OpenCV3.0来啦
千呼万唤始出来，说了很久的Openvv3.0Alpha终于开放了。
上下载地址：
http://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.0.0-alpha/
这里翻译一下官网上的新闻，看看opencv3.0有哪些变化：（新闻地址：http://opencv.org/opencv-3-0-alpha.html）
废话略去：
1. Change in the project architecture. Since very beginning OpenCV was one solid project, built and shipped as a whole, and that was good strategy for many years. However, with constantly growing functionality, including bleeding-edge algorithms published a few minutes before a pull request has been submitted to our repository, and increasing number of contributors (thank you all very much, guys!) we came to the same conclusion and decision as many other big project – the solid model does not work anymore. Let’s use use the core + plugins architecture then!
项目结构的变化：原来OpenCV是一个整体的项目，但是随着越来越牛逼，就改成了core+plugins的结构。
In addition to our main repository and the additional “test data” repository, we are now glad to introduce http://github.com/itseez/opencv_contrib, where we put a lot of exciting functionality, including already known face recognition and text detection, but also text recognition, new-age edge detectors, state-of-art inpainting, depth maps processing, new optical flow and tracking algorithms etc.
除了原来的opencv仓库和测试数据的仓库，现在有了一个新的opencv_contrib的仓库（其实opencv_contrib在2.4.x里面也有，现在好像是分出来了的意思），在这个仓库里面，有很多有意思的功能，不仅仅有面部识别，文字检测，还有文字识别，new-age边缘检测，bla bla bla.
What’s common and what’s different between opencv and opencv_contrib?
- They are both served by our continuous integration system (note the combo-box on the top of the page), although unit tests for contrib are not regularly run yet.
- 都是一个娘生的。虽然单元测试还没开始。
- All or some of these extra modules can be built using our build system, pass OPENCV_EXTRA_MODULES_PATH=/modules to CMake.
- 这些extra module可以通过改cmake参数获得
- Documentation for contrib is automatically generated and is available at docs.opencv.org/master. It will be made better shaped and more organized by OpenCV 3.0 beta and final release.
- contrib的文档会自动生成在docs.opencv.org/master.
- The main opencv is Itseez-supported code, it will have very stable API and probably just a little innovation.
- 主要的opencv比较稳定，但是创新少
- opencv_contrib is the place where most of the experimental code is put, some parts may change API and it’s where you are welcome to contribute your new exciting algorithms.
- contrib里面有很多实验性的代码，有些地方会改变API，欢迎加入你的代码
2. Thanks to support from Intel and AMD companies, we made GPU acceleration of many vision algorithms very easily accessible to our users. The technology is nicknamed T-API (“transparent API”). A separate guide on this topic is being prepared, but you are welcome to take a look at and try out our t-api samples to see how it works.
狂拽坤吊炸天，这是要逆袭cuda的节奏吗！得到英特尔和AMD的支持，我们使得很多视觉算法的GPU加速很容易使用。这个技术成为T-API（透明API）。独立的文档正在准备，但是你可以看一下我们的t-api样例来看看他是怎么工作的。
3. Intel corporation gave us another exciting present. A subset of Intel Integrated Performance Primitives (IPP) is linked by default into OpenCV and is available at no charge for all our users. And that includes the license to redistribute applications that use IPP-accelerated OpenCV. As you may see, for quite a few image processing functions we achieved very noticeable speedup with IPP (where IPP is compared with OpenCV built with all possible optimizations turned on):
英特尔还给我们一个很大的礼物。IPP的一部分被默认连接在了opencv里，并且不要钱！并且包含了用IPP加速Opencv的license. 可以看到，很多图像处理的算法被加快了好多！（其实也没有那么多。。。，但是不要钱！）
4. Last but not least, OpenCV 3.0 brings a lot of new functionality, such as:
- Text detection and recognition by Lluis Gomez
- 文字检测和识别
- HDR by Fedor Morozov and Alexander Shishkov
- HDR
- KAZE/A-KAZE by Eugene Khvedchenya, the algorithm author Pablo Alcantarilla and some improvements by F. Morozov.
- KAZE/A-KAZE(不知道什么)
- Smart segmentation and edge-aware filters by Vitaly Lyudvichenko, Yuri Gitman, Alexander Shishkov and Alexander Mordvintsev
- 只能分割和边缘滤波？
- Car detection using Waldboost, ACF by Vlad Shakhuro and Nikita Manovich
- 车辆检测
- TLD tracker and several common-use optimization algorithms by Alex Leontiev
- TLD跟踪，和一些常用的最优化算法
- Matlab bindings by Hilton Bristow, with support from Mathworks.
- Matlab
- Greatly extended Python bindings, including Python 3 support, and several OpenCV+Python tutorials by Alexander Mordvintsev, Abid Rahman and others.
- Python
- 3D Visualization using VTK by Ozan Tonkal and Anatoly Baksheev.
- 3D可视化
- RGBD module by Vincent Rabaud
- RGBD模块
- Line Segment Detector by Daniel Angelov
- 线分割检测
- Many useful Computational Photography algorithms by Siddharth Kherada
- 很多计算摄影（？）算法
- Shape descriptors, matching and morphing shapes (shape module) by Juan Manuel Perez Rua and Ilya Lysenkov
- 形状描述子等等
- Long-term tracking + saliency-based improvements (tracking module) by Antonella Cascitelli and Francesco Puja
- 长时间跟踪加基于显著性的改进
- Another good pose estimation algorithm and the tutorial on pose estimation by Edgar Riba and Alexander Shishkov
- 另一个姿态估计算法
- Line descriptors and matchers by Biagio Montesano and Manuele Tambourin
- 线描述子和匹配器
- Myriads of improvements in various parts of the library by Steven Puttemans; thank you a lot, Steven!
- 不懂
- Several NEON optimizations by Adrian Stratulat, Cody Rigney, Alexander Petrikov, Yury Gorbachev and others.
- 不懂
- Fast foreach loop over cv::Mat by Kazuki Matsuda
- cv::Mat的更快的foreach loop
- Image alignment (ECC algorithm) by Georgios Evangelidis
- 不知道
- GDAL image support by Marvin Smith
- 不知道
- RGBD module by Vincent Rabaud
- ？
- Fisheye camera model by Ilya Krylov
- 鱼眼相机
- OSX framework build script by Eugene Khvedchenya
- OSX
- Multiple FLANN improvements by Pierre-Emmanuel Viel
- 不知道
- Improved WinRT support by Gregory Morse
- WinRT
- Latent SVM Cascade by Evgeniy Kozhinov and NNSU team (awaiting integration)
- 隐SVM
- Logistic regression by Rahul Kavi
- 逻辑回归
- Five-point pose estimation algorithm by Bo Li
- 五点姿态估计
This release would not be possible without big help from many people all over the world. Thanks to all the people who contributed code, submitted bug reports, patches, reviewed patches and helped us in any other ways. In particular, we would like to thank
Alexander Shishkov (who also maintains opencv.org site), Andrey Pavlenko, Alexander Alekhin, Alexander Smorkalov, Roman Donchenko, Kirill Kornyakov, Andrey Kamaev, Sergey Sivolgin, Vladimir Bystritsky, Sergey Nosov, Nikita Manovich, Evgeniy Talanin, Elena Gvozdeva, Alexander Karsakov, Konstantin Matskevich, Ilya Lavrenov, Anna Kogan, Ivan Korolev, Dinar Ahmatnurov, Andrey Senin, Vlad Vinogradov, Alexey Spizhevoy, Anatoly Baksheev, Marina Kolpakova, Daniil Osokin, Leonid Beynenson, Dmitry Retinsky, Maria Dimashova, Ilya Lysenkov, Andrey Morozov, Victor Eruhimov, Alexander Bovyrin, Sergey Molinov, Gary Bradski, Vincent Rabaud, Harris Gasparakis and many other people.
xxxxxx
The 3.0-alpha package can be downloaded in source form as .zip package directly from github:
https://github.com/Itseez/opencv/tree/3.0.0-alpha
in binary form, as self-extracting archive for Windows:
https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.0.0-alpha/
or an iOS framework:
https://sourceforge.net/projects/opencvlibrary/files/opencv-ios/3.0.0-alpha/
This is alpha, so expect some glitches, such as partially broken Python bindings, a few failing tests etc. Those items are in progress and also we appreciate your feedback very much.
OpenCV 3.0 beta is expected in middle of this fall and the OpenCV 3.0 final release should be ready by the Christmas/New Year holidays.
Best regards,
OpenCV Development Team.