Added flag to GaussianBlur for faster but not bit-exact implementation #25792
Rationale:
Current implementation of GaussianBlur is almost always bit-exact. It helps to get predictable results according platforms, but prohibits most of approximations and optimization tricks.
The patch converts `borderType` parameter to more generic `flags` and introduces `GAUSS_ALLOW_APPROXIMATIONS` flag to allow not bit-exact implementation. With the flag IPP and generic HAL implementation are called first. The flag naming and location is a subject for discussion.
Replaces https://github.com/opencv/opencv/pull/22073
Possibly related issue: https://github.com/opencv/opencv/issues/24135
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Add a new function that approximates the polygon bounding a convex hull with a certain number of sides #25607
merge PR with <https://github.com/opencv/opencv_extra/pull/1179>
This PR is based on the paper [View Frustum Optimization To Maximize Object’s Image Area](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=1fbd43f3827fffeb76641a9c5ab5b625eb5a75ba).
# Problem
I needed to reduce the number of vertices of the convex hull so that the additional area was minimal, andall vertices of the original contour enter the new contour.
# Description
Initially in the contour of n vertices, at each stage we consider the intersection points of the lines formed by each adjacent edges. Each of these intersection points will form a triangle with vertices through which lines pass. Let's choose a triangle with the minimum area and merge the two vertices at the intersection point. We continue until there are more vertices than the specified number of sides of the approximated polygon.
# Complexity:
Using a std::priority_queue or std::set time complexity is **(O(n\*ln(n))**, memory **O(n)**,
n - number of vertices in convex hull.
count of sides - the number of points by which we must reduce.
## Comment
If epsilon_percentage more 0, algorithm can return more values than _side_.
Algorithm returns OutputArray. If OutputArray.type() equals 0, algorithm returns values with InputArray.type().
New test uses image which are not in opencv_extra, needs to be added.
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imgproc: remove C-API usage from tests #25842
Final cleanup will be done in 5.x after regular merge.
Some tests have been reworked, some required only slight modifications.
Accuracy tests for equalizeHist() added #25759
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Reverted contour approximation behavior #25680
Related issue #25663 - revert new function behavior despite it returning different result than the old one (reverts PR #25672).
Also added Coverity issue fix.
Tests for cvSmooth -> tests for boxFilter #25634fixes#25448
### Motivation
The obsolete function `cvSmooth` has two modes in which it calls `cv::boxFilter()` inside with and without normalization.
This function is covered by tests exactly for that modes.
This means that by replacing `cvSmooth` call by `cv::boxFilter()` we will leave the coverage untouched (but more obvious) and remove that obsolete function from tests.
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imgproc: C-API cleanup, drawContours refactor #25564
Changes:
* moved several macros from types_c.h to cvdef.h (assuming we will continue using them)
* removed some cases of C-API usage in _imgproc_ module (`CV_TERMCRIT_*` and `CV_CMP_*`)
* refactored `drawContours` to use C++ API instead of calling `cvDrawContours` + test for filled contours with holes (case with non-filled contours is simpler and is covered in some other tests)
#### Note:
There is one case where old drawContours behavior doesn't match the new one - when `contourIdx == -1` (means "draw all contours") and `maxLevel == 0` (means draw only selected contours, but not what is inside).
From the docs:
> **contourIdx** Parameter indicating a contour to draw. If it is negative, all the contours are drawn.
> **maxLevel** Maximal level for drawn contours. If it is 0, only the specified contour is drawn. If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account when there is hierarchy available.
Old behavior - only one first contour is drawn:
a
New behavior (also expected by the test) - all contours are drawn:
imgproc: refactor EMD to reduce C-API usage #25469
- added more tests for EMD
- refactored to remove CvArr
- used BufferArea for memory allocations
- renamed functions and variables and formatted the code
- kept legacy functions intact in separate header
Reworked findContours to reduce C-API usage #25146
What is done:
* rewritten `findContours` and `icvApproximateChainTC89` using C++ data structures
* extracted LINK_RUNS mode to separate new public functions - `findContoursLinkRuns` (it uses completely different algorithm)
* ~added new public `cv::approximateChainTC89`~ - **❌ decided to hide it**
* enabled chain code output (method = 0, no public enum value for this in C++ yet)
* kept old function as `findContours_old` (exported, but not exposed to user)
* added more tests for findContours (`test_contours_new.cpp`), some tests compare results of old function with new one. Following tests have been added:
* contours of random rectangle
* contours of many small (1-2px) blobs
* contours of random noise
* backport of old accuracy test
* separate test for LINK RUNS variant
What is left to be done (can be done now or later):
* improve tests:
* some tests have limited verification (e.g. only verify contour sizes)
* perhaps reference data can be collected and stored
* maybe more test variants can be added (?)
* add enum value for chain code output and a method of returning starting points (e.g. first 8 elements of returned `vector<uchar>` can represent 2 int point coordinates)
* add documentation for new functions - **✔️ DONE**
* check and improve performance (my experiment showed 0.7x-1.1x some time ago)
* remove old functions completely (?)
* change contour return order (BFS) or allow to select it (?)
* return result tree as-is (?) (new data structures should be exposed, bindings should adapt)
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.
First proposal of cv::remap with relative displacement field (#24603) #24621
Implements #24603
Currently, `remap()` is applied as `dst(x, y) <- src(mapX(x, y), mapY(x, y))` It means that the maps must be filled with absolute coordinates.
However, if one wants to remap something according to a displacement field ("warp"), the operation should be `dst(x, y) <- src(x+displacementX(x, y), y+displacementY(x, y))`
It is trivial to build a mapping from a displacement field, but it is an undesirable overhead for CPU and memory.
This PR implements the feature as an experimental option, through the optional flag WARP_RELATIVE_MAP than can be ORed to the interpolation mode.
Since the xy maps might be const, there is no attempt to add the coordinate offset to those maps, and everything is postponed on-the-fly to the very last coordinate computation before fetching `src`. Interestingly, this let `cv::convertMaps()` unchanged since the fractional part of interpolation does not care of the integer coordinate offset.
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Fix out of image corners in cv::cornerSubPix #24527
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Implement color conversion from RGB to YUV422 family #24333
Related PR for extra: https://github.com/opencv/opencv_extra/pull/1104
Hi,
This patch provides CPU and OpenCL implementations of color conversions from RGB/BGR to YUV422 family (such as UYVY and YUY2).
These features would come in useful for enabling standard RGB images to be supplied as input to algorithms or networks that make use of images in YUV422 format directly (for example, on resource constrained devices working with camera images captured in YUV422).
The code, tests and perf tests are all written following the existing pattern. There is also an example `bin/example_cpp_cvtColor_RGB2YUV422` that loads an image from disk, converts it from BGR to UYVY and then back to BGR, and displays the result as a visual check that the conversion works.
The OpenCL performance for the forward conversion implemented here is the same as the existing backward conversion on my hardware. The CPU implementation, unfortunately, isn't very optimized as I am not yet familiar with the SIMD code.
Please let me know if I need to fix something or can make other modifications.
Thanks!
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* 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 distanceTransform for inputs with large step and height #24214
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23895
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* 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.
Fix harmless ASAN error. #24042
For an empty radius, &v[0] would be accessed (though the called functions would not use it due to v.size() being 0). Also add checks for emptyness and fix the first element checks, in case we get INT_MAX to compare to.
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