imgcodecs(webp): improve IMWRITE_WEBP_LOSSLESS_MODE to support exact lossless compression #28519Close#28503
Add IMWRITE_WEBP_LOSSLESS_MODE enum to control lossless strategy:
- IMWRITE_WEBP_LOSSLESS_OFF: Lossy compression.
- IMWRITE_WEBP_LOSSLESS_ON: Optimize/drop color in transparent pixels.
- IMWRITE_WEBP_LOSSLESS_PRESERVE_COLOR: Preserve color in transparent pixels.
Note: Currently limited to still images; animated WebP support is deferred per YAGNI.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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Fix IPP warpAffine #28562
The issue is that we compute the inverse transformation and pass that to the HAL, but tell IPP that we use the actual transformation.
https://github.com/opencv/opencv/blob/a269a489b94b84717691533a04f79d9a0e5f479a/modules/imgproc/src/imgwarp.cpp#L2399-L2412
I have added an additional test with `CV_16S` Mats to test the IPP implementation, because right now no other `warpAffine` test enters the IPP branch.
This fixes#28554.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
This commit addresses a compiler warning encountered when building with GCC 13 and C++20.
The compiler triggers a false-positive -Wstringop-overflow warning in `findKSides`.
By adding `sides.reserve(k)`, we explicitly inform the compiler about the required
memory allocation, which suppresses the warning and provides a minor optimization
by avoiding potential reallocations.
DNN: Fix Squeeze to remove all size-1 dims when axes is empty #28425Fixes#28424
OpenCV Extra: [opencv/opencv_extra#1308](https://github.com/opencv/opencv_extra/pull/1308)
This PR fixes the ONNX Squeeze operator to correctly remove all size-1 dimensions when `axes` is not provided, conforming to the ONNX specification.
### Details
Per [ONNX Squeeze specification](https://onnx.ai/onnx/operators/onnx__Squeeze.html):
> 'If axes is not provided, all the single dimensions will be removed from the shape.'
Previously, OpenCV DNN would not remove any dimensions in this case, causing shape mismatch errors with models like LaMa (inpainting).
### Example
```python
# Input: [1, 1, 2, 4]
# Squeeze with no axes attribute
# Before: [1, 1, 2, 4] ✗ (No change)
# After: [2, 4] ✓ (matches ONNX Runtime)
```
### Tests
Added `testONNXModels("squeeze_no_axes")` which validates this behavior with new test data.
opencv_extra_pr=opencv/opencv_extra#1324
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch (4.x for bug fixes)
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
- Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
docs(calib3d): clarify coordinate systems in projectPoints, undistort Points, and fisheye::undistortPoints #28333
This PR improves documentation clarity by explicitly describing:
- Input/output coordinate systems (pixel vs normalized coordinates)
- When to use normalized vs pixel coordinates in undistortPoints output
- Differences between fisheye and standard pinhole camera models
- Coordinate system transformations for better understanding
Changes:
- projectPoints: Added explicit note about input (world coords) and output (pixel coords)
- undistortPoints: Clarified that input is pixel coordinates, and output depends on parameter P (normalized vs pixel)
- fisheye::undistortPoints: Added comprehensive documentation including coordinate systems, when to use fisheye vs standard model, and distortion coefficient differences
These improvements help users avoid ambiguity when using these functions for camera calibration and 3D vision pipelines.
features2d: add missing KAZE DIFF_CHARBONNIER support #28324
### Description
This PR fixes the missing implementation for `DIFF_CHARBONNIER` diffusivity type in KAZE feature detector.
### Changes
- Added `charbonnier_diffusivity()` call for `DIFF_CHARBONNIER` type in `Create_Nonlinear_Scale_Space()`
- Added proper error handling for unsupported diffusivity types
### Problem
When using KAZE with `DIFF_CHARBONNIER` diffusivity type, keypoint coordinates were not computed at subpixel level, because the code lacked the specific handling for this diffusivity mode.
### Solution
The `charbonnier_diffusivity()` function already exists in `nldiffusion_functions.cpp`, it just wasn't being called. This PR adds the missing `else if` branch to call it, matching the pattern already implemented in `AKAZEFeatures.cpp`.
Fixes#27134
### Pull Request Readiness Checklist
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another copyleft license.
- [x] The PR is proposed to the proper branch.
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
- [ ] The feature is well documented and sample code can be built with the project CMake
optimize(dnn): parallelize Slice layer implementation (4.x) #28511
### Summary
Backport of PR #28447 to 4.x branch.
### Description
This PR optimizes the SliceLayer implementation for strided inputs (where step > 1). The original implementation used a recursive element-wise copy (getSliceRecursive) for any strided slice, which was extremely inefficient.
This PR introduces:
- **Parallelization**: Uses `cv::parallel_for_` to parallelize the outermost dimension of the slice operation.
- **Memcpy Optimization**: Automatically detects "pseudo-contiguous" blocks in strided slices (e.g., slicing an outer dimension but keeping inner dimensions intact) and uses `std::memcpy` instead of scalar loops.
- **Refactoring**: Replaces the recursive function with a dedicated `ParallelSlice` loop body.
### Impact
Significant performance improvement for strided slice operations (common in detection heads, strided sampling, etc.).
### Benchmark Results
Tested on CPU with 20 threads.
| Test Case | Baseline (ms) | Optimized (ms) | Speedup |
| :--- | :--- | :--- | :--- |
| Strided Axis 0 [::2, ...] | 1.10 | 0.02 | **~55x** |
| Strided Axis 2 [..., ::2] | 1.15 | 0.11 | **~10.5x** |
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
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- Change 'element' to 'kernel' in LaTeX formulas to match actual parameter name
- Fix erode() and dilate() function documentation (lines 2330, 2338, 2362, 2370)
- Fix MorphTypes enum documentation (MORPH_OPEN, MORPH_CLOSE, MORPH_GRADIENT, MORPH_TOPHAT, MORPH_BLACKHAT)
- Fix backtick formatting in dilate() documentation
Resolves#18095
dnn: improve robustness of MVN layer#28308
This change adds small defensive improvements to the MVN layer implementation:
->Guard against zero-sized OpenCL kernel launches
->Add input validation in finalize()
->Use int64 for FLOPS computation to avoid overflow
No functional or performance changes are intended.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
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imgcodecs: fix integer overflow in BMP and SunRaster decoders #28379
### Pull Request Readiness Checklist
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Fixes#28350
### Description
This PR fixes integer overflow vulnerabilities in BMP and SunRaster image decoders that could cause heap buffer over-read when decoding malformed images.
### Root Cause
The `src_pitch` and `width3` calculations in `BmpDecoder::readData()` and `SunRasterDecoder::readData()` used `int` arithmetic:
```cpp
int src_pitch = ((m_width * m_bpp + 7) / 8 + 3) & -4;
int width3 = m_width * nch;
```
When `m_width` or `m_bpp` are large values from a crafted malicious file, the multiplication overflows, resulting in a small or negative value. This leads to insufficient buffer allocation, causing heap buffer over-read during subsequent decoding operations.
### Fix
1. **Use `size_t` arithmetic**: Cast operands to `size_t` before multiplication:
```cpp
const size_t bits_per_row = static_cast<size_t>(m_width) * static_cast<size_t>(m_bpp);
const size_t src_pitch_size = ((bits_per_row + 7) / 8 + 3) & ~static_cast<size_t>(3);
```
2. **Add size validation**: Added `CV_CheckLT` to reject images requiring buffers larger than 256MB:
```cpp
const size_t MAX_SRC_PITCH = static_cast<size_t>(1) << 28;
CV_CheckLT(src_pitch_size, MAX_SRC_PITCH, "BMP: src_pitch exceeds maximum allowed size");
```
3. **Safe conversion**: Use `validateToInt()` for safe conversion back to `int`.
### Files Changed
- `modules/imgcodecs/src/grfmt_bmp.cpp` - BmpDecoder::readData()
- `modules/imgcodecs/src/grfmt_sunras.cpp` - SunRasterDecoder::readData()
### Testing
- Code compiles without warnings
- Basic BMP and SunRaster encode/decode tests pass
- Overflow conditions are now properly rejected with CV_CheckLT
hal/riscv-rvv: Fix test failures on hardware that implements tail-agnostic as all 1s #28375
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
### Summary
Fix test failures in `opencv_test_core` and `opencv_test_imgproc` on hardware that implements the tail-agnostic policy by overwriting tail elements with all 1s
### Root Cause
According to the [RISC-V Vector Extension Specification v1.0](https://github.com/riscvarchive/riscv-v-spec/blob/master/v-spec.adoc#343-vector-tail-agnostic-and-vector-mask-agnostic-vta-and-vma):
> "When a set is marked agnostic, the corresponding set of destination elements in any vector destination operand can either retain the value they previously held, or are overwritten with 1s."
Both `dotProd_32f` and `dotProd_32s` functions use accumulator variables(`s`) that persist across loop iterations, but were using vector intrinsics with tail-agnostic policy. The tail elements can be overwritten with 1s, corrupting the accumulator and producing NaN during the final reduction sum.
### Solution
Changed both functions to use `tail-undisturbed`(`tu`) policy to ensure tail elements remain unchanged across loop iterations.
### Reproduce Steps
The failures can be reproduced using [QEMU](https://gitlab.com/qemu-project/qemu) with `rvv_ma_all_1s=true` and `rvv_ta_all_1s=true` options to emulate hardware implementing tail-agnostic policy as all 1s.
#### Reproduce **`opencv_test_core`** failures:
```
qemu-riscv64 -cpu rv64,zba=true,zbb=true,zbc=true,zbs=true,v=true,vlen=512,elen=64,vext_spec=v1.0,rvv_ma_all_1s=true,rvv_ta_all_1s=true -L '/PATH_TO_SYSROOT/sysroot/' ./opencv_test_core --gtest_filter="Core_DotProduct*"
```
Before the patch:
```
[ FAILED ] Core_DotProduct.accuracy (24 ms)
```
After the patch:
```
[ PASSED ] 1 test.
```
#### Reproduce **`opencv_test_imgproc`** failures:
```
qemu-riscv64 -cpu rv64,zba=true,zbb=true,zbc=true,zbs=true,v=true,vlen=512,elen=64,vext_spec=v1.0,rvv_ma_all_1s=true,rvv_ta_all_1s=true -L '/workspace/riscv/sysroot/' ./opencv_test_imgproc --gtest_filter="fitLine_Modes.accuracy/*"
```
Before the patch
```
[ FAILED ] 24 tests, listed below:
[ FAILED ] fitLine_Modes.accuracy/0, where GetParam() = (13, 1)
[ FAILED ] fitLine_Modes.accuracy/1, where GetParam() = (13, 2)
[ FAILED ] fitLine_Modes.accuracy/2, where GetParam() = (13, 4)
[ FAILED ] fitLine_Modes.accuracy/3, where GetParam() = (13, 5)
[ FAILED ] fitLine_Modes.accuracy/4, where GetParam() = (13, 6)
[ FAILED ] fitLine_Modes.accuracy/5, where GetParam() = (13, 7)
[ FAILED ] fitLine_Modes.accuracy/6, where GetParam() = (21, 1)
[ FAILED ] fitLine_Modes.accuracy/7, where GetParam() = (21, 2)
[ FAILED ] fitLine_Modes.accuracy/8, where GetParam() = (21, 4)
[ FAILED ] fitLine_Modes.accuracy/9, where GetParam() = (21, 5)
[ FAILED ] fitLine_Modes.accuracy/10, where GetParam() = (21, 6)
[ FAILED ] fitLine_Modes.accuracy/11, where GetParam() = (21, 7)
[ FAILED ] fitLine_Modes.accuracy/12, where GetParam() = (12, 1)
[ FAILED ] fitLine_Modes.accuracy/13, where GetParam() = (12, 2)
[ FAILED ] fitLine_Modes.accuracy/14, where GetParam() = (12, 4)
[ FAILED ] fitLine_Modes.accuracy/15, where GetParam() = (12, 5)
[ FAILED ] fitLine_Modes.accuracy/16, where GetParam() = (12, 6)
[ FAILED ] fitLine_Modes.accuracy/17, where GetParam() = (12, 7)
[ FAILED ] fitLine_Modes.accuracy/18, where GetParam() = (20, 1)
[ FAILED ] fitLine_Modes.accuracy/19, where GetParam() = (20, 2)
[ FAILED ] fitLine_Modes.accuracy/20, where GetParam() = (20, 4)
[ FAILED ] fitLine_Modes.accuracy/21, where GetParam() = (20, 5)
[ FAILED ] fitLine_Modes.accuracy/22, where GetParam() = (20, 6)
[ FAILED ] fitLine_Modes.accuracy/23, where GetParam() = (20, 7)
```
After the patch
`[ PASSED ] 24 tests.`
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