The Kullback-Leibler divergence works with histogram that have integral = 1,
otherwise it can return negative values. The normalization of the histograms
have been changed accordingly, and all the six comparison methods have been
used in the histogram comparison tutorial.
Fix Typos and Improve Clarity in Documentation #27444
Description:
This pull request addresses minor typographical errors and improves the clarity of documentation in several markdown files. Specifically:
- Corrected spelling mistakes such as "traslation" to "translation".
- Improved phrasing for better readability and understanding.
- Added references to specific setter methods in the StereoBM documentation for more detailed guidance.
These changes are limited to documentation and do not affect any code functionality.
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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Document Qualcomm's FastCV DSP based OpenCV Extension APIs and usage instructions #27430
This PR updates the documentation by:
- Adding a new section: Qualcomm's FastCV DSP based OpenCV Extension APIs list, detailing the OpenCV APIs under the cv::fastcv::dsp namespace and their corresponding Qualcomm's FastCV DSP accelerated implementations.
- Providing a step-by-step guide on how to use the Qualcomm's FastCV DSP APIs.
- Update resizeDown and warpAffine mappings
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Fix NaNs in HDR Triangle Weights and Tonemapping and Update LDR Ground Truth in tutorial #27396
The PR closes#27392
Updated the triangle weights to use a small epsilon value instead of zero to prevent NaN issues in HDR processing.
Also fixed a float-to-double division issue by explicitly casting double values to float, which was previously producing garbage values and leading to NaNs in tonemapping.
The current LDR ground truth image used in the tutorial [ldr.png](https://github.com/opencv/opencv/blob/4.x/doc/tutorials/others/images/ldr.png) was originally generated using TonemapDurand (check this commit 833f8d16fa), which was moved to opencv_contrib a long time ago in this commit: 742f22c09b. However, the current Tonemap implementation in OpenCV main only performs normalization and gamma correction, which produces noticeably different results. This PR updates the LDR grouth truth image in tutorial with the result of TonemapDrago, and tutorials to use TonemapDrago as Tonemap gives a darker image.
Tonemap output:
TonemapDrago output:
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Feature: Add OpenVINO NPU support #27363
## Why
- OpenVINO now supports inference on integrated NPU devices in intel's Core Ultra series processors.
- Sometimes as fast as GPU, but should use considerably less power.
## How
- The NPU plugin is now available as "NPU" in openvino `ov::Core::get_available_devices()`.
- Removed the guards and checks for NPU in available targets for Inference Engine backend.
## Test example
### Pre-requisites
- Intel [Core Ultra series processor](https://www.intel.com/content/www/us/en/products/details/processors/core-ultra/edge.html#tab-blade-1-0)
- [Intel NPU driver](https://github.com/intel/linux-npu-driver/releases)
- OpenVINO 2023.3.0+ (Tested on 2025.1.0)
### Example
```cpp
#include <opencv2/dnn.hpp>
#include <iostream>
int main(){
cv::dnn::Net net = cv::dnn::readNet("../yolov8s-openvino/yolov8s.xml", "../yolov8s-openvino/yolov8s.bin");
cv::Size net_input_shape = cv::Size(640, 480);
std::cout << "Setting backend to DNN_BACKEND_INFERENCE_ENGINE and target to DNN_TARGET_NPU" << std::endl;
net.setPreferableBackend(cv::dnn::DNN_BACKEND_INFERENCE_ENGINE);
net.setPreferableTarget(cv::dnn::DNN_TARGET_NPU);
cv::Mat image(net_input_shape, CV_8UC3);
cv::randu(image, cv::Scalar(0, 0, 0), cv::Scalar(255, 255, 255));
cv::Mat blob = cv::dnn::blobFromImage(
image, 1, net_input_shape, cv::Scalar(0, 0, 0), true, false, CV_32F);
net.setInput(blob);
std::cout << "Running forward" << std::endl;
cv::Mat result = net.forward();
std::cout << "Output shape: " << result.size << std::endl; // Output shape: 1 x 84 x 6300
}
```
model files [here](https://limewire.com/d/bPgiA#BhUeSTBnMc)
docker image used to build opencv: [ghcr.io/mro47/opencv-builder](https://github.com/MRo47/opencv-builder/blob/main/Dockerfile)
Closes#26240
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Fix typos #27338
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videoio: add Orbbec Gemini 330 camera support #27230
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### Description of Changes
#### motivated：
- Orbbec has launched a new RGB-D camera — the Gemini 330. To fully leverage the capabilities of the Gemini 330, Orbbec simultaneously released version 2 of the open-source OrbbecSDK. This PR adapts the support for the Gemini 330 series cameras to better meet and respond to users’ application requirements.
#### change：
- Add support for the Orbbec Gemini330 camera.
- Fixed an issue with Femto Mega on Windows 10/11; for details, see [issue](https://github.com/opencv/opencv/pull/23237#issuecomment-2242347295).
- When enabling `HAVE_OBSENSOR_ORBBEC_SDK`, the build now fetches version 2 of the OrbbecSDK, and the sample API calls have been updated to the v2 format.
### Testing
| OS | Compiler | Camera | Result |
|:----------:|:---------------------------------------:|:-----------------:|:------:|
| Windows 11 | (VS2022) MSVC runtime library version 14.40 | Gemini 335/336L | Pass |
| Windows 11 | (VS2022) MSVC runtime library version 14.19 | Gemini 335/336L | Pass |
| Ubuntu22.04| GCC 11.4 | Gemini 335/336L | Pass |
| Ubuntu18.04| GCC 7.5 | Gemini 335/336L | Pass |
### Acknowledgements
Thank you to the OpenCV team for the continuous support and for creating such a robust open source project. I appreciate the valuable feedback from the community and reviewers, which has helped improve the quality of this contribution!
Minor changes in calib3d docs for clarity #27221
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build: Check supported C++ standard features and user setting #27107Close#27105
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* Added mcc to opencv modules
* Removed color correction module
* Updated parameters return type
* Added python sample for macbeth_chart_detection
* Added models.yml support to samples
* Removed unnecessary headers and classes
* fixed datatype conversion
* fixed datatype conversion
* Cleaned headers and added reference/actual colors to samples
* Added mcc tutorial
* fixed datatype and header
* replaced unsigned with int
* Aligned actual and reference color function, added imread
* Fixed shadow variable
* Updated samples
* Added last frame colors prints
* updated detector class
* Added getter functions and useNet function
* Refactoring
* Fixes in test
* fixed infinite divison issue
Update tutorials #26441
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Documentation to enable FastCV based OpenCV HAL and Extensions #26910
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doc: update supporting imgcodec format settings #26889
Close https://github.com/opencv/opencv/issues/26877
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Add direct pdf links in the bibliography #26754
Update and add pdf links in the bibliography.
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OpenEXR 2.2 or earlier cannot be used with C++17 or later #26678
Close https://github.com/opencv/opencv/issues/26673
Close https://github.com/opencv/opencv/issues/25313
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Feature: weighted Hough Transform #21407
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Animated WebP Support #25608
related issues #24855#22569
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Improvement of macOS installation guide in documentation #26564
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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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