Add next and previous navigation links to all tutorials

2026-07-30 07:43:03 +04:00 · 2020-05-19 18:59:28 -04:00
parent d991c22090
commit 94d187e269
67 changed files with 207 additions and 0 deletions
@@ -1,6 +1,10 @@
 OpenCV4Android SDK {#tutorial_O4A_SDK}
 ==================

+@prev_tutorial{tutorial_android_dev_intro}
+@next_tutorial{tutorial_dev_with_OCV_on_Android}
+
+
 This tutorial was designed to help you with installation and configuration of OpenCV4Android SDK.

 This guide was written with MS Windows 7 in mind, though it should work with GNU Linux and Apple Mac
@@ -1,6 +1,10 @@
 Introduction into Android Development {#tutorial_android_dev_intro}
 =====================================

+@prev_tutorial{tutorial_clojure_dev_intro}
+@next_tutorial{tutorial_O4A_SDK}
+
+
 This guide was designed to help you in learning Android development basics and setting up your
 working environment quickly. It was written with Windows 7 in mind, though it would work with Linux
 (Ubuntu), Mac OS X and any other OS supported by Android SDK.
@@ -1,6 +1,10 @@
 Use OpenCL in Android camera preview based CV application {#tutorial_android_ocl_intro}
 =====================================

+@prev_tutorial{tutorial_dev_with_OCV_on_Android}
+@next_tutorial{tutorial_macos_install}
+
+
 This guide was designed to help you in use of [OpenCL &trade;](https://www.khronos.org/opencl/) in Android camera preview based CV application.
 It was written for [Eclipse-based ADT tools](http://developer.android.com/tools/help/adt.html)
 (deprecated by Google now), but it easily can be reproduced with [Android Studio](http://developer.android.com/tools/studio/index.html).
@@ -1,6 +1,10 @@
 Android Development with OpenCV {#tutorial_dev_with_OCV_on_Android}
 ===============================

+@prev_tutorial{tutorial_O4A_SDK}
+@next_tutorial{tutorial_android_ocl_intro}
+
+
 This tutorial has been created to help you use OpenCV library within your Android project.

 This guide was written with Windows 7 in mind, though it should work with any other OS supported by
@@ -1,6 +1,10 @@
 Building OpenCV for Tegra with CUDA {#tutorial_building_tegra_cuda}
 ===================================

+@prev_tutorial{tutorial_arm_crosscompile_with_cmake}
+@next_tutorial{tutorial_display_image}
+
+
@tableofcontents

 OpenCV with CUDA for Tegra
@@ -1,6 +1,10 @@
 Introduction to OpenCV Development with Clojure {#tutorial_clojure_dev_intro}
 ===============================================

+@prev_tutorial{tutorial_java_eclipse}
+@next_tutorial{tutorial_android_dev_intro}
+
+
 As of OpenCV 2.4.4, OpenCV supports desktop Java development using nearly the same interface as for
 Android development.

@@ -1,6 +1,9 @@
 Cross referencing OpenCV from other Doxygen projects {#tutorial_cross_referencing}
 ====================================================

+@prev_tutorial{tutorial_transition_guide}
+
+
 Cross referencing OpenCV
 ------------------------

@@ -1,6 +1,10 @@
 Cross compilation for ARM based Linux systems {#tutorial_arm_crosscompile_with_cmake}
 =============================================

+@prev_tutorial{tutorial_ios_install}
+@next_tutorial{tutorial_building_tegra_cuda}
+
+
 This steps are tested on Ubuntu Linux 12.04, but should work for other Linux distributions. I case
 of other distributions package names and names of cross compilation tools may differ. There are
 several popular EABI versions that are used on ARM platform. This tutorial is written for *gnueabi*
@@ -1,6 +1,10 @@
 Introduction to Java Development {#tutorial_java_dev_intro}
 ================================

+@prev_tutorial{tutorial_windows_visual_studio_image_watch}
+@next_tutorial{tutorial_java_eclipse}
+
+
 As of OpenCV 2.4.4, OpenCV supports desktop Java development using nearly the same interface as for
 Android development. This guide will help you to create your first Java (or Scala) application using
 OpenCV. We will use either [Apache Ant](http://ant.apache.org/) or [Simple Build Tool
@@ -1,6 +1,9 @@
 Getting Started with Images {#tutorial_display_image}
 ===========================

+@prev_tutorial{tutorial_building_tegra_cuda}
+@next_tutorial{tutorial_documentation}
+
 Goal
 ----

@@ -1,6 +1,10 @@
 Writing documentation for OpenCV {#tutorial_documentation}
 ================================

+@prev_tutorial{tutorial_display_image}
+@next_tutorial{tutorial_transition_guide}
+
+
@tableofcontents

 Doxygen overview {#tutorial_documentation_overview}
@@ -1,6 +1,9 @@
 Installation in iOS {#tutorial_ios_install}
 ===================

+@prev_tutorial{tutorial_macos_install}
+@next_tutorial{tutorial_arm_crosscompile_with_cmake}
+
 Required Packages
 -----------------

@@ -1,6 +1,10 @@
 Using OpenCV Java with Eclipse {#tutorial_java_eclipse}
 ==============================

+@prev_tutorial{tutorial_java_dev_intro}
+@next_tutorial{tutorial_clojure_dev_intro}
+
+
 Since version 2.4.4 [OpenCV supports Java](http://opencv.org/opencv-java-api.html). In this tutorial
 I will explain how to setup development environment for using OpenCV Java with Eclipse in
 **Windows**, so you can enjoy the benefits of garbage collected, very refactorable (rename variable,
@@ -1,6 +1,9 @@
 Using OpenCV with Eclipse (plugin CDT) {#tutorial_linux_eclipse}
 ======================================

+@prev_tutorial{tutorial_linux_gcc_cmake}
+@next_tutorial{tutorial_windows_install}
+
 Prerequisites
 -------------
 Two ways, one by forming a project directly, and another by CMake Prerequisites
@@ -1,6 +1,10 @@
 Using OpenCV with gcc and CMake {#tutorial_linux_gcc_cmake}
 ===============================

+@prev_tutorial{tutorial_linux_install}
+@next_tutorial{tutorial_linux_eclipse}
+
+
@note We assume that you have successfully installed OpenCV in your workstation.

 -   The easiest way of using OpenCV in your code is to use [CMake](http://www.cmake.org/). A few
@@ -1,6 +1,9 @@
 Installation in Linux {#tutorial_linux_install}
 =====================

+@next_tutorial{tutorial_linux_gcc_cmake}
+
+
 The following steps have been tested for Ubuntu 10.04 but should work with other distros as well.

 Required Packages
@@ -1,6 +1,10 @@
 Installation in MacOS {#tutorial_macos_install}
 =====================

+@prev_tutorial{tutorial_android_ocl_intro}
+@next_tutorial{tutorial_ios_install}
+
+
 The following steps have been tested for MacOSX (Mavericks) but should work with other versions as well.

 Required Packages
@@ -1,6 +1,10 @@
 Transition guide {#tutorial_transition_guide}
 ================

+@prev_tutorial{tutorial_documentation}
+@next_tutorial{tutorial_cross_referencing}
+
+
@tableofcontents

 Changes overview {#tutorial_transition_overview}
@@ -1,6 +1,10 @@
 Installation in Windows {#tutorial_windows_install}
 =======================

+@prev_tutorial{tutorial_linux_eclipse}
+@next_tutorial{tutorial_windows_visual_studio_opencv}
+
+
 The description here was tested on Windows 7 SP1. Nevertheless, it should also work on any other
 relatively modern version of Windows OS. If you encounter errors after following the steps described
 below, feel free to contact us via our [OpenCV Q&A forum](http://answers.opencv.org). We'll do our
@@ -1,6 +1,10 @@
 Image Watch: viewing in-memory images in the Visual Studio debugger {#tutorial_windows_visual_studio_image_watch}
 ===================================================================

+@prev_tutorial{tutorial_windows_visual_studio_opencv}
+@next_tutorial{tutorial_java_dev_intro}
+
+
 Image Watch is a plug-in for Microsoft Visual Studio that lets you to visualize in-memory images
 (*cv::Mat* or *IplImage_* objects, for example) while debugging an application. This can be helpful
 for tracking down bugs, or for simply understanding what a given piece of code is doing.
@@ -1,6 +1,10 @@
 How to build applications with OpenCV inside the "Microsoft Visual Studio" {#tutorial_windows_visual_studio_opencv}
 ==========================================================================

+@prev_tutorial{tutorial_windows_install}
+@next_tutorial{tutorial_windows_visual_studio_image_watch}
+
+
 Everything I describe here will apply to the `C\C++` interface of OpenCV. I start out from the
 assumption that you have read and completed with success the @ref tutorial_windows_install tutorial.
 Therefore, before you go any further make sure you have an OpenCV directory that contains the OpenCV