Added in-place support for cartToPolar and polarToCart #24893
- a fused hal::cartToPolar[32|64]f() is used instead of sequential hal::magnitude[32|64]f/hal::fastAtan[32|64]f
- ipp_polarToCart is skipped for in-place processing (it seems not to support it correctly)
relates to #24891
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dnn: avoid const layer forwarding in layer norm layer and attention layer #25238
While profiling ViTs with dnn, I found `ConstLayer` can take a proportion of the inference time, which is weird. This comes from the data copy during the inference of `ConstLayer`. There is a chance that we can improve the efficiency of data copying but the easiest and most convenient way is to avoid `ConstLayer`. This PR change the way how we handle constants in layer normalization layer and attention layer, which is storing in the layer blobs instead of making constant layers for them.
Checklists:
- [x] Backend compatibility in layer normalization layer.
### Pull Request Readiness Checklist
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doc: add note on handling of spaces in CommandLineParser #25237
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Added note that this class will not work properly if tabs and other whitespace characters are included in the key.
The support of whitespace characters by istringstream, etc. is on hold because the future of this class is not clear compared to implementations in Python and other languages.
Added and tested yolov8s and yolov8n model #25176
### Pull Request Readiness Checklist
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- [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
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Below is evidence of the test:
dnn (CANN): Fix incorrect shape of 1d bias in Gemm #25166
Gemm layer was refactored some time ago. Users found that the mobilenet example in https://github.com/opencv/opencv/wiki/Huawei-CANN-Backend does not work because of incorrect shape set for 1d bias in Gemm. This PR resolves this issue.
### Pull Request Readiness Checklist
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- [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
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Patch to opencv_extra has the same branch name.
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Release convolution weightsMat after usage #25181
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related (but not resolved): https://github.com/opencv/opencv/issues/24134
Minor memory footprint improvement. Also, adds a test for VmHWM.
RAM top memory usage (-230MB)
| YOLOv3 (237MB file) | 4.x | PR |
|---------------------|---------|---------|
| no winograd | 808 MB | 581 MB |
| winograd | 1985 MB | 1750 MB |
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.
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- [x] The PR is proposed to the proper branch
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Patch to opencv_extra has the same branch name.
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3rdparty: libtiff: fix for small version expression problems for built-in tiff460 #25257Close#25256
1. fix to show build-int libtiff version
2. fix to set value of LIBTIFF_VERSION define.
(RELEASE-DATE file coms from original libtiff 4.6.0)
### Pull Request Readiness Checklist
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- [x] I agree to contribute to the project under Apache 2 License.
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Normaly, we sets IMWRITE_* flags for imwrite() params.
But imgcodecs expects to use some TIFFTAG_* directory.
This patch introduce IMWRITE_TIFF_ROWSPERSTRIP and
IMWRITE_TIFF_PREDICTOR instead of TIFFTAG_*.
* libtiff upgrade to version 4.6.0
* fix tiffvers.h cmake generation
* temp: force build 3rd party deps from source
* remove libport.h and spintf.c
* cmake fixes
* don't use tiff_dummy_namespace on windows
* introduce numeric_types namespace alias
* include cstdint
* uint16_t is not a numeric_types type
* fix uint16 and uint32 type defs
* use standard c++ types
* remove unused files
* remove more unused files
* revert build 3rd party code from source
---------
Co-authored-by: Misha Klatis <misha.klatis@autodesk.com>
G-API: A quick value-initialization support GMat #25055
This PR enables `GMat` objects to be value-initialized in the same way as it was done for `GScalar`s (and, possibly, other types).
- Added some helper methods in backends to distinguish if a certain G-type value initialization is supported or not;
- Added tests, including negative.
Where it is needed:
- Further extension of the OVCV backend (#24379 - will be refreshed soon);
- Further experiments with DNN module;
- Further experiments with "G-API behind UMat" sort of aggregation.
In the current form, PR can be reviewed & merged (@TolyaTalamanov please have a look)
### Pull Request Readiness Checklist
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Patch to opencv_extra has the same branch name.
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calib3d: doc: remove C API link (For 4.x) #25141
Related to #25140 (for 4.x)
### Pull Request Readiness Checklist
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- [x] The PR is proposed to the proper branch
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Documentation transition to fresh Doxygen #25042
* current Doxygen version is 1.10, but we will use 1.9.8 for now due to issue with snippets (https://github.com/doxygen/doxygen/pull/10584)
* Doxyfile adapted to new version
* MathJax updated to 3.x
* `@relates` instructions removed temporarily due to issue in Doxygen (to avoid warnings)
* refactored matx.hpp - extracted matx.inl.hpp
* opencv_contrib - https://github.com/opencv/opencv_contrib/pull/3638
