Deprecate copyData Parameter in UMat Construction from std::vector and Always Copy Data #27408
Overview
This PR simplifies and modernizes the construction of cv::UMat from std::vector by removing the legacy copyData parameter, always copying the data, and ensuring clearer, safer semantics. This brings UMat in line with current best practices and paves the way for the upcoming OpenCV 5.x series.
What Changed?
1. Header Documentation Update
Removed confusing or obsolete documentation about copyData and clarified the behavior:
Old: builds matrix from std::vector with or without copying the data
New: builds matrix from std::vector. The data is always copied. The copyData parameter is deprecated and will be removed in OpenCV 5.0.
2. Implementation Update
In UMat::UMat(const std::vector<_Tp>& vec, bool copyData), the copyData parameter:
Is now ignored and marked as deprecated.
Marked with CV_UNUSED(copyData) for backward compatibility and to avoid warnings.
The constructor always copies the data from the input vector, regardless of the value of copyData.
All branching logic around copyData has been removed. Any code for "not copying" was not implemented and is now dropped.
This guarantees data safety and predictable behavior.
3. Test Added
A new test construct_from_vector in test_umat_from_vector.cpp:
Verifies that UMat copies the vector data, not referencing it.
Modifies the source vector after construction to confirm that the UMat is unaffected (proving copy, not reference).
Checks matrix shape, type, and content to ensure correctness.
Why This Change?
1. Safety and Predictability
Always copying avoids dangling references and hard-to-debug lifetime issues with stack/heap-allocated vectors.
Removes an undocumented, unimplemented branch (copyData=false).
2. Backward Compatibility
The constructor signature remains for now, but the copyData parameter is marked as deprecated and ignored.
Codebases that pass the parameter will still compile and run as before (but always copy).
3. API Clarity and Maintenance
Documentation now matches the real implementation.
No misleading expectations about zero-copy.
Code is cleaner, future-proof, and easier to maintain.
4. Preparation for OpenCV 5.0
The copyData parameter is deprecated and will be removed in OpenCV 5.x.
Prepares users and downstream libraries for the planned change.
How This Helps OpenCV Users and Developers
Guarantees data safety and makes behavior explicit.
Removes legacy/ambiguous code.
Provides a clear path to OpenCV 5.x.
Minimizes future migration pain.
Ensures all users see the same, reliable behavior (copy semantics).
Refer:#27409
Improve solveCubic accuracy #27347
### Pull Request Readiness Checklist
Fix#27323
```
2e-13 * x^3 + x^2 - 2 * x + 1 = 0 -> x^3 + 5e12 * x^2 - 1e13 * x + 5e12 = 0
```
The problem that coefficients have quite big magnitudes and current calculations are subject to round-off error
```
Q = (a1 * a1 - 3 * a2) * (1./9)
R = (2 * a1 * a1 * a1 - 9 * a1 * a2 + 27 * a3) * (1./54)
Qcubed = Q * Q * Q = a1^6/729 - (a1^4 a2)/81 + (a1^2 a2^2)/27 - a2^3/27
R * R = R^2 = a1^6/729 - (a1^4 a2)/81 + (a1^2 a2^2)/36 + (a1^3 a3)/27 - (a1 a2 a3)/6 + a3^2/4
d = Qcubed - R * R
```
Let `a1`, `a2`, `a3` have quite big same magnitudes, then we see that `Qcubed` and `R * R` have same terms `a1^6/729` and `-(a1^4 a2)/81` (which will be reduced in `d`), but they level out the other terms (these terms have `6`th and `5`th degree and other terms - less or equal than `4`th degree).
So, if these terms will participate in the calculation, this will lead to a huge round-off error.
But if we expand the expression, then round-off error should be less
```
d = Qcubed - R * R = 1/108 (a1^2 a2^2 - 4 a2^3 - 4 a1^3 a3 + 18 a1 a2 a3 - 27 a3^2)
```
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build: fix more warnings from recent gcc versions after #27337#27343
More fixings after https://github.com/opencv/opencv/pull/27337
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build: fix warnings from recent gcc versions #27337
This PR addresses the following found warnings:
- [x] -Wmaybe-uninitialized
- [x] -Wunused-variable
- [x] -Wsign-compare
Tested building with GCC 14.2 (RISC-V 64).
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Add tests for solveCubic #27331
### Pull Request Readiness Checklist
Related to #27323
I found only randomized tests with number of roots always equal to `1` or `3`, `x^3 = 0` and some simple test for Java and Swift.
Obviously, they don't cover all cases (implementation has strong branching and number of roots can be equal to `-1`, `0` and `2` additionally).
So, I think it will be useful to try explicitly cover more cases (and implementation branches correspondingly)
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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FastCV gemm hal #27184
FastCV hal for gemm 32f
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User-defined logger callback, C-style. #27154
This is a competing PR, an alternative to #27140
Both functions accept C-style pointer to static functions. Both functions allow restoring the OpenCV built-in implementation by passing in a nullptr.
- replaceWriteLogMessage
- replaceWriteLogMessageEx
This implementation is not compatible with C++ log handler objects.
This implementation has minimal thread safety, in the sense that the function pointer are stored and read atomically. But otherwise, the user-defined static functions must accept calls at all times, even after having been deregistered, because some log calls may have started before deregistering.
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Impl hal_rvv LUT | Add more LUT test #26941
Implement through the existing `cv_hal_lut` interfaces.
Add more LUT accuracy and performance tests:
- **Accuracy test**: Multi-channel table tests are added, and the boundary of `randu` used for generating test data is broadened to make the test more robust.
- **Performance test**: Multi-channel input and multi-channel table tests are added.
Perf test done on
- MUSE-PI (vlen=256)
- Compiler: gcc 14.2 (riscv-collab/riscv-gnu-toolchain Nightly: December 16, 2024)
```sh
$ opencv_test_core --gtest_filter="Core_LUT*"
$ opencv_perf_core --gtest_filter="SizePrm_LUT*" --perf_min_samples=300 --perf_force_samples=300
```
```sh
Geometric mean (ms)
Name of Test scalar ui rvv ui rvv
vs vs
scalar scalar
(x-factor) (x-factor)
LUT::SizePrm::320x240 0.248 0.249 0.052 1.00 4.74
LUT::SizePrm::640x480 0.277 0.275 0.085 1.01 3.28
LUT::SizePrm::1920x1080 0.950 0.947 0.634 1.00 1.50
LUT_multi2::SizePrm::320x240 2.051 2.045 2.049 1.00 1.00
LUT_multi2::SizePrm::640x480 2.128 2.134 2.125 1.00 1.00
LUT_multi2::SizePrm::1920x1080 7.397 7.380 7.390 1.00 1.00
LUT_multi::SizePrm::320x240 0.715 0.747 0.154 0.96 4.64
LUT_multi::SizePrm::640x480 0.741 0.766 0.257 0.97 2.88
LUT_multi::SizePrm::1920x1080 2.766 2.765 1.925 1.00 1.44
```
This optimization is achieved by loading the entire lookup table into vector registers. Due to register size limitations, the optimization is only effective under the following conditions:
- For the U8C1 table type, the optimization works when `vlen >= 256`
- For U16C1, it works when `vlen >= 512`
- For U32C1, it works when `vlen >= 1024`
Since I don’t have real hardware with `vlen > 256`, the corresponding accuracy tests were conducted on QEMU built from the `riscv-collab/riscv-gnu-toolchain`.
This patch does not implement optimizations for multi-channel tables.
Previous attempts:
1. For the U8C1 table type, when `vlen = 128`, it is possible to use four `u8m4` vectors to load the entire table, perform gathering, and merge the results. However, the performance is almost the same as the scalar version.
2. Loading part of the table and repeatedly loading the source data is faster for small sizes. But as the table size grows, the performance quickly degrades compared to the scalar version.
3. Using `vluxei8` as a general solution does not show any performance improvement.
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Fix issues in RISC-V Vector (RVV) Universal Intrinsic #27006
This PR aims to make `opencv_test_core` pass on RVV, via following two parts:
1. Fix bug in Universal Intrinsic when VLEN >= 512:
- `max_nlanes` should be multiplied by 2, because we use LMUL=2 in RVV Universal Intrinsic since #26318.
- Related tests are also expanded to match longer registers
- Relax the precision threshold of `v_erf` to make the tests pass
2. Temporary fix #26936
- Disable 3 Universal Intrinsic code blocks on GCC
- This is just a temporary fix until we figure out if it's our issue or GCC/something else's
This patch is tested under the following conditions:
- Compier: GCC 14.2, Clang 19.1.7
- Device: Muse-Pi (VLEN=256), QEMU (VLEN=512, 1024)
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Fix bug with int64 support for FileStorage #26846
### Pull Request Readiness Checklist
Fix#26829, https://github.com/opencv/opencv-python/issues/1078
In current implementation of `int64` support raw size of recorded integer is variable (`4` or `8` bytes depending on value). But then we iterate over nodes we need to know it exact value
https://github.com/opencv/opencv/blob/dfad11aae7ef3b3a0643379266bc363b1a9c3d40/modules/core/src/persistence.cpp#L2596-L2609
Bug is that `rawSize` method still return `4` for any integer. I haven't figured out a way how to get variable raw size for integer in this method. I made raw size for integer is constant and equal to `8`.
Yes, after this patch memory consumption for integers will increase, but I don't know a better way to do it yet. At least this fixes bug and implementation becomes more correct
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int64 data type support for FileStorage. 1d and empty Mat with exact dimensions #26434
### Pull Request Readiness Checklist
Port of https://github.com/opencv/opencv/pull/26399 to 4.x branch
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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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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>
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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core: add v_erf #25872
This patch adds v_erf, which is needed by https://github.com/opencv/opencv/pull/25147.
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Add support for v_log (Natural Logarithm) #25781
This PR aims to implement `v_log(v_float16 x)`, `v_log(v_float32 x)` and `v_log(v_float64 x)`.
Merged after https://github.com/opencv/opencv/pull/24941
TODO:
- [x] double and half float precision
- [x] tests for them
- [x] doc to explain the implementation
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Add support for v_exp (exponential) #24941
This PR aims to implement `v_exp(v_float16 x)`, `v_exp(v_float32 x)` and `v_exp(v_float64 x)`.
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Add missing cv2eigen overload #25751Fixes#16606
Add overloads to cv2eigen to handle eigen matrices of type
Eigen::Matrix<Tp_, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
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Tests added for mixed type arithmetic operations #25671
### Changes
* added accuracy tests for mixed type arithmetic operations
_Note: div-by-zero values are removed from checking since the result is implementation-defined in common case_
* added perf tests for the same cases
* fixed a typo in `getMulExtTab()` function that lead to dead code
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Suppress build warnings for GCC14 #25686Close#25674
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Tests for cv::rotate() added #25633fixes#25449
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Fix v_round and enable unit tests for scalable universal intrinsic 64F type. #25586
This may be a legacy issue from the previous PR #24325. I don't quite remember why the float 64 part of the unit test was not enabled at that time.
Whatever, this patch enables the unit tests for scalable 64F type , and makes the necessary modifications to the RVV backend to make the tests pass.
This patch is compiled by GCC 14 and LLVM 17 &18, and tested on QEMU and k230.
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Transform offset to indeces for MatND in minMaxIdx HAL #25563
Address comments in https://github.com/opencv/opencv/pull/25553
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