Split Javascript white-list to support contrib modules #25986
Single whitelist converted to several per-module json files. They are concatenated automatically and can be overriden by user config.
Related to https://github.com/opencv/opencv/pull/25656
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Increase neighbors search radius for corners in ChessBoardDetector:findQuadNeighbors #26014
I didn't do everything right the way I wanted at #25991. I forgot that `edge_len` is edge **squared** length as well as `thresh_scale` is threshold for **squared** scale. So, I wanted to increase scale by `sqrt(2)` times (idea is to use quad diagonal instead of quad side) and therefore `thresh_scale` should be equal to `sqrt(2)^2 = 2`.
And refactor variables names to explicitly indicate that they are squared, so that no one else falls into this trap
I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```
PR increases detected chessboards number by `1/2%`:
```
cell_img_size = 100 (default)
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.941667 13560 14400 0.596726
Total detected time: 136.68963200000007 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.952083 13710 14400 0.595984
Total detected time: 136.55770600000014 sec
----------------------------------------------------------------------------------------------------------------------------------------------
cell_img_size = 10
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.579167 8340 14400 4.198448
Total detected time: 2.535998999999999 sec
after
category detected chessboard total detected chessboard total chessboard average detected error
all 0.591389 8516 14400 4.155250
Total detected time: 2.700832999999997 sec
```
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Improve corners matching in ChessBoardDetector::NeighborsFinder::findCornerNeighbor #25991
### Pull Request Readiness Checklist
Idea was mentioned in `Section III-B. New Heuristic for Quadrangle Linking` of `Rufli, Martin & Scaramuzza, Davide & Siegwart, Roland. (2008). Automatic Detection of Checkerboards on Blurred and Distorted Images. 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS. 3121-3126. 10.1109/IROS.2008.4650703` (https://rpg.ifi.uzh.ch/docs/IROS08_scaramuzza_b.pdf):
```
* For each candidate pair, focus on the quadrangles they belong to and draw two straight lines passing through the midsections of the respective quadrangle edges (see Fig. 6).
* If the candidate corner and the source corner are on the same side of every of the four straight lines drawn this way (this corresponds to the yellow shaded area in Fig. 6), then the corners are successfully matched.
```
By improving corners matching, we can increase the search radius (`thresh_scale`).
I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```
PR increases detected chessboards number by `3/7%`:
```
cell_img_size = 100 (default)
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.910417 13110 14400 0.599746
Total detected time: 147.50906700000002 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.941667 13560 14400 0.596726
Total detected time: 136.68963200000007 sec
----------------------------------------------------------------------------------------------------------------------------------------------
cell_img_size = 10
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.539792 7773 14400 4.208237
Total detected time: 2.668964 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.579167 8340 14400 4.198448
Total detected time: 2.535998999999999 sec
```
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
- [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.
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Search in two directions when try to add new quad in addOuterQuad #25807
In ChessBoardDetector::addOuterQuad, previous code try to connect new quad with inner quad, if possible, but only search for one direction. I have made three test images, one is normal(a.jpg), one lossed an outer quad(b.jpg), and then i flipped it vertically(c.jpg). Only last one fails. I fixed it by check two directions and row/col.
Here is the test code and images:
```
Mat img;
vector<Point2f> corners;
auto size = cv::Size(6, 6);
img = imread("D:/tmp/a.jpg", 0);
std::cout<<cv::findChessboardCorners(img, size, corners)<<"\n";
std::cout << corners.size() << "\n";
img = imread("D:/tmp/b.jpg", 0);
std::cout<<cv::findChessboardCorners(img, size, corners)<<"\n";
std::cout << corners.size() << "\n";
img = imread("D:/tmp/c.jpg", 0);
std::cout<<cv::findChessboardCorners(img, size, corners)<<"\n";
std::cout << corners.size() << "\n";
```
a
b
c
calib3d: fix Rodrigues CV_32F and CV_64F type mismatch in projectPoints #25824Fixes#25318
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Enable checkerboard detection with a central / corner marker on a black tile #25808
This pull request closes the issue #25806.
The issue doesn't require any documentation - it's quite intuitive that the detection result shouldn't depend on the color of the marker's tile.
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Fix Homography computation. #25665
The bug was introduced in https://github.com/opencv/opencv/pull/25308
I am sorry I do not have a proper test.
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Fix handeye #24897
Fixes to the hand-eye calibration methods, from #24871.
The Tsai method is sensitive to poses separated by small rotations, so I filter those out.
The Horaud and Daniilidis methods use quaternions (and dual quaternions), where $q$ and $-q$ represent the same transform.
However, these methods depend on the gripper motion and camera motion having the same sign for the real part.
The fix was simply to multiply the (dual) quaternions by -1 if their real part is negative.
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HAL for projectPoints() added #25511
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Fix documentation for findEssentialMat to reflect how it actually works. #25488
Documentation for findEssentialMat() incorrectly states that the method uses the same cameraMatrix for both lists of points even though there are two cameraMatrix and distCoeffs.
Checked the code and it does the right thing i.e. uses cameraMatrix1, distCoeffs1 for points1 and cameraMatrix2, distCoeffs2 for points2.
Updated the documentation for the method to clarify what it does. The code itself is not changed.
Calibrate hand eye datatype fix#25423
Fix for issue https://github.com/opencv/opencv/issues/25421.
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- [x] I agree to contribute to the project under Apache 2 License.
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Speed up adaptive threshold in findChessboardCorners #25177
### Pull Request Readiness Checklist
If `block_size` hasn't been changed between iterations for same `k`, then all `adaptiveThreshold` arguments will be same and we can reuse result from previous iteration.
I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```
PR speed up chessboards detection by `7.5/17%` without any changes in detected chessboards number:
```
cell_img_size = 100 (default)
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.904167 13020 14400 0.600512
Total detected time: 107.27875600000003 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.904167 13020 14400 0.600512
Total detected time: 99.0223499999999 sec
----------------------------------------------------------------------------------------------------------------------------------------------
cell_img_size = 10
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.539792 7773 14400 4.209964
Total detected time: 2.989205999999999 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.539792 7773 14400 4.209964
Total detected time: 2.4802350000000013 sec
```
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
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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)
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Handle degenerate cases in RQDecomp3x3 #25050
The point of the Givens rotations here is to iteratively set the lower left matrix entries to zero. If an element is zero already, we don't need to do anything. This resolves#24330.
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Compensate edge length in ChessBoardDetector::generateQuads (attempt 2) #25090
### Pull Request Readiness Checklist
New attempt for #24833, which was reverted as #25036.
Locally I fixed `Calib3d_StereoCalibrate_CPP.regression` test by corners refinement using `cornerSubPix` function
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Fix very slow compilation of five-point algorithm on some platforms (e.g. Qualcomm) #25064
Thanks to our big friend and long-term contributor for the patch!
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solvePnP implementation for Fisheye camera model #25028
Credits to Linfei Pan
Extracted from https://github.com/opencv/opencv/pull/24052
**Warning:** The patch changes Obj-C generator behaviour and adds "fisheye_" prefix for all ObjC functions from namespace.
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Co-authored-by: lpanaf <linpan@student.ethz.ch>
Co-authored-by: Vadim Levin <vadim.levin@xperience.ai>
bug fix infinite loop #24987Fixes#24967
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Bugfix to #24967
Fix bug in ChessBoardDetector::findQuadNeighbors #24779
### Pull Request Readiness Checklist
`corners` and `neighbors` indices means not filling order, but relative position. So, for example if `quad->count = 2`, it doesn't mean that `quad->neighbors[0]` and `quad->neighbors[1]` are filled. And we should should iterate over all four `neighbors`.
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Fix mismatch and simplify code in ChessBoardDetector::findQuadNeighbors #24667
### Pull Request Readiness Checklist
Сode doesn't match comment.
If we want check `1:4` edges ratio and `edge_len` is squared edge length, then we should check
```
ediff > 15*edge_len
```
with constant `15`, not `32`, because
```
ediff > 15*edge_len2 <=> edge_len1 - edge_len2 > 15*edge_len2 <=> edge_len1 > 16*edge_len2 <=> 1:4 edges ratio
```
But for me it's better and simpler to directly check `edge_len1 > 16*edge_len2`
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