Xfeat feature - #29361
## PR Description
### Summary
Integrate XFeat into OpenCV's `features` module as a native `Feature2D` implementation, enabling lightweight neural feature detection and descriptor extraction through OpenCV's standard feature extraction API.
---
### What's included
#### New class
- **`cv::XFeat`** extends `Feature2D`
- CNN-based keypoint detection
- 64-D descriptor extraction via ONNX/DNN
- Score-map based keypoint selection
- Descriptor sampling from the dense feature map
---
### Files added
| File | Description |
|------|-------------|
| `src/feature2d_xfeat.cpp` | XFeat `Feature2D` implementation |
| `test/test_xfeat.cpp` | XFeat unit and regression tests |
---
### Files modified
- `features.hpp`
- Add `cv::XFeat` declaration and public factory APIs
---
### Usage
```cpp
#include <opencv2/features.hpp>
using namespace cv;
// Feature extraction
Ptr<XFeat> xfeat =
XFeat::create("xfeat.onnx", 2000, 0.5f, 640);
std::vector<KeyPoint> keypoints;
Mat descriptors;
xfeat->detectAndCompute(image, noArray(), keypoints, descriptors);
```
---
### Test dependency
Depends on the opencv_extra changes adding the XFeat ONNX model and reference outputs.
Required test data:
https://github.com/opencv/opencv_extra/pull/1383
- `xfeat.onnx`
- `xfeat_lena_640_kpts.npy`
- `xfeat_lena_640_desc.npy`
These files are required for the `Features2d_XFeat` tests in the main OpenCV repository to validate XFeat feature extraction and descriptor generation.
### Pull Request Readiness Checklist
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
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
