Added extra tests for reshape #26254
Attempt to reproduce problems described in #25174. No success; everything works as expected. Probably, the function has been used improperly. Slightly modified the code of Mat::reshape() to provide better diagnostic.
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Fix hfloat conflicts of v_func in merging 4.x to 5.x #26369
This PR solves the conflicts in merging 4.x to 5.x https://github.com/opencv/opencv/pull/26358
1. Explicitly convert the inputs number for `v_setall_` to hfloat number
2. Loosens the threshold for `v_sincos` test. (related issue: https://github.com/opencv/opencv/issues/26362)
3. Remove the new but temp api `template <> inline v_float16x8 v_setall_(float v) { return v_setall_f16((hfloat)v); }`
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Finally dropped convertFp16 function in favor of cv::Mat::convertTo() #26327
Partially address https://github.com/opencv/opencv/issues/24909
Related PR to contrib: https://github.com/opencv/opencv_contrib/pull/3812
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Fix#26322: construction of another Mat header for empty matrix #26333
The PR fixes#26322
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2x more accurate float => bfloat conversion #26321
There is a magic trick to make float => bfloat conversion more accurate (_original reference needed, is it done this way in PyTorch?_). In simplified form it looks like:
```
uint16_t f2bf(float x) {
union {
unsigned u;
float f;
} u;
u.f = x;
// return (uint16_t)(u.u >> 16); <== the old method before this patch
return (uint16_t)((u.u + 0x8000) >> 16);
}
```
it works correctly for almost all valid floating-point values, positive, zero or negative, and even for some extreme cases, like `+/-inf`, `nan` etc. The addition of `0x8000` to integer representation of 32-bit float before retrieving the highest 16 bits reduces the rounding error by ~2x.
The slight problem with this improved method is that the numbers very close to or equal to `+/-FLT_MAX` are mistakenly converted to `+/-inf`, respectively.
This patch implements improved algorithm for `float => bfloat` conversion in scalar and vector form; it fixes the above-mentioned problem using some extra bit magic, i.e. 0x8000 is not added to very big (by absolute value) numbers:
```
// the actual implementation is more efficient,
// without conditions or floating-point operations, see the source code
return (uint16_t)(u.u + (fabsf(x) <= big_threshold ? 0x8000 : 0)) >> 16);
```
The corresponding test has been added as well and this is output from the test:
```
[----------] 1 test from Core_BFloat
[ RUN ] Core_BFloat.convert
maxerr0 = 0.00774842, mean0 = 0.00190643, stddev0 = 0.00186063
maxerr1 = 0.00389057, mean1 = 0.000952614, stddev1 = 0.000931268
[ OK ] Core_BFloat.convert (7 ms)
```
Here `maxerr0, mean0, stddev0` are for the original method and `maxerr1, mean1, stddev1` are for the new method. As you can see, there is a significant improvement in accuracy.
**Note:**
_Actually, on ~32,000,000 random FP32 numbers with uniformly distributed sign, exponent and mantissa the new method is always at least as accurate as the old one._
The test also checks all the corner cases, where we see no degradation either vs the original method.
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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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extended Norm tests to prove that cv::norm() already supports all the types.
cv::norm() already provides enough functionality; just extended tests to prove it. See #24887
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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>
C-API cleanup: moved cvErrorStr to new interface, minor ts changes #26101
Merge with opencv/opencv_contrib#3786
**Note:** `toString` might be too generic name (even though it is in `cv::Error::` namespace), another variant is `codeToString` (we have `typeToString` and `depthToString` in check.hpp).
**Note:** _ts_ module seem to have no other C API usage except for `ArrayTest` class which requires refactoring.
Fix hfloat, float16_t, float collision in 5.x about v_exp and v_log #26023
This PR try to fix https://github.com/opencv/opencv/issues/25922
Because the `hfloat` is defined as explicit conversion, the test code should be modified as it. The `vx_setall_f16` problem has already been fixed.
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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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Fix size() for 0d matrix #25945
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Mask support with CV_Bool in ts and core #25902
Partially cover https://github.com/opencv/opencv/issues/25895
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Use hfloat instead of __fp16. #25796
Related: #25743
Currently, the type for the half-precision floating point data in the OpenCV source code is `__fp16`, which is a unique(?) type supported by the ARM compiler. Other compilers have very limited support for `__fp16`, so in order to introduce more backends that support FP16 (such as RISC-V), we may need a the more general FP16 type.
In this patch, we use `hfloat` instead of `__fp16` in non-ARM code blocks, mainly affected parts are:
- `core/hal/intrin.hpp`: Type Traits, REG Traits and `vx_` interface.
- `core/hal/intrin_neon.hpp`: Universal Intrinsic API for FP16 type.
- `core/test/test_intrin_utils.hpp`: Usage of Univseral Intrinsic
- `core/include/opencv2/core/cvdef.h`: Definition of class `hfloat`
If I understand correctly, class `hfloat` acts as a wrapper around FP16 types in different platform (`__fp16` for ARM and `_Float16` for RISC-V). Any OpenCV generic interface/source code should use `hfloat`, while platform-specific FP16 types only used in macro-guarded code blocks.
/cc @fengyuentau @mshabunin
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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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core: add universal intrinsics for fp16 #25196
Partially resolves the section "Universal intrinsics evolution in OpenCV 5.0" in https://github.com/opencv/opencv/issues/25019.
Universal intrinsics for bf16 will be added in a subsequent pull request.
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