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.
- [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
- [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.
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Fix#26322: construction of another Mat header for empty matrix #26333
The PR fixes#26322
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- [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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- [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.
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New dnn engine #26056
This is the 1st PR with the new engine; CI is green and PR is ready to be merged, I think.
Merge together with https://github.com/opencv/opencv_contrib/pull/3794
---
**Known limitations:**
* [solved] OpenVINO is temporarily disabled, but is probably easy to restore (it's not a deal breaker to merge this PR, I guess)
* The new engine does not support any backends nor any targets except for the default CPU implementation. But it's possible to choose the old engine when loading a model, then all the functionality is available.
* [Caffe patch is here: #26208] The new engine only supports ONNX. When a model is constructed manually or is loaded from a file of different format (.tf, .tflite, .caffe, .darknet), the old engine is used.
* Even in the case of ONNX some layers are not supported by the new engine, such as all quantized layers (including DequantizeLinear, QuantizeLinear, QLinearConv etc.), LSTM, GRU, .... It's planned, of course, to have full support for ONNX by OpenCV 5.0 gold release. When a loaded model contains unsupported layers, we switch to the old engine automatically (at ONNX parsing time, not at `forward()` time).
* Some layers , e.g. Expat, are only partially supported by the new engine. In the case of unsupported flavours it switches to the old engine automatically (at ONNX parsing time, not at `forward()` time).
* 'Concat' graph optimization is disabled. The optimization eliminates Concat layer and instead makes the layers that generate tensors to be concatenated to write the outputs to the final destination. Of course, it's only possible when `axis=0` or `axis=N=1`. The optimization is not compatible with dynamic shapes since we need to know in advance where to store the tensors. Because some of the layer implementations have been modified to become more compatible with the new engine, the feature appears to be broken even when the old engine is used.
* Some `dnn::Net` API is not available with the new engine. Also, shape inference may return false if some of the output or intermediate tensors' shapes cannot be inferred without running the model. Probably this can be fixed by a dummy run of the model with zero inputs.
* Some overloads of `dnn::Net::getFLOPs()` and `dnn::Net::getMemoryConsumption()` are not exposed any longer in wrapper generators; but the most useful overloads are exposed (and checked by Java tests).
* [in progress] A few Einsum tests related to empty shapes have been disabled due to crashes in the tests and in Einsum implementations. The code and the tests need to be repaired.
* OpenCL implementation of Deconvolution is disabled. It's very bad and very slow anyway; need to be completely revised.
* Deconvolution3D test is now skipped, because it was only supported by CUDA and OpenVINO backends, both of which are not supported by the new engine.
* Some tests, such as FastNeuralStyle, checked that the in the case of CUDA backend there is no fallback to CPU. Currently all layers in the new engine are processed on CPU, so there are many fallbacks. The checks, therefore, have been temporarily disabled.
---
- [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
Mark cv::Mat(Mat&&) as noexcept #25899
This fixes https://github.com/opencv/opencv/issues/25065
### 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
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
C-API cleanup: apps, imgproc_c and some constants #25075
Merge with https://github.com/opencv/opencv_contrib/pull/3642
* Removed obsolete apps - traincascade and createsamples (please use older OpenCV versions if you need them). These apps relied heavily on C-API
* removed all mentions of imgproc C-API headers (imgproc_c.h, types_c.h) - they were empty, included core C-API headers
* replaced usage of several C constants with C++ ones (error codes, norm modes, RNG modes, PCA modes, ...) - most part of this PR (split into two parts - all modules and calib+3d - for easier backporting)
* removed imgproc C-API headers (as separate commit, so that other changes could be backported to 4.x)
Most of these changes can be backported to 4.x.
* attempt to add 0d/1d mat support to OpenCV
* revised the patch; now 1D mat is treated as 1xN 2D mat rather than Nx1.
* a step towards 'green' tests
* another little step towards 'green' tests
* calib test failures seem to be fixed now
* more fixes _core & _dnn
* another step towards green ci; even 0D mat's (a.k.a. scalars) are now partly supported!
* * fixed strange bug in aruco/charuco detector, not sure why it did not work
* also fixed a few remaining failures (hopefully) in dnn & core
* disabled failing GAPI tests - too complex to dig into this compiler pipeline
* hopefully fixed java tests
* trying to fix some more tests
* quick followup fix
* continue to fix test failures and warnings
* quick followup fix
* trying to fix some more tests
* partly fixed support for 0D/scalar UMat's
* use updated parseReduce() from upstream
* trying to fix the remaining test failures
* fixed [ch]aruco tests in Python
* still trying to fix tests
* revert "fix" in dnn's CUDA tensor
* trying to fix dnn+CUDA test failures
* fixed 1D umat creation
* hopefully fixed remaining cuda test failures
* removed training whitespaces
Fix undefined behavior arithmetic in copyMakeBorder and adjustROI. #24260
This is due to the undefined: negative int multiplied by size_t pointer increment.
To test, compile with:
```
mkdir build
cd build
cmake ../ -DCMAKE_C_FLAGS_INIT="-fsanitize=undefined" -DCMAKE_CXX_FLAGS_INIT="-fsanitize=undefined" -DCMAKE_C_COMPILER="/usr/bin/clang" -DCMAKE_CXX_COMPILER="/usr/bin/clang++" -DCMAKE_SHARED_LINKER_FLAGS="-fsanitize=undefined -lubsan"
```
And run:
```
make -j opencv_test_core && ./bin/opencv_test_core --gtest_filter=*UndefinedBehavior*
```
### 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
- [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
* started working on adding 32u, 64u, 64s, bool and 16bf types to OpenCV
* core & imgproc tests seem to pass
* fixed a few compile errors and test failures on macOS x86
* hopefully fixed some compile problems and test failures
* fixed some more warnings and test failures
* trying to fix small deviations in perf_core & perf_imgproc by revering randf_64f to exact version used before
* trying to fix behavior of the new OpenCV with old plugins; there is (quite strong) assumption that video capture would give us frames with depth == CV_8U (0) or CV_16U (2). If depth is > 7 then it means that the plugin is built with the old OpenCV. It needs to be recompiled, of course and then this hack can be removed.
* try to repair the case when target arch does not have FP64 SIMD
* 1. fixed bug in itoa() found by alalek
2. restored ==, !=, > and < univ. intrinsics on ARM32/ARM64.
Thread Sanitizer identified an incorrect implementation of double checked locking.
Replaced it with a static, which therefore can only be created once.
Changed the type of variable *r* from int to size_t.
This change makes sure that a valid result of std::max(r + delta,
(r*3+1)/2) can be passed into the reserve function.
* make sure that the matrix with more than INT_MAX elements is marked as non-continuous, and thus all the pixel-wise functions process it correctly (i.e. row-by-row, not as a single row, where integer overflow may occur when computing the total number of elements)
The same code was repeated several time for different data types, so
it was extracted as a templated function to improve maintability and
make a code more clear.
Exception may be rasied inside the body of a copying constructor after
refcount has been increased, and beacause in the case of the exception
destrcutor is never called what causes memory leak. This commit adds a
workaround that calls the release() function before the exception is
thrown outside the contructor.