Add next and previous navigation links to all tutorials

Author: dmallia17

doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown

@@ -1,6 +1,10 @@
 Camera calibration With OpenCV {#tutorial_camera_calibration}
 ==============================
 
+@prev_tutorial{tutorial_camera_calibration_square_chess}
+@next_tutorial{tutorial_real_time_pose}
+
+
 Cameras have been around for a long-long time. However, with the introduction of the cheap *pinhole*
 cameras in the late 20th century, they became a common occurrence in our everyday life.
 Unfortunately, this cheapness comes with its price: significant distortion. Luckily, these are

doc/tutorials/calib3d/camera_calibration_pattern/camera_calibration_pattern.markdown

@@ -1,6 +1,9 @@
 Create calibration pattern {#tutorial_camera_calibration_pattern}
 =========================================
 
+@next_tutorial{tutorial_camera_calibration_square_chess}
+
+
 The goal of this tutorial is to learn how to create calibration pattern.
 
 You can find a chessboard pattern in https://github.com/opencv/opencv/blob/3.4/doc/pattern.png

doc/tutorials/calib3d/camera_calibration_square_chess/camera_calibration_square_chess.markdown

@@ -1,6 +1,10 @@
 Camera calibration with square chessboard {#tutorial_camera_calibration_square_chess}
 =========================================
 
+@prev_tutorial{tutorial_camera_calibration_pattern}
+@next_tutorial{tutorial_camera_calibration}
+
+
 The goal of this tutorial is to learn how to calibrate a camera given a set of chessboard images.
 
 *Test data*: use images in your data/chess folder.

doc/tutorials/calib3d/interactive_calibration/interactive_calibration.markdown

@@ -1,6 +1,9 @@
 Interactive camera calibration application {#tutorial_interactive_calibration}
 ==============================
 
+@prev_tutorial{tutorial_real_time_pose}
+
+
 According to classical calibration technique user must collect all data first and when run @ref cv::calibrateCamera function
 to obtain camera parameters. If average re-projection error is huge or if estimated parameters seems to be wrong, process of
 selection or collecting data and starting of @ref cv::calibrateCamera repeats.

doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown

@@ -1,6 +1,10 @@
 Real Time pose estimation of a textured object {#tutorial_real_time_pose}
 ==============================================
 
+@prev_tutorial{tutorial_camera_calibration}
+@next_tutorial{tutorial_interactive_calibration}
+
+
 Nowadays, augmented reality is one of the top research topic in computer vision and robotics fields.
 The most elemental problem in augmented reality is the estimation of the camera pose respect of an
 object in the case of computer vision area to do later some 3D rendering or in the case of robotics

doc/tutorials/dnn/dnn_android/dnn_android.markdown

@@ -1,5 +1,8 @@
 # How to run deep networks on Android device {#tutorial_dnn_android}
 
+@prev_tutorial{tutorial_dnn_halide_scheduling}
+@next_tutorial{tutorial_dnn_yolo}
+
 ## Introduction
 In this tutorial you'll know how to run deep learning networks on Android device
 using OpenCV deep learning module.

doc/tutorials/dnn/dnn_custom_layers/dnn_custom_layers.md

@@ -1,5 +1,7 @@
 # Custom deep learning layers support {#tutorial_dnn_custom_layers}
 
+@prev_tutorial{tutorial_dnn_javascript}
+
 ## Introduction
 Deep learning is a fast growing area. The new approaches to build neural networks
 usually introduce new types of layers. They could be modifications of existing

doc/tutorials/dnn/dnn_googlenet/dnn_googlenet.markdown

@@ -1,6 +1,8 @@
 Load Caffe framework models  {#tutorial_dnn_googlenet}
 ===========================
 
+@next_tutorial{tutorial_dnn_halide}
+
 Introduction
 ------------
 

doc/tutorials/dnn/dnn_halide/dnn_halide.markdown

@@ -1,5 +1,8 @@
 # How to enable Halide backend for improve efficiency  {#tutorial_dnn_halide}
 
+@prev_tutorial{tutorial_dnn_googlenet}
+@next_tutorial{tutorial_dnn_halide_scheduling}
+
 ## Introduction
 This tutorial guidelines how to run your models in OpenCV deep learning module
 using Halide language backend. Halide is an open-source project that let us

doc/tutorials/dnn/dnn_halide_scheduling/dnn_halide_scheduling.markdown

@@ -1,5 +1,8 @@
 # How to schedule your network for Halide backend {#tutorial_dnn_halide_scheduling}
 
+@prev_tutorial{tutorial_dnn_halide}
+@next_tutorial{tutorial_dnn_android}
+
 ## Introduction
 Halide code is the same for every device we use. But for achieving the satisfied
 efficiency we should schedule computations properly. In this tutorial we describe