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 ``` $ cmake -D OPENCV_EXTRA_MODULES_PATH=/modules -D BUILD_opencv_=OFF ``` - **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. - **hfs**: Hierarchical Feature Selection for Efficient Image Segmentation -- This module contains an efficient algorithm to segment an image. - **img_hash**: This module contains algorithms to extract hash of an image allowing to efficiently estimate similarity between images. - **intensity_transform**: The module brings implementations of intensity transformation algorithms to adjust image contrast. - **julia**: Julia language wrappers with samples and tests. - **line_descriptor**: Line Segment Extract and Match -- Methods of extracting, describing and matching 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. - **phase_unwrapping**: Quality-guided phase unwrapping. - **plot**: Plotting -- The plot module allows you to easily plot data in 1D or 2D. - **quality**: Image Quality Analysis (IQA) API. - **rapid**: Silhouette based 3D object tracking. - **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. - **signal**: Signal processing algorithms - **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. - **shape**: Shape Distance and Matching - **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. - **superres**: Super Resolution - **surface_matching**: Point Pair Features -- Implements 3d object detection and localization using multimodal point pair features. - **text**: Scene Text Detection and Recognition -- This module contains algorithms to perform text detection, words segmentation and text recognition in a visual scene. - **tracking**: Vision Based Object Tracking -- Use and/or evaluate different visual object tracking techniques. - **videostab**: Video Stabilization - **viz**: 3D Visualizer - **wechat_qrcode**: WeChat QR code detector for detecting and parsing QR code. - **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.