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‎.github/ISSUE_TEMPLATE.md

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<!--
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If you have a question rather than reporting a bug please go to http://answers.opencv.org where you get much faster responses.
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If you need further assistance please read [How To Contribute](https://github.com/Itseez/opencv/wiki/How_to_contribute).
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If you need further assistance please read [How To Contribute](https://github.com/opencv/opencv/wiki/How_to_contribute).
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This is a template helping you to create an issue which can be processed as quickly as possible. This is the bug reporting section for the OpenCV library.
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-->

‎3rdparty/ffmpeg/ffmpeg.cmake

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set(FFMPEG_FILE_HASH_BIN64 "35fe6ccdda6d7a04e9056b0d73b98e76")
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set(FFMPEG_FILE_HASH_CMAKE "8606f947a780071f8fcce8cbf39ceef5")
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set(FFMPEG_DOWNLOAD_URL ${OPENCV_FFMPEG_URL};$ENV{OPENCV_FFMPEG_URL};https://raw.githubusercontent.com/Itseez/opencv_3rdparty/${FFMPEG_BINARIES_COMMIT}/ffmpeg/)
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set(FFMPEG_DOWNLOAD_URL ${OPENCV_FFMPEG_URL};$ENV{OPENCV_FFMPEG_URL};https://raw.githubusercontent.com/opencv/opencv_3rdparty/${FFMPEG_BINARIES_COMMIT}/ffmpeg/)
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ocv_download(PACKAGE opencv_ffmpeg.dll
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HASH ${FFMPEG_FILE_HASH_BIN32}

‎3rdparty/ippicv/downloader.cmake

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if(DEFINED ENV{OPENCV_ICV_URL})
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set(OPENCV_ICV_URL $ENV{OPENCV_ICV_URL})
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else()
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set(OPENCV_ICV_URL "https://raw.githubusercontent.com/Itseez/opencv_3rdparty/${IPPICV_BINARIES_COMMIT}/ippicv")
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set(OPENCV_ICV_URL "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${IPPICV_BINARIES_COMMIT}/ippicv")
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endif()
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endif()
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‎CONTRIBUTING.md

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## Contributing guidelines
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All guidelines for contributing to the OpenCV repository can be found at [`How to contribute guideline`](https://github.com/Itseez/opencv/wiki/How_to_contribute).
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All guidelines for contributing to the OpenCV repository can be found at [`How to contribute guideline`](https://github.com/opencv/opencv/wiki/How_to_contribute).

‎README.md

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* Homepage: <http://opencv.org>
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* Docs: <http://docs.opencv.org/master/>
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* Q&A forum: <http://answers.opencv.org>
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* Issue tracking: <https://github.com/Itseez/opencv/issues>
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* Issue tracking: <https://github.com/opencv/opencv/issues>
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#### Contributing
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Please read before starting work on a pull request: <https://github.com/Itseez/opencv/wiki/How_to_contribute>
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Please read before starting work on a pull request: <https://github.com/opencv/opencv/wiki/How_to_contribute>
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Summary of guidelines:
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‎doc/Doxyfile.in

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TOC_EXPAND = NO
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GENERATE_QHP = @CMAKE_DOXYGEN_GENERATE_QHP@
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QCH_FILE = ../opencv-@[email protected]
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QHP_NAMESPACE = org.itseez.opencv.@OPENCV_VERSION@
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QHP_NAMESPACE = org.opencv.@OPENCV_VERSION@
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QHP_VIRTUAL_FOLDER = opencv
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QHP_CUST_FILTER_NAME =
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QHP_CUST_FILTER_ATTRS =

‎doc/py_tutorials/py_feature2d/py_brief/py_brief.markdown

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Below code shows the computation of BRIEF descriptors with the help of CenSurE detector. (CenSurE
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detector is called STAR detector in OpenCV)
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note, that you need [opencv contrib](https://github.com/Itseez/opencv_contrib)) to use this.
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note, that you need [opencv contrib](https://github.com/opencv/opencv_contrib)) to use this.
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@code{.py}
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import numpy as np
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import cv2

‎doc/py_tutorials/py_feature2d/py_sift_intro/py_sift_intro.markdown

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So this is a summary of SIFT algorithm. For more details and understanding, reading the original
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paper is highly recommended. Remember one thing, this algorithm is patented. So this algorithm is
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included in [the opencv contrib repo](https://github.com/Itseez/opencv_contrib)
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included in [the opencv contrib repo](https://github.com/opencv/opencv_contrib)
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SIFT in OpenCV
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--------------

‎doc/py_tutorials/py_setup/py_intro/py_intro.markdown

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Since OpenCV is an open source initiative, all are welcome to make contributions to the library,
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documentation, and tutorials. If you find any mistake in this tutorial (from a small spelling
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mistake to an egregious error in code or concept), feel free to correct it by cloning OpenCV in
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[GitHub](https://github.com/Itseez/opencv) and submitting a pull request. OpenCV developers will
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[GitHub](https://github.com/opencv/opencv) and submitting a pull request. OpenCV developers will
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check your pull request, give you important feedback and (once it passes the approval of the
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reviewer) it will be merged into OpenCV. You will then become an open source contributor :-)
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‎doc/py_tutorials/py_setup/py_setup_in_fedora/py_setup_in_fedora.markdown

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choose this. It always keeps your OpenCV up-to-date). For that, you need to install **Git** first.
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@code{.sh}
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yum install git
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git clone https://github.com/Itseez/opencv.git
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git clone https://github.com/opencv/opencv.git
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@endcode
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It will create a folder OpenCV in home directory (or the directory you specify). The cloning may
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take some time depending upon your internet connection.

‎doc/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.markdown

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-# Download OpenCV source. It can be from
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[Sourceforge](http://sourceforge.net/projects/opencvlibrary/) (for official release version) or
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from [Github](https://github.com/Itseez/opencv) (for latest source).
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from [Github](https://github.com/opencv/opencv) (for latest source).
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-# Extract it to a folder, opencv and create a new folder build in it.
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-# Open CMake-gui (*Start \> All Programs \> CMake-gui*)
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-# Fill the fields as follows (see the image below):

‎doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown

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You may also find the source code in the `samples/cpp/tutorial_code/calib3d/camera_calibration/`
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folder of the OpenCV source library or [download it from here
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](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). The program has a
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](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). The program has a
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single argument: the name of its configuration file. If none is given then it will try to open the
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one named "default.xml". [Here's a sample configuration file
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](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
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](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
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configuration file you may choose to use camera as an input, a video file or an image list. If you
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opt for the last one, you will need to create a configuration file where you enumerate the images to
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use. Here's [an example of this ](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
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use. Here's [an example of this ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
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The important part to remember is that the images need to be specified using the absolute path or
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the relative one from your application's working directory. You may find all this in the samples
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directory mentioned above.

‎doc/tutorials/calib3d/interactive_calibration/interactive_calibration.markdown

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- *camera_resolution*: resolution of camera which is used for calibration
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**Note:** *charuco_dict*, *charuco_square_lenght* and *charuco_marker_size* are used for chAruco pattern generation
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(see Aruco module description for details: [Aruco tutorials](https://github.com/Itseez/opencv_contrib/tree/master/modules/aruco/tutorials))
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(see Aruco module description for details: [Aruco tutorials](https://github.com/opencv/opencv_contrib/tree/master/modules/aruco/tutorials))
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Default chAruco pattern:
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‎doc/tutorials/core/basic_geometric_drawing/basic_geometric_drawing.markdown

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----
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- This code is in your OpenCV sample folder. Otherwise you can grab it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp)
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Explanation
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-----------

‎doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.markdown

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-----------
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You can [download this from here
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](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
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](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
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find it in the
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`samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp` of the
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OpenCV source code library.
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example, let us find out if a text is horizontal or not? Looking at some text you'll notice that the
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text lines sort of form also horizontal lines and the letters form sort of vertical lines. These two
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main components of a text snippet may be also seen in case of the Fourier transform. Let us use
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[this horizontal ](https://github.com/Itseez/opencv/tree/master/samples/data/imageTextN.png) and [this rotated](https://github.com/Itseez/opencv/tree/master/samples/data/imageTextR.png)
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[this horizontal ](https://github.com/opencv/opencv/tree/master/samples/data/imageTextN.png) and [this rotated](https://github.com/opencv/opencv/tree/master/samples/data/imageTextR.png)
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image about a text.
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In case of the horizontal text:

‎doc/tutorials/core/file_input_output_with_xml_yml/file_input_output_with_xml_yml.markdown

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-----------
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You can [download this from here
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](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
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](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
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`samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp` of the OpenCV source code
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library.
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‎doc/tutorials/core/how_to_scan_images/how_to_scan_images.markdown

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will make the scanning for each image using all of these methods, and print out how long it took.
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You can download the full source code [here
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](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
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](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
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the samples directory of OpenCV at the cpp tutorial code for the core section. Its basic usage is:
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@code{.bash}
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how_to_scan_images imageName.jpg intValueToReduce [G]

‎doc/tutorials/core/how_to_use_ippa_conversion/how_to_use_ippa_conversion.markdown

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You may also find the source code in the
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`samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp` file of the OpenCV source library or
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download it from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp).
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download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp).
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@include cpp/tutorial_code/core/ippasync/ippasync_sample.cpp
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‎doc/tutorials/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.markdown

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A case study
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------------
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Now that you have the basics done [here's](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
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Now that you have the basics done [here's](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
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an example that mixes the usage of the C interface with the C++ one. You will also find it in the
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sample directory of the OpenCV source code library at the
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`samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp` .
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You may observe a runtime instance of this on the [YouTube
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here](https://www.youtube.com/watch?v=qckm-zvo31w) and you can [download the source code from here
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](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
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](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
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or find it in the
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`samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp`
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of the OpenCV source code library.

‎doc/tutorials/core/mat-mask-operations/mat_mask_operations.markdown

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![](images/resultMatMaskFilter2D.png)
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You can download this source code from [here
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](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
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](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
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OpenCV source code libraries sample directory at
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`samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp`.
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‎doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.markdown

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![](images/MatBasicContainerOut15.png)
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Most of the samples here have been included in a small console application. You can download it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
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or in the core section of the cpp samples.
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You can also find a quick video demonstration of this on

‎doc/tutorials/features2d/trackingmotion/corner_subpixeles/corner_subpixeles.markdown

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----
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
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@code{.cpp}
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"

‎doc/tutorials/features2d/trackingmotion/generic_corner_detector/generic_corner_detector.markdown

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----
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)
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@include cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp
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‎doc/tutorials/features2d/trackingmotion/good_features_to_track/good_features_to_track.markdown

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----
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
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@code{.cpp}
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"

‎doc/tutorials/features2d/trackingmotion/harris_detector/harris_detector.markdown

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----
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
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@code{.cpp}
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"

‎doc/tutorials/gpu/gpu-basics-similarity/gpu_basics_similarity.markdown

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You may also find the source code and these video file in the
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`samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity` folder of the OpenCV
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source library or download it from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
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source library or download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
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The full source code is quite long (due to the controlling of the application via the command line
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arguments and performance measurement). Therefore, to avoid cluttering up these sections with those
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you'll find here only the functions itself.

‎doc/tutorials/imgproc/erosion_dilatation/erosion_dilatation.markdown

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----
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
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@include samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp
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Explanation

‎doc/tutorials/imgproc/gausian_median_blur_bilateral_filter/gausian_median_blur_bilateral_filter.markdown

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- Applies 4 different kinds of filters (explained in Theory) and show the filtered images
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sequentially
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- **Downloadable code**: Click
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Smoothing.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Smoothing.cpp)
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- **Code at glance:**
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@code{.cpp}
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#include "opencv2/imgproc.hpp"

‎doc/tutorials/imgproc/histograms/back_projection/back_projection.markdown

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- **Downloadable code**:
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-# Click
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
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for the basic version (explained in this tutorial).
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-# For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
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skin area) you can check the [improved
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demo](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
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demo](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
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-# ...or you can always check out the classical
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[camshiftdemo](https://github.com/Itseez/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
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[camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
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in samples.
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- **Code at glance:**

‎doc/tutorials/imgproc/histograms/histogram_calculation/histogram_calculation.markdown

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@@ -66,7 +66,7 @@ Code
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- Calculate the Histogram of each 1-channel plane by calling the function @ref cv::calcHist
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- Plot the three histograms in a window
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- **Downloadable code**: Click
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp)
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- **Code at glance:**
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@include samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp
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‎doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.markdown

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histogram of the lower half base image and with the same base image histogram.
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- Display the numerical matching parameters obtained.
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- **Downloadable code**: Click
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp)
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- **Code at glance:**
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@include cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp

‎doc/tutorials/imgproc/histograms/histogram_equalization/histogram_equalization.markdown

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- Equalize the Histogram by using the OpenCV function @ref cv::equalizeHist
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- Display the source and equalized images in a window.
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- **Downloadable code**: Click
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp)
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- **Code at glance:**
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@include samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp
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‎doc/tutorials/imgproc/histograms/template_matching/template_matching.markdown

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- Localize the location with higher matching probability
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- Draw a rectangle around the area corresponding to the highest match
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- **Downloadable code**: Click
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp)
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp)
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- **Code at glance:**
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@include samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp
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