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Open Source Computer Vision Library https://opencv.org/
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opencv/doc/tutorials/gapi/table_of_content_gapi.markdown

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Merge pull request #13030 from dmatveev:tutorial * G-API: First steps with tutorial * G-API Tutorial: First iteration * G-API port of anisotropic image segmentation tutorial; * Currently works via OpenCV only; * Some new kernels have been required. * G-API Tutorial: added chapters on execution code, inspection, and profiling * G-API Tutorial: make Fluid kernel headers public For some reason, these headers were not moved to the public headers subtree during the initial development. Somehow it even worked for the existing workloads. * G-API Tutorial: Fix a couple of issues found during the work * Introduced Phase & Sqrt kernels, OCV & Fluid versions * Extended GKernelPackage to allow kernel removal & policies on include() All the above stuff needs to be tested, tests will be added later * G-API Tutorial: added chapter on running Fluid backend * G-API Tutorial: fix a number of issues in the text * G-API Tutorial - some final updates - Fixed post-merge issues after Sobel kernel renaming; - Simplified G-API code a little bit; - Put a conclusion note in text. * G-API Tutorial - fix build issues in test/perf targets Public headers were refactored but tests suites were not updated in time * G-API Tutorial: Added tests & reference docs on new kernels * Phase * Sqrt * G-API Tutorial: added link to the tutorial from the main module doc * G-API Tutorial: Added tests on new GKernelPackage functionality * G-API Tutorial: Extended InRange tests to cover 32F * G-API Tutorial: Misc fixes * Avoid building examples when gapi module is not there * Added a volatile API disclaimer to G-API root documentation page * G-API Tutorial: Fix perf tests build issue This change came from master where Fluid kernels are still used incorrectly. * G-API Tutorial: Fixed channels support in Sqrt/Phase fluid kernels Extended tests to cover this case * G-API Tutorial: Fix text problems found on team review
6 years ago
# Graph API (gapi module) {#tutorial_table_of_content_gapi}
In this section you will learn about graph-based image processing and
how G-API module can be used for that.
- @subpage tutorial_gapi_anisotropic_segmentation
*Languages:* C++
*Compatibility:* \> OpenCV 4.0
*Author:* Dmitry Matveev
This is an end-to-end tutorial where an existing sample algorithm
is ported on G-API, covering the basic intuition behind this
transition process, and examining benefits which a graph model
brings there.