OpenCV  4.10.0-dev
Open Source Computer Vision
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Graph API (gapi module)

In this section you will learn about graph-based image processing and how G-API module can be used for that.

  • Face analytics pipeline with G-API

    Languages: C++

    Compatibility: > OpenCV 4.2

    Author: Dmitry Matveev

    This tutorial illustrates how to build a hybrid video processing pipeline with G-API where Deep Learning and image processing are combined effectively to maximize the overall throughput. This sample requires Intel® distribution of OpenVINO™ Toolkit version 2019R2 or later.

  • Porting anisotropic image segmentation on G-API

    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.

  • Implementing a face beautification algorithm with G-API

    Languages: C++

    Compatibility: > OpenCV 4.2

    Author: Orest Chura

    In this tutorial we build a complex hybrid Computer Vision/Deep Learning video processing pipeline with G-API.

  • Using DepthAI Hardware / OAK depth sensors

    Languages: C++

    Compatibility: > OpenCV 4.6

    Author: Alessandro de Oliveira Faria (A.K.A. CABELO)

    In this tutorial we showed how to use the Luxonis DepthAI library with G-API.