinear`, `test_quantizelinear_axis`, `test_quantizelinear_blocked` just in CPU backend. All of them pass successfully.
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modules/js/perf/perf_helpfunc.js and target tests, e.g. perf_gaussianBlur.js contained "const isNodeJs", leading to re-definition when using associated *.html files.
Search in two directions when try to add new quad in addOuterQuad #25807
In ChessBoardDetector::addOuterQuad, previous code try to connect new quad with inner quad, if possible, but only search for one direction. I have made three test images, one is normal(a.jpg), one lossed an outer quad(b.jpg), and then i flipped it vertically(c.jpg). Only last one fails. I fixed it by check two directions and row/col.
Here is the test code and images:
```
Mat img;
vector<Point2f> corners;
auto size = cv::Size(6, 6);
img = imread("D:/tmp/a.jpg", 0);
std::cout<<cv::findChessboardCorners(img, size, corners)<<"\n";
std::cout << corners.size() << "\n";
img = imread("D:/tmp/b.jpg", 0);
std::cout<<cv::findChessboardCorners(img, size, corners)<<"\n";
std::cout << corners.size() << "\n";
img = imread("D:/tmp/c.jpg", 0);
std::cout<<cv::findChessboardCorners(img, size, corners)<<"\n";
std::cout << corners.size() << "\n";
```
a
b
c
Properly check markers when none are provided. #25938
CharucoDetectorImpl::detectBoard finds temporary markers when none are provided but those are discarded when
charucoDetectorImpl::checkBoard is called.
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HAL for dot product added #25936
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videoio: fix cv::VideoWriter with FFmpeg encapsulation timestamps #25874
Fix https://github.com/opencv/opencv/issues/25873 by modifying `cv::VideoWriter` to use provided presentation indices (pts).
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