imgproc: optimized nearest neighbour interpolation for warpAffine, warpPerspective and remap #26505
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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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HAL added for add(array, scalar) #25624
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Fix empty mat debug assertion #26444
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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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int64 data type in FileStorage #26399
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resolves#23333
Proposed approach is not perfect in terms of complexity and potential bugs. Instead of changing `INT` raw size from `4` to `8`, we check int64 value can be fitted to int32 or not.
Collections such as cv::Mat rely on data type symbol.
This PR is addressed to 5.x branch first to cover `CV_64S` Mat. Later, it can be backported to 4.x
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Support 0d/1d Mat in FileStorage #26420
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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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doc: fix doxygen errors at Algorithm and QRCodeEncoder #26373
Close https://github.com/opencv/opencv/issues/26372
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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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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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