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116 lines
4.0 KiB
Markdown
116 lines
4.0 KiB
Markdown
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High level stitching API (Stitcher class) {#tutorial_stitcher}
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=========================================
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Goal
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----
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In this tutorial you will learn how to:
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- use the high-level stitching API for stitching provided by
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- @ref cv::Stitcher
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- learn how to use preconfigured Stitcher configurations to stitch images
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using different camera models.
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Code
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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/opencv/opencv/tree/master/samples/cpp/samples/cpp/stitching.cpp).
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@include samples/cpp/stitching.cpp
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Explanation
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-----------
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The most important code part is:
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@code{.cpp}
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Mat pano;
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Ptr<Stitcher> stitcher = Stitcher::create(mode, try_use_gpu);
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Stitcher::Status status = stitcher->stitch(imgs, pano);
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if (status != Stitcher::OK)
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{
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cout << "Can't stitch images, error code = " << int(status) << endl;
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return -1;
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}
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@endcode
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A new instance of stitcher is created and the @ref cv::Stitcher::stitch will
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do all the hard work.
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@ref cv::Stitcher::create can create stitcher in one of the predefined
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configurations (argument `mode`). See @ref cv::Stitcher::Mode for details. These
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configurations will setup multiple stitcher properties to operate in one of
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predefined scenarios. After you create stitcher in one of predefined
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configurations you can adjust stitching by setting any of the stitcher
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properties.
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If you have cuda device @ref cv::Stitcher can be configured to offload certain
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operations to GPU. If you prefer this configuration set `try_use_gpu` to true.
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OpenCL acceleration will be used transparently based on global OpenCV settings
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regardless of this flag.
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Stitching might fail for several reasons, you should always check if
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everything went good and resulting pano is stored in `pano`. See
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@ref cv::Stitcher::Status documentation for possible error codes.
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Camera models
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-------------
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There are currently 2 camera models implemented in stitching pipeline.
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- _Homography model_ expecting perspective transformations between images
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implemented in @ref cv::detail::BestOf2NearestMatcher cv::detail::HomographyBasedEstimator
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cv::detail::BundleAdjusterReproj cv::detail::BundleAdjusterRay
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- _Affine model_ expecting affine transformation with 6 DOF or 4 DOF implemented in
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@ref cv::detail::AffineBestOf2NearestMatcher cv::detail::AffineBasedEstimator
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cv::detail::BundleAdjusterAffine cv::detail::BundleAdjusterAffinePartial cv::AffineWarper
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Homography model is useful for creating photo panoramas captured by camera,
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while affine-based model can be used to stitch scans and object captured by
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specialized devices.
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@note
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Certain detailed settings of @ref cv::Stitcher might not make sense. Especially
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you should not mix classes implementing affine model and classes implementing
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Homography model, as they work with different transformations.
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Try it out
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----------
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If you enabled building samples you can found binary under
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`build/bin/cpp-example-stitching`. This example is a console application, run it without
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arguments to see help. `opencv_extra` provides some sample data for testing all available
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configurations.
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to try panorama mode run:
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```
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./cpp-example-stitching --mode panorama <path to opencv_extra>/testdata/stitching/boat*
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```
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to try scans mode run (dataset from home-grade scanner):
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```
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./cpp-example-stitching --mode scans <path to opencv_extra>/testdata/stitching/newspaper*
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```
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or (dataset from professional book scanner):
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```
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./cpp-example-stitching --mode scans <path to opencv_extra>/testdata/stitching/budapest*
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```
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@note
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Examples above expects POSIX platform, on windows you have to provide all files names explicitly
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(e.g. `boat1.jpg` `boat2.jpg`...) as windows command line does not support `*` expansion.
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See also
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--------
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If you want to study internals of the stitching pipeline or you want to experiment with detailed
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configuration see
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[stitching_detailed.cpp](https://github.com/opencv/opencv/tree/master/samples/cpp/stitching_detailed.cpp)
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in `opencv/samples/cpp` folder.
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