Feat #25150: Pose Graph MST initialization #27423
Implements an MST-based initialisation for pose graphs, as proposed in issue #25150. Both Prim’s and Kruskal’s algorithms were added to the 3D module. These receive a vector of node IDs and a vector of edges (each with source and target IDs and a weight), and return a vector with the resulting edges. These MST implementations treat edges as undirected internally, meaning users only need to provide one direction (A→B or B→A), and duplicates are handled automatically.
Additionally, a new pose graph initialisation method using MST (Prim) was implemented. It constructs the MST over the pose graph, then traverses it to reconstruct node poses. With this, users can call `poseGraph->initializePosesWithMST()` to create an initial solution for the pose graph problem.
A set of test cases validating the implementation was also included.
#### Notes
- The edge weight used in the MST for pose graphs is calculated as:
`weight = || translation || + λ * rotation_angle`,
where λ = 0.485 was determined empirically based on optimiser performance;
- Validated on [Sphere-a](https://lucacarlone.mit.edu/datasets/) pose graph, showing similar convergence behaviour with or without MST initialisation;
- Alternative weight formulas, such as the Mahalanobis distance formula, were also tested, but the current formula yielded better results.
#### Future Work
- Extend testing to more diverse pose graphs (currently limited to [Sphere-a](https://github.com/opencv/opencv_extra/blob/5.x/testdata/cv/rgbd/sphere_bignoise_vertex3.g2o) in opencv_extra)
- Explore adaptive tuning of the λ parameter for broader applicability.
Co-authored-by: @miguel1099
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Extend image I/O API with metadata support #27499
Covered with the PR:
* AVIF encoder can write exif, xmp, icc
* AVIF decoder can read exif
* JPEG encoder can write exif
* JPEG decoder can read exif
* PNG encoder can write exif
* PNG decoder can read exif
This PR is a sort of preamble for #27488. I suggest to merge this one first to OpenCV 4.x, then promote this change to OpenCV 5.x and then provide extra API to read and write metadata in 5.x (or maybe 4.x) in a style similar to #27488. Maybe in that PR exif packing/unpacking should be done using a separate external API. That is, metadata reading and writing can/should be done in 2 steps:
* [1] pack and then [2] embed exif into image at the encoding stage.
* [1] extract and then [2] unpack exif at the decoding stage.
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Consider QRCode ECI encoding #24426
### Pull Request Readiness Checklist
related: https://github.com/opencv/opencv/pull/24350#pullrequestreview-1661658421
1. Add `getEncoding` method to obtain ECI number
2. Add `detectAndDecodeBytes`, `decodeBytes`, `decodeBytesMulti`, `detectAndDecodeBytesMulti` methods in Python (return `bytes`) and Java (return `byte[]`)
3. Allow Python bytes to std::string conversion in general and add `encode(byte[] encoded_info, Mat qrcode)` in Java
Python example with Kanji encoding:
```python
img = cv.imread("test.png")
detect = cv.QRCodeDetector()
data, points, straight_qrcode = detect.detectAndDecodeBytes(img)
print(data)
print(detect.getEncoding(), cv.QRCodeEncoder_ECI_SHIFT_JIS)
print(data.decode("shift-jis"))
```
```
b'\x82\xb1\x82\xf1\x82\xc9\x82\xbf\x82\xcd\x90\xa2\x8aE'
20 20
こんにちは世界
```
source: https://github.com/opencv/opencv/blob/ba4d6c859d21536f84e0328c16f4cc3e96bf3065/modules/objdetect/test/test_qrcode_encode.cpp#L332

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Adding color correction module to photo module from opencv_contrib #27051
This PR moved color correction module from opencv_contrib to main repo inside photo module.
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Add HoughCirclesWithAccumulator binding #27389
### Pull Request Readiness Checklist
Fix#27377
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Java VideoCapture buffered stream constructor #27284
### Pull Request Readiness Checklist
resolves#26809
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Support bool type for FileStorage Base64 #26937
### Pull Request Readiness Checklist
OpenCV extra: https://github.com/opencv/opencv_extra/pull/1238
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Added trackers factory with pre-loaded dnn models #26875
Replaces https://github.com/opencv/opencv/pull/26295
Allows to substitute custom models or initialize tracker from in-memory model.
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Removed g-api from the main repo #26469
Following #25000.
CI patch: https://github.com/opencv/ci-gha-workflow/pull/196
This is migration of G-API from opencv to opencv_contrib, part 1.
Here we simply remove G-API from the main repo. The next patch should bring G-API to opencv_contrib.
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int64 data type support for FileStorage. 1d and empty Mat with exact dimensions #26434
### Pull Request Readiness Checklist
Port of https://github.com/opencv/opencv/pull/26399 to 4.x branch
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int64 data type in FileStorage #26399
### Pull Request Readiness Checklist
resolves#23333
Proposed approach is not perfect in terms of complexity and potential bugs. Instead of changing `INT` raw size from `4` to `8`, we check int64 value can be fitted to int32 or not.
Collections such as cv::Mat rely on data type symbol.
This PR is addressed to 5.x branch first to cover `CV_64S` Mat. Later, it can be backported to 4.x
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Features2d cleanup: Move several feature detectors and descriptors to opencv_contrib #25292
features2d cleanup: #24999
The PR moves KAZE, AKAZE, AgastFeatureDetector, BRISK and BOW to opencv_contrib/xfeatures2d.
Related PR: opencv/opencv_contrib#3709
C-API cleanup: moved cvErrorStr to new interface, minor ts changes #26101
Merge with opencv/opencv_contrib#3786
**Note:** `toString` might be too generic name (even though it is in `cv::Error::` namespace), another variant is `codeToString` (we have `typeToString` and `depthToString` in check.hpp).
**Note:** _ts_ module seem to have no other C API usage except for `ArrayTest` class which requires refactoring.
Add support for boolan input/outputs in python bindings #26026
This PR add support boolean input/output binding in python. The issue what mention in ticket https://github.com/opencv/opencv/issues/26024 and the PR soleves it. Data and models are located in [here](https://github.com/opencv/opencv_extra/pull/1201)
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