Fix race condition in InternalFFMpegRegister initialization. #25419
initLogger_ does not check if the logger has been initizalized before and it might initialize it several times from different threads, racing with other threads that are logging.
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Handle top and left border masked pixels correctly in inpaint method #25402Fixes#25389
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Fixed ONNX range layer #25414
Partially address https://github.com/opencv/opencv/issues/25363
Fixed ONNX range layer. It should support any input type.
Added tests (extra [PR](https://github.com/opencv/opencv_extra/pull/1170))
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Move Charuco/Calib tutorials and samples to main repo #25378
Merge with https://github.com/opencv/opencv_contrib/pull/3708
Move Charuco/Calib tutorials and samples to main repo:
- [x] update/fix charuco_detection.markdown and samples
- [x] update/fix charuco_diamond_detection.markdown and samples
- [x] update/fix aruco_calibration.markdown and samples
- [x] update/fix aruco_faq.markdown
- [x] move tutorials, samples and tests to main repo
- [x] remove old tutorials, samples and tests from contrib
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Rename remaining float16_t for future proof #25387
Resolves comment: https://github.com/opencv/opencv/pull/25217#discussion_r1547733187.
`std::float16_t` and `std::bfloat16_t` are introduced since c++23: https://en.cppreference.com/w/cpp/types/floating-point.
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core: persistence: output reals as human-friendly expression. #25351Close#25073
Related https://github.com/opencv/opencv/pull/25087
This patch is need to merge same time with https://github.com/opencv/opencv_contrib/pull/3714
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imgproc: fix unaligned memory access in filters and Gaussian blur #25364
* filter/SIMD: removed parts which casted 8u pointers to int causing unaligned memory access on RISC-V platform.
* GaussianBlur/fixed_point: replaced casts from s16 to u32 with union operations
Performance comparison:
- [x] check performance on x86_64 - (4 threads, `-DCPU_BASELINE=AVX2`, GCC 11.4, Ubuntu 22) - [report_imgproc_x86_64.ods](https://github.com/opencv/opencv/files/14904702/report_x86_64.ods)
- [x] check performance on AArch64 - (4 cores of RK3588, GCC 11.4 aarch64, Raspbian) - [report_imgproc_aarch64.ods](https://github.com/opencv/opencv/files/14908437/report_aarch64.ods)
Note: for some reason my performance results are quite unstable, unaffected functions show speedups and slowdowns in many cases. Filter2D and GaussianBlur seem to be OK.
Slightly related PR: https://github.com/opencv/ci-gha-workflow/pull/165
Reworked findContours to reduce C-API usage #25146
What is done:
* rewritten `findContours` and `icvApproximateChainTC89` using C++ data structures
* extracted LINK_RUNS mode to separate new public functions - `findContoursLinkRuns` (it uses completely different algorithm)
* ~added new public `cv::approximateChainTC89`~ - **❌ decided to hide it**
* enabled chain code output (method = 0, no public enum value for this in C++ yet)
* kept old function as `findContours_old` (exported, but not exposed to user)
* added more tests for findContours (`test_contours_new.cpp`), some tests compare results of old function with new one. Following tests have been added:
* contours of random rectangle
* contours of many small (1-2px) blobs
* contours of random noise
* backport of old accuracy test
* separate test for LINK RUNS variant
What is left to be done (can be done now or later):
* improve tests:
* some tests have limited verification (e.g. only verify contour sizes)
* perhaps reference data can be collected and stored
* maybe more test variants can be added (?)
* add enum value for chain code output and a method of returning starting points (e.g. first 8 elements of returned `vector<uchar>` can represent 2 int point coordinates)
* add documentation for new functions - **✔️ DONE**
* check and improve performance (my experiment showed 0.7x-1.1x some time ago)
* remove old functions completely (?)
* change contour return order (BFS) or allow to select it (?)
* return result tree as-is (?) (new data structures should be exposed, bindings should adapt)
core: doc: add note for countNonZero, hasNonZero and findNonZero #25356Close#25345
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[BugFix] dnn (ONNX): Foce dropping constant inputs in parseClip if they are shared #25319
Resolves https://github.com/opencv/opencv/issues/25278
Merge with https://github.com/opencv/opencv_extra/pull/1165
In Gold-YOLO ,`Div` has a constant input `B=6` which is then parsed into a `Const` layer in the ONNX importer, but `Clip` also has the shared constant input `max=6` which is already a `Const` layer and then connected to `Elementwise` layer. This should not happen because in the `forward()` of `Elementwise` layer, the legacy code goes through and apply activation to each input. More details on https://github.com/opencv/opencv/issues/25278#issuecomment-2032199630.
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Ownership check in TFLite importer #25312
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resolves https://github.com/opencv/opencv/issues/25310
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Optimize int8 layers in DNN modules by using RISC-V Vector intrinsic. #25230
This patch optimize 3 functions in the int8 layer by using RVV Native Intrinsic.
This patch was tested on QEMU using VLEN=128 and VLEN=256 on `./bin/opencv_test_dnn --gtest_filter="*Int8*"`;
On the real device (k230, VLEN=128), `EfficientDet_int8` in `opencv_perf_dnn` showed a performance improvement of 1.46x.
| Name of Test | Original | optimized | Speed-up |
| ------------------------------------------ | -------- | ---------- | -------- |
| EfficientDet_int8::DNNTestNetwork::OCV/CPU | 2843.467 | 1947.013 | 1.46 |
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imgcodecs: jpeg: re-support to read CMYK Jpeg #25280Close#25274
OpenCV Extra: https://github.com/opencv/opencv_extra/pull/1163
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Merge with https://github.com/opencv/opencv_extra/pull/1158
Todo:
- [x] Fix Attention pattern recognition.
- [x] Handle other backends.
Benchmark:
"VIT_B_32 OCV/CPU", M1, results in milliseconds.
| Model | 4.x | This PR |
| - | - | - |
| VIT_B_32 OCV/CPU | 87.66 | **83.83** |
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Orbbec Camera supports MacOS，Gemini2 and Gemini2L support Y16 format #24877
note:
1.Gemini2 and Gemini2L must use the latest firmware -- https://github.com/orbbec/OrbbecFirmware;
2.Administrator privileges are necessary to run on MacOS.
Add imread #24415
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Hello everyone,
I created this new version of the imread function and I think it can be very useful in several cases.
It is actually passed to it object on which you want to upload the image.
The advantages can be different like in case one needs to open several large images all the same in sequence.
one can use the same pointer and the system would not allocate memory each time.
libjpeg upgrade to version 9f #25092
Upgrade libjpeg dependency from version 9d to 9f.
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The parallel code works out how many CPUs are on the system by checking
the quota it has been assigned in the Linux cgroup. The existing code
works under cgroups v1 but the file structure changed in cgroups v2.
From [1]:
"cpu.cfs_quota_us" and "cpu.cfs_period_us" are replaced by "cpu.max"
which contains both quota and period.
This commit add support to parallel so it will read from the cgroups v2
location. v1 support is still retained.
Resolves#25284
[1] 0d5936344f
fengyuentau
Maksim Shabunin
Vincent Rabaud
Linaname
Alexander Smorkalov
alexlyulkov
Alexander Panov
mikhail.shtennikov
Kumataro
Vadim Levin
ecchen
Alexander Lyulkov
Tsukasa Sugiura
MaximSmolskiy
Susumu IINO
Liutong HAN
Dmitry Kurtaev
catree
sepperliu
utibenkei
Yuantao Feng
zzuliys
thewoz
Michael Klatis
John Slade