Fix bug with predictions in RTrees/Boost
* address bug where predict functions with invalid feature count in rtrees/boost models
* compact matrix rep in tests
* check 1..n-1 and n+1 in feature size validation test
Fix KD Tree kNN Implementation
* Make KDTree mode in kNN functional
remove docs and revert change
Make KDTree mode in kNN functional
spacing
Make KDTree mode in kNN functional
fix window compilations warnings
Make KDTree mode in kNN functional
fix window compilations warnings
Make KDTree mode in kNN functional
casting
Make KDTree mode in kNN functional
formatting
Make KDTree mode in kNN functional
* test coding style
Objc binding
* Initial work on Objective-C wrapper
* Objective-C generator script; update manually generated wrappers
* Add Mat tests
* Core Tests
* Imgproc wrapper generation and tests
* Fixes for Imgcodecs wrapper
* Miscellaneous fixes. Swift build support
* Objective-C wrapper build/install
* Add Swift wrappers for videoio/objdetect/feature2d
* Framework build;iOS support
* Fix toArray functions;Use enum types whenever possible
* Use enum types where possible;prepare test build
* Update test
* Add test runner scripts for iOS and macOS
* Add test scripts and samples
* Build fixes
* Fix build (cmake 3.17.x compatibility)
* Fix warnings
* Fix enum name conflicting handling
* Add support for document generation with Jazzy
* Swift/Native fast accessor functions
* Add Objective-C wrapper for calib3d, dnn, ml, photo and video modules
* Remove IntOut/FloatOut/DoubleOut classes
* Fix iOS default test platform value
* Fix samples
* Revert default framework name to opencv2
* Add converter util functions
* Fix failing test
* Fix whitespace
* Add handling for deprecated methods;fix warnings;define __OPENCV_BUILD
* Suppress cmake warnings
* Reduce severity of "jazzy not found" log message
* Fix incorrect #include of compatibility header in ios.h
* Use explicit returns in subscript/get implementation
* Reduce minimum required cmake version to 3.15 for Objective-C/Swift binding
SVM sigmoid kernel fix (issue #13621) (#13718)
* Added test for sigmoid case for retrieving support vectors
* undo unhelpful test
* add test for sigmoid SVM with data that is easily separable into two concentric circles
* Update sigmoid kernel to use tanh(gamma * <x, y> + coef0) instead of -tanh(gamma * <x, y> + coef0)
* remove unnecessary constraint on coef0
* cleanup
* fixing inappropriate use of doubles
* Add f to float literal
* replace CV_Assert with ASSERT_EQ where appropriate
* integrated the new C++ persistence; removed old persistence; most of OpenCV compiles fine! the tests have not been run yet
* fixed multiple bugs in the new C++ persistence
* fixed raw size of the parsed empty sequences
* [temporarily] excluded obsolete applications traincascade and createsamples from build
* fixed several compiler warnings and multiple test failures
* undo changes in cocoa window rendering (that was fixed in another PR)
* fixed more compile warnings and the remaining test failures (hopefully)
* trying to fix the last little warning
* Add HPX backend for OpenCV implementation
Adds hpx backend for cv::parallel_for_() calls respecting the nstripes chunking parameter. C++ code for the backend is added to modules/core/parallel.cpp. Also, the necessary changes to cmake files are introduced.
Backend can operate in 2 versions (selectable by cmake build option WITH_HPX_STARTSTOP): hpx (runtime always on) and hpx_startstop (start and stop the backend for each cv::parallel_for_() call)
* WIP: Conditionally include hpx_main.hpp to tests in core module
Header hpx_main.hpp is included to both core/perf/perf_main.cpp and core/test/test_main.cpp.
The changes to cmake files for linking hpx library to above mentioned test executalbles are proposed but have issues.
* Add coditional iclusion of hpx_main.hpp to cpp cpu modules
* Remove start/stop version of hpx backend
In case of regression trees, node risk is computed as sum of squared
error. To get a meaningfull value to compare with it needs to be
normalized to the number of samples in the node (or more generally to
the sum of sample weights in this node). Otherwise the sum of squared
error is highly dependend on the number of samples in the node and
comparision with `regressionAccuracy` parameter is not very meaningful.
After normalization `node_risk` means in fact sample variance for all
samples in the node, which makes much more sence and seams to be what
was originaly intended by the code given that node risk is later used as
a split termination criteria by
```
sqrt(node.node_risk) < params.getRegressionAccuracy()
```
- removed tr1 usage (dropped in C++17)
- moved includes of vector/map/iostream/limits into ts.hpp
- require opencv_test + anonymous namespace (added compile check)
- fixed norm() usage (must be from cvtest::norm for checks) and other conflict functions
- added missing license headers