Add RISC-V HAL implementation for cv::norm and cv::normalize #26804
This patch implements `cv::norm` with norm types `NORM_INF/NORM_L1/NORM_L2/NORM_L2SQR` and `Mat::convertTo` function in RVV_HAL using native intrinsic, optimizing the performance for `cv::norm(src)`, `cv::norm(src1, src2)`, and `cv::normalize(src)` with data types `8UC1/8UC4/32FC1`.
`cv::normalize` also calls `minMaxIdx`, #26789 implements RVV_HAL for this.
Tested on MUSE-PI for both gcc 14.2 and clang 20.0.
```
$ opencv_test_core --gtest_filter="*Norm*"
$ opencv_perf_core --gtest_filter="*norm*" --perf_min_samples=300 --perf_force_samples=300
```
The head of the perf table is shown below since the table is too long.
View the full perf table here: [hal_rvv_norm.pdf](https://github.com/user-attachments/files/18468255/hal_rvv_norm.pdf)
<img width="1304" alt="Untitled" src="https://github.com/user-attachments/assets/3550b671-6d96-4db3-8b5b-d4cb241da650" />
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imgcodecs:gif: support IMREAD_UNCHANGED and IMREAD_GRAYSCALE #26859Close#26858
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Add missing include in gislandmodel.hpp #26879
Add `<exception>`, `<string>`, and `<cstddef>` includes to `gislandmodel.hpp` which are required due to the usage of `std::exception_ptr`, `std::string`, and `size_t` in this header.
Notably one of those causes a build error on recent versions of Xcode: #26780
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Performance tests for image encoders and decoders and code cleanup #26872
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Add RISC-V HAL implementation for minMaxIdx #26789
On the RISC-V platform, `minMaxIdx` cannot benefit from Universal Intrinsics because the UI-optimized `minMaxIdx` only supports `CV_SIMD128` (and does not accept `CV_SIMD_SCALABLE` for RVV).
https://github.com/opencv/opencv/blob/1d701d1690b8cc9aa6b86744bffd5d9841ac6fd3/modules/core/src/minmax.cpp#L209-L214
This patch implements `minMaxIdx` function in RVV_HAL using native intrinsic, optimizing the performance for all data types with one channel.
Tested on MUSE-PI for both gcc 14.2 and clang 20.0.
```
$ opencv_test_core --gtest_filter="*MinMaxLoc*"
$ opencv_perf_core --gtest_filter="*minMaxLoc*"
```
<img width="1122" alt="Untitled" src="https://github.com/user-attachments/assets/6a246852-87af-42c5-a50b-c349c2765f3f" />
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Fix oss-fuzz bugs 391934081 and 392318892 #26854
- fix a potential overflow in x0+w0
- use the proper function to deal with background color to deal with all cases of the spec
- use BGR layout for APNG background color
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Added 16-bit support to fastNlMeansDenoising and updated tests #26831
Fixes : #26582
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Fix bug with int64 support for FileStorage #26846
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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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Update includes in filter.hpp #26850
Fixes :
```
identifier "Mat" is undefinedC/C++(20)
namespace "std" has no member "vector"C/C++(135)
```
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imgcodecs: jpegxl: imdecode() directly read from memory #26844Close#26843
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`step` and `maskStep` are used to increase/decrease `pImage`.
But it's done on unsigned type, relying on overflow, which is UB.
(step is size_t but seed.y is int and can be negative, the result
is therefore unsigned which can overflow)
Add direct pdf links in the bibliography #26754
Update and add pdf links in the bibliography.
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Corrections on bKGD chunk writing and reading in PNG #26835
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Zoom functionality for Android native camera capture #26837
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solvePnPRansac implementation for Fisheye camera model #26669
Related: https://github.com/opencv/opencv/pull/25028
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Add cv::THRESH_DRYRUN flag to get adaptive threshold values without thresholding #26836
A first proposal for #26777
Adds a `cv::THRESH_DRYRUN` flag to let cv::threshold() compute the threshold (useful for OTSU/TRIANGLE), but without actually running the thresholding. This flags is a proposal instead of a new function cv::computeThreshold()
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Android camera refactoring #26646
This patch set does not contain any functional changes. It just cleans up the code structure to improve readability and to prepare for future changes.
* videoio(Android): Use 'unique_ptr' instead of 'shared_ptr'
Using shared pointers for unshared data is considered an antipattern.
* videoio(Android): Make callback functions private static members
Don't leak internal functions into global namespace. Some member
variables are now private as well.
* videoio(Android): Move resolution matching into separate function
Also make internally used member functions private.
* videoio(Android): Move ranges query into separate function
Also remove some unneccessary initialisations from initCapture().
* videoio(Android): Wrap extremly long source code lines
* videoio(Android): Rename members of 'RangeValue'
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Fix potential READ memory access #26782
This fixes https://oss-fuzz.com/testcase-detail/4923671881252864 and https://oss-fuzz.com/testcase-detail/5048650127966208
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Fixed default cap_prop_orientation_auto behaviour #26800
Fixes : #26795
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Improve robustness for fitEllipseAMS #26810
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Related to #26694
Added functionality to add noise to points in degenerate cases and try again for `fitEllipseAMS`. `fitEllipseNoDirect` and `fitEllipseDirect` already have this
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jpegxl: support cv::IMREAD_UNCHANGED and other ImreadFlags #26788
Close https://github.com/opencv/opencv/issues/26767
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Added CV_WRAP to Animation struct #26813closes#26808
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Improve robustness for ellipse fitting #26773
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Related to #26694
Current noise addition is not very good because for example it turns degenerate case of one horizontal line into degenerate case of two parallel horizontal lines
Improving noise addition leads to improved robustness of algorithms
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shyama7004
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Alexander Smorkalov
Vincent Rabaud
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