Pev binary kmeans
* Ongoing work transposing kmeans clustering method for bitfields: the computeClustering method
Ongoing work transposing kmeans clustering method for bitfields: interface computeBitfieldClustering
Fix genericity of computeNodeStatistics
Ongoing work transposing kmeans clustering method for bitfields: adapt computeNodeStatistics()
Ongoing work transposing kmeans clustering method for bitfields: adapt findNN() method
Ongoing work transposing kmeans clustering method for bitfields: allow kmeans with Hamming distance
Ongoing work transposing kmeans clustering method for bitfields: adapt distances code
Ongoing work transposing kmeans clustering method for bitfields: adapt load/save code
Ongoing work transposing kmeans clustering method for bitfields: adapt kmeans hierarchicalClustring()
PivotType -> CentersType Renaming
Fix type casting for ARM SIMD implementation of Hamming
Fix warnings with Win32 compilation
Fix warnings with Win64 compilation
Fix wrong parenthesis position on rounding
* Ensure proper rounding when CentersType is integral
double area = moms.m00;
is same as
double area = contourArea(contours[contourIdx]);
Not to mention
"moms" already calculated here,"contourArea" should not apply
* Clean: replace C style asserts by CV_Assert and CV_DbgAssert
* Try fixing warning on Windows compilation
* Another way trying to fix warnings on Win
* Fixing warnings with some compilers:
Some compilers warn on systematic exit preventing to execute the code that follows.
This is why assert(0) that exits only in debug was working, but not CV_Assert or CV_Error
that exit both in release and debug, even if with different behavior.
In addition, other compilers complain when return 0 is removed from getKey(),
even if before we have a statement leading to systematic exit.
* Disable "unreachable code" warnings for Win compilers so we can use proper CV_Error
Before, when maxCheck was reached in the first descent of a tree, time was still wasted parsing
the next trees till their best leaves whose points were not used at all.
Clarify component statistics documentation
* Change ConnectedComponentsTypes documentation
Change from "algorithm output formats" to "statistics" because it specifies types of statistics, not formats.
* Documentation: clarify component statistics
Explain that ConnectedComponentTypes selects a statistic.
Argument "a" is of type ElementType* that is either int* or float*, while b was double*.
Mixing types prevents the possibility to use SSE or AVX instructions.
On implementation without SIMD instructions, this doesn't show any impact on performance.
* Clean: make the use of the indices array length consistent
Either we don't want this method to be used in the future for any other node
than the root node, and so we replace indices_length by size_ and remove it as
argument, or we want to be able to use it potentially for other nodes, and
so using size_ instead of indices_length would have lead to a bug.
* Fix: b was not an address
* Fix: transpose the Flann repo commit "Fixes in accum_dist methods" from Adil Ibragimov
Avoids trying to compute log(ratio) with ratio = 0
* Fix: transpose the Flann repo commit "result_set bugfix" from Jack Rae
* Fix Jack Rae commit as the initial i - 1 index was decremented before entering the loop body
* Clean: transpose the Flann repo commit "Updated comments in lsh_index" from Richard McPherson
* Fix: Transpose the Flann repo commit "Fixing unreachable code in lsh_table.h" from hypevr
* Fix warning the same way it was done in flann standalone repo
* Change the return value in case of unsupported type
Instead of using the current dimension for which we just got a big span,
we were computing Min and Max for the previous dimension stored in cutfeat
(and using 0 instead of the dimension indice for the very first dimension
with "span > (1-eps)max_span")
* Add documentation about usage of cv2eigen functions in eigen.hpp
* Fixed Doxygen syntax.
Co-authored-by: Alexander Smorkalov <smorkalov.a.m@gmail.com>
* improved fitEllipse and fitEllipseDirect accuracy in singular or close-to-singular cases (see issue #9923)
* scale points using double precision
* added normalization to fitEllipseAMS as well; fixed Java test case by raising the tolerance (it's unclear what is the correct result in this case).
* improved point perturbation a bit. make the code a little bit more clear
* trying to fix Java fitEllipseTest by slightly raising the tolerance threshold
* synchronized C++ version of Java's fitEllipse test
* removed trailing whitespaces
* fixed#17044
1. fixed Python part of the tutorial about using OpenCV XML-YAML-JSON I/O functionality from C++ and Python.
2. added startWriteStruct() and endWriteStruct() methods to FileStorage
3. modifed FileStorage::write() methods to make them work well inside sequences, not only mappings.
* try to fix the doc builder
* added Python regression test for FileStorage I/O API ([TODO] iterating through long sequences can be very slow)
* fixed yaml testing
Fix Test Case: in latest version, window.cv is a promise instance that makes most test case failed.
* Fix Browser Test Case: In latest version, window.cv is a promise instance
In latest version of opencv.js, window.cv is promise instance.
So that most of the test cases is run failed.
This commit is to fix browser test case.
* Add comment for backward compatible
Add comments for backward compatible
* Fix integer overflow in parseOption().
Previous code does not work for values like 100000MB.
* Fix warning during 32-bit build on inactive code path.
* fix build without C++11
* add eigen tensor conversion functions
* add eigen tensor conversion tests
* add support for column major order
* update eigen tensor tests
* fix coding style and add conditional compilation
* fix conditional compilation checks
* remove whitespace
* rearrange functions for easier reading
* reformat function documentation and add tensormap unit test
* cleanup documentation of unit test
* remove condition duplication
* check Eigen major version, not minor version
* restrict to Eigen v3.3.0+
* add documentation note and add type checking to cv2eigen_tensormap()
* Fixed indexing in prefilter
* Initialised prefilter
* Initialised prefilter with value initialisation
* Added TC to trigger different Mem Allocs in BufferBM
* Optimize cases with only needed conditions
