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An overview of the opencv_contrib modules
-----------------------------------------
This list gives an overview of all modules available inside the contrib repository.
To turn off building one of these module repositories, set the names in bold below to <reponame>
```
$ cmake -D OPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules -D BUILD_opencv_<reponame>=OFF <opencv_source_directory>
```
- **alphamat**: Computer Vision based Alpha Matting -- Given an input image and a trimap, generate an alpha matte.
- **aruco**: ArUco and ChArUco Markers -- Augmented reality ArUco marker and "ChARUco" markers where ArUco markers embedded inside the white areas of the checker board.
- **bgsegm**: Background segmentation algorithm combining statistical background image estimation and per-pixel Bayesian segmentation.
- **bioinspired**: Biological Vision -- Biologically inspired vision model: minimize noise and luminance variance, transient event segmentation, high dynamic range tone mapping methods.
- **ccalib**: Custom Calibration -- Patterns for 3D reconstruction, omnidirectional camera calibration, random pattern calibration and multi-camera calibration.
- **cnn_3dobj**: Deep Object Recognition and Pose -- Uses Caffe Deep Neural Net library to build, train and test a CNN model of visual object recognition and pose.
- **cvv**: Computer Vision Debugger -- Simple code that you can add to your program that pops up a GUI allowing you to interactively and visually debug computer vision programs.
- **datasets**: Datasets Reader -- Code for reading existing computer vision databases and samples of using the readers to train, test and run using that dataset's data.
- **dnn_objdetect**: Object Detection using CNNs -- Implements compact CNN Model for object detection. Trained using Caffe but uses opencv_dnn module.
- **dnn_superres**: Superresolution using CNNs -- Contains four trained convolutional neural networks to upscale images.
- **dnns_easily_fooled**: Subvert DNNs -- This code can use the activations in a network to fool the networks into recognizing something else.
- **dpm**: Deformable Part Model -- Felzenszwalb's Cascade with deformable parts object recognition code.
- **face**: Face Recognition -- Face recognition techniques: Eigen, Fisher and Local Binary Pattern Histograms LBPH methods.
- **freetype**: Drawing text using freetype and harfbuzz.
- **fuzzy**: Fuzzy Logic in Vision -- Fuzzy logic image transform and inverse; Fuzzy image processing.
- **hdf**: Hierarchical Data Storage -- This module contains I/O routines for Hierarchical Data Format: https://en.m.wikipedia.org/wiki/Hierarchical_Data_Format meant to store large amounts of data.
- **julia**: Julia language wrappers with samples and tests.
- **line_descriptor**: Line Segment Extract and Match -- Methods of extracting, describing and latching line segments using binary descriptors.
- **matlab**: Matlab Interface -- OpenCV Matlab Mex wrapper code generator for certain opencv core modules.
- **mcc**: Macbeth Color Chart detector -- Find and return color patch location in MacBeth color calibration charts.
- **optflow**: Optical Flow -- Algorithms for running and evaluating deepflow, simpleflow, sparsetodenseflow and motion templates (silhouette flow).
- **ovis**: OGRE 3D Visualiser -- allows you to render 3D data using the OGRE 3D engine.
- **plot**: Plotting -- The plot module allows you to easily plot data in 1D or 2D.
- **reg**: Image Registration -- Pixels based image registration for precise alignment. Follows the paper "Image Alignment and Stitching: A Tutorial", by Richard Szeliski.
- **rgbd**: RGB-Depth Processing module -- Linemod 3D object recognition; Fast surface normals and 3D plane finding. 3D visual odometry. 3d reconstruction using KinectFusion.
- **saliency**: Saliency API -- Where humans would look in a scene. Has routines for static, motion and "objectness" saliency.
- **sfm**: Structure from Motion -- This module contains algorithms to perform 3d reconstruction from 2d images. The core of the module is a light version of Libmv.
- **stereo**: Stereo Correspondence -- Stereo matching done with different descriptors: Census / CS-Census / MCT / BRIEF / MV and dense stereo correspondence using Quasi Dense Stereo method.
- **structured_light**: Structured Light Use -- How to generate and project gray code patterns and use them to find dense depth in a scene.
- **surface_matching**: Point Pair Features -- Implements 3d object detection and localization using multimodal point pair features.
- **text**: Visual Text Matching -- In a visual scene, detect text, segment words and recognise the text.
- **tracking**: Vision Based Object Tracking -- Use and/or evaluate one of 5 different visual object tracking techniques.
- **xfeatures2d**: Features2D extra -- Extra 2D Features Framework containing experimental and non-free 2D feature detector/descriptor algorithms. SURF, BRIEF, Censure, Freak, LUCID, Daisy, Self-similar.
- **ximgproc**: Extended Image Processing -- Structured Forests / Domain Transform Filter / Guided Filter / Adaptive Manifold Filter / Joint Bilateral Filter / Superpixels / Ridge Detection Filter.
- **xobjdetect**: Boosted 2D Object Detection -- Uses a Waldboost cascade and local binary patterns computed as integral features for 2D object detection.
- **xphoto**: Extra Computational Photography -- Additional photo processing algorithms: Color balance / Denoising / Inpainting.
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