vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

modules/xstereo/tutorials/qds_export_parameters/qds_export_parameters.markdown

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+Exporting a template parameter file {#tutorial_qds_export_parameters}
+==================
+
+Goal
+----
+
+In this tutorial you will learn how to
+
+-   create a simple parameter file template.
+
+@include ./samples/export_param_file.cpp
+
+## Explanation:
+
+The class supports loading configuration parameters from a .yaml file using the method `loadParameters()`.
+This is very useful for fine-tuning the class' parameters on the fly. To extract a template of this
+parameter file you run the following code.
+
+We create an instance of a `QuasiDenseStereo` object. Not specifying the second argument of the constructor,
+makes the object to load default parameters.
+@snippet ./samples/export_param_file.cpp create
+By calling the method `saveParameters()`, we store the template file to the location specified by `parameterFileLocation`
+@snippet ./samples/export_param_file.cpp write

modules/xstereo/tutorials/qds_quasi_dense_stereo/qds_quasi_dense_stereo.markdown

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+Quasi dense Stereo {#tutorial_qds_quasi_dense_stereo}
+==================
+
+Goal
+----
+
+In this tutorial you will learn how to
+
+-   Configure a QuasiDenseStero object
+-   Compute dense Stereo correspondences.
+
+@include ./samples/dense_disparity.cpp
+
+## Explanation:
+
+The program loads a stereo image pair.
+
+After importing the images.
+@snippet ./samples/dense_disparity.cpp load
+We need to know the frame size of a single image, in order to create an instance of a `QuasiDesnseStereo` object.
+
+@snippet ./samples/dense_disparity.cpp create
+
+Because we didn't specify the second argument in the constructor, the `QuasiDesnseStereo` object will
+load default parameters.
+
+We can then pass the imported stereo images in the process method like this
+@snippet ./samples/dense_disparity.cpp process
+
+The process method contains most of the functionality of the class and does two main things.
+-   Computes a sparse stereo based in "Good Features to Track" and "pyramidal Lucas-Kanade" flow algorithm
+-   Based on those sparse stereo points, densifies the stereo correspondences using Quasi Dense Stereo method.
+
+After the execution of `process()` we can display the disparity Image of the stereo.
+@snippet ./samples/dense_disparity.cpp disp
+
+
+At this point we can also extract all the corresponding points using `getDenseMatches()` method and export them in a file.
+@snippet ./samples/dense_disparity.cpp export

modules/xstereo/tutorials/table_of_content_quasi_dense_stereo.markdown

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+Quasi Dense Stereo (stereo module) {#tutorial_table_of_content_quasi_dense_stereo}
+==========================================================
+
+Quasi Dense Stereo is method for performing dense stereo matching. `QuasiDenseStereo` implements this process.
+The code uses pyramidal Lucas-Kanade with Shi-Tomasi features to get the initial seed correspondences.
+Then these seeds are propagated by using mentioned growing scheme.
+
+-   @subpage tutorial_qds_quasi_dense_stereo
+
+    Example showing how to get dense correspondences from a stereo image pair.
+
+-   @subpage tutorial_qds_export_parameters
+
+    Example showing how to genereate a parameter file template.