OpenCV 3.0 Gold which was released early last month, is the most functional and the fastest OpenCV ever. This release comes with over 1500 patches, opencv_contrib repository has been added. A lot of new functionality have been included in the release.
OpenCV 3.0 Gold changelog
- opencv_contrib (http://github.com/itseez/opencv_contrib) repository has been added. A lot of new functionality is there already! opencv_contrib is only compatible with 3.0/master, not 2.4.
- a subset of Intel IPP (IPPCV) is given to us and our users free of charge, free of licensing fees, for commercial and non-commerical use. It’s used by default in x86 and x64 builds on Windows, Linux and Mac.
- T-API (transparent API) has been introduced, this is transparent GPU acceleration layer using OpenCL. It does not add any compile-time or runtime dependency of OpenCL.
- ~40 OpenCV functions have been accelerated using NEON intrinsics and because these are mostly basic functions, some higher-level functions got accelerated as well.
- There is also new OpenCV HAL layer that will simplifies creation of NEON-optimized code and that should form a base for the open-source and proprietary OpenCV accelerators.
- Greatly improved and extended Python & Java bindings (also, see below on the Python bindings), newly introduced Matlab bindings (still in alpha stage).
- Improved Android support – now OpenCV Manager is in Java and supports both 2.4 and 3.0.
- Greatly improved WinRT support, including video capturing and multi-threading capabilities. Thanks for Microsoft team for this!
- Big thanks to Google who funded several successive GSoC programs and let OpenCV in. The results of many successful GSoC 2013 and 2014 projects have been integrated in opencv 3.0 and opencv_contrib (earlier results are also available in OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting, edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support, many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- See release note for more info
Install OpenCV 3.0 Gold on Ubuntu 14.04
sudo apt-get -y install libopencv-dev build-essential cmake git libgtk2.0-dev pkg-config python-dev python-numpy libdc1394-22 libdc1394-22-dev libjpeg-dev libpng12-dev libtiff4-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev libtbb-dev libqt4-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils unzip mkdir opencv cd opencv wget https://github.com/Itseez/opencv/archive/3.0.0.zip -O opencv-3.0.0.zip unzip opencv-3.0.0.zip cd opencv-3.0.0 mkdir build cd build cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D WITH_QT=ON -D WITH_OPENGL=ON .. make -j $(nproc) sudo make install sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf' sudo ldconfig