Optimize&Fix fitEllipse sample

…layers

Minor grammatical fixes to dnn_custom_layers doc file

…ample

Optimize&Fix fitEllipse sample

Add ENABLE_DELAYLOAD option

Added argument to print notice in `roiSelector.cpp`

Related Issue : opencv#23175

I've added a printNotice argument to `selectROI` (and it's overload) and `selectROIs` functions.
I've also updated the function declarations in `highgui.hpp`.
Tested by building locally.

### 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
- [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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Added regression test for the flipped images

use findFile in opengl.cpp sample

…_PROP_WHITE_BALANCE_BLUE_U_support_in_CAP_DSHOW

Support VideoCapture CAP_PROP_AUTO_WB and CV_CAP_PROP_WHITE_BALANCE_BLUE_U for DShow

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [OK] I agree to contribute to the project under Apache 2 License.
- [OK] 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
- [OK] The PR is proposed to the proper branch
- [OK] There is a reference to the original bug report and related work
opencv#19621
opencv#21408

### Before apply this pull request console output.

before AWB setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

after AWB disable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

after AWB enable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

after Manual WB(and Disable AWB) setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

### After apply this pull request console output.

before AWB setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: 0

after AWB disable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 4000
CAP_PROP_AUTO_WB: 0

after AWB enable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 4000
CAP_PROP_AUTO_WB: 1

after Manual WB(and Disable AWB) setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: 0

### Test Code
[OpenCvVideoCapTest.zip](https://github.com/opencv/opencv/files/10825399/OpenCvVideoCapTest.zip)

Propagate inputs info for ONNX and TFLite models

### Pull Request Readiness Checklist

Needed for generic applications such as benchmarking pipelines. So OpenCV can tell about the default input shapes specified in the models.

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
- [x] 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

Add possibility for disabling inlining `wasm` in `opencv.js`

…ected_but_not_decoded_bug

Added QR_Code data flip support, flip and retry after first ECC failure

highgui: Set hard GLib requirement to >=2.32

Fix error of `POSE_PAIRS` in pose estimation doc

Python tutorial links update

…ing keypoints prior to region growing

This makes LineSegmentDetector deterministic by using stable_sort for ordering points by norm. Without this change the region growing in LSD is non-determinstic and thus the returned lines are changing between invocations.

This is a replacement for opencv#23370

two typos

…aracter code

Fix for using sampleIdx to limit training data

Make LineSegmentDetector deterministic by using stable_sort

…ction_precision

better accuracy for _rotatedRectangleIntersection() (proposal for opencv#23546) opencv#23690

_rotatedRectangleIntersection() can be (statically) customized to use double instead of float for better accuracy
this is a proposal for experimentation around opencv#23546

for better accuracy, _rotatedRectangleIntersection() could use double. It will still return cv::Point2f list for backward compatibility, but the inner computations are controlled by a typedef

- [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
- [X] 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

…tion

G-API: Integration branch for ONNX & Python-related changes opencv#23597

# Changes overview

## 1. Expose ONNX backend's Normalization and Mean-value parameters in Python

* Since Python G-API bindings rely on `Generic` infer to express Inference, the `Generic` specialization of `onnx::Params` was extended with new methods to control normalization (`/255`) and mean-value; these methods were exposed in the Python bindings
* Found some questionable parts in the existing API which I'd like to review/discuss (see comments)

UPD:
1. Thanks to @TolyaTalamanov normalization inconsistencies have been identified with `squeezenet1.0-9` ONNX model itself; tests using these model were updated to DISABLE normalization and NOT using mean/value.
2. Questionable parts were removed and tests still pass.

### Details (taken from @TolyaTalamanov's comment):

`squeezenet1.0.*onnx` - doesn't require scaling to [0,1] and mean/std because the weights of the first convolution already scaled. ONNX documentation is broken. So the correct approach to use this models is:

1. ONNX: apply preprocessing from the documentation: https://github.com/onnx/models/blob/main/vision/classification/imagenet_preprocess.py#L8-L44 but without normalization step:
```
# DON'T DO IT:
# mean_vec = np.array([0.485, 0.456, 0.406])
# stddev_vec = np.array([0.229, 0.224, 0.225])
# norm_img_data = np.zeros(img_data.shape).astype('float32')
# for i in range(img_data.shape[0]):
#     norm_img_data[i,:,:] = (img_data[i,:,:]/255 - mean_vec[i]) / stddev_vec[i]
#     # add batch channel
#     norm_img_data = norm_img_data.reshape(1, 3, 224, 224).astype('float32')
#     return norm_img_data

# INSTEAD
return img_data.reshape(1, 3, 224, 224)
```

2. G-API: Convert image from BGR to RGB and then pass to `apply` as-is with configuring parameters:
```
net = cv.gapi.onnx.params('squeezenet', model_filename)
net.cfgNormalize('data_0', False)
```
**Note**: Results might be difference because `G-API` doesn't apply central crop but just do resize to model resolution.

---

`squeezenet1.1.*onnx` - requires scaling to [0,1] and mean/std - onnx documentation is correct.
1. ONNX: apply preprocessing from the documentation: https://github.com/onnx/models/blob/main/vision/classification/imagenet_preprocess.py#L8-L44
2. G-API: Convert image from BGR to RGB and then pass to `apply` as-is with configuring parameters:
```
net = cv.gapi.onnx.params('squeezenet', model_filename)
net.cfgNormalize('data_0', True) // default
net.cfgMeanStd('data_0', [0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
```
**Note**: Results might be difference because `G-API` doesn't apply central crop but just do resize to model resolution.

## 2. Expose Fluid & kernel package-related functionality in Python

* `cv::gapi::combine()`
* `cv::GKernelPackage::size()` (mainly for testing purposes)
* `cv::gapi::imgproc::fluid::kernels()`

Added a test for the above.

## 3. Fixed issues with Python stateful kernel handling

Fixed error message when `outMeta()` of custom python operation fails.

## 4. Fixed various issues in Python tests

1. `test_gapi_streaming.py` - fixed behavior of Desync test to avoid sporadic issues
2. `test_gapi_infer_onnx.py` - fixed model lookup (it was still using the ONNX Zoo layout but was NOT using the proper env var we use to point to one).

### 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
- [x] 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