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Installing and Updating Cygwin for 64-bit versions of Windows
Run setup-x86_64.exe any time you want to update orinstall a Cygwin package for 64-bit windows. The signature for setup-x86_64.exe can be used to verify the validity ofthis binary.
CMake, the cross-platform, open-source build system. CMake is a family of tools designed to build, test and package software. CMake is used to control the software compilation process using simple platform and compiler independent configuration files.
Take a look at the CMake Fortran modules paper for the gory details. From a build system's point of view, Fortran's modules behave very similar to the C20 modules. Update: CMake 3.20 introduces experimental support for Modules with the Ninja Generator (and only for Ninja). Details can be found in the respective pull request. CMake-tutorial这份渐进式的教程涵盖了 CMake 帮助处理的一些常见的构建问题。许多议题已经在《Mastering CMake》中作为独立的话题介绍过，但是了解它们是如何在示例项目中结合在一起的将非常有帮助。 你可以在 CMake 源码中的 Tests/Tutorial 文件夹找到这份教程，每一步的内容都放置在各自的子文. Installing and Updating Cygwin Packages Installing and Updating Cygwin for 64-bit versions of Windows. Run setup-x8664.exe any time you want to update or install a Cygwin package for 64-bit windows. CMake is a tool for defining and managing code builds, primarily for C. CMake is a cross-platform tool; the idea is to have a single definition of how the project is built - which translates into specific build definitions for any supported platform.
Installing and Updating Cygwin for 32-bit versions of Windows
Run setup-x86.exe any time you want to update orinstall a Cygwin package for 32-bit windows. The signature for setup-x86.exe can be used to verify the validity ofthis binary.
Signing key transition
The key used to sign setup binaries has been updated. During the transitionperiod, signatures are made using both old (676041BA) and new (1A698DE9E2E56300)public keys here.See thismail for more details.In General You Can Detect And Specify Variables For Several Operating Systems Like That: Detect Microsoft Windows If(WIN32) # For Windows Opera...
General installation notes
When installing packages for the first time, the setup programdoes not install every package. Only the minimal base packagesfrom the Cygwin distribution are installed by default, which takes up about 100 MB.
Clicking on categories and packages in the setup program package installationscreen allows you to select what is installed or updated.
Individual packages like bash, gcc, less, etc.are released independently of the Cygwin DLL, so the Cygwin DLL version is notuseful as a general Cygwin release number. The setup programtracks the versions of all installed components and provides the mechanismfor installing or updating everything available from this site forCygwin.
Once you've installed your desired subset of the Cygwin distribution,the setup program will remember what you selected, so re-running itwill update your system with any new package releases.
On Windows Vista and later, the setup program will check bydefault if it runs with administrative privileges and, if not, will tryto elevate the process. If you want to avoid this behaviour and installunder an unprivileged account just for your own usage, runsetup with the --no-admin option.
Q: How do I add a package to my existing Cygwin installation?
A: Run the setup program and select the package you want to add.
Tip: if you don't want to also upgrade existing packages, select 'Keep' at thetop-right of the package chooser page.
Q: Is there a command-line installer?
A: Yes and no. The setup program understandscommand-linearguments which allow you to control its behavior and chooseindividual packages to install. While this provides some functionalitysimilar to such tools as apt-get or yum it is not asfull-featured as those package managers.
Q: Why not use apt, yum, myfavourite package manager, etc.?
A: The basic reason for not using a more full-featured package manager is thatsuch a program would need full access to all of Cygwin's POSIX functionality. Thatis, however, difficult to provide in a Cygwin-free environment, such as exists onfirst installation. Additionally, Windows does not easily allow overwriting ofin-use executables so installing a new version of the Cygwin DLL while a packagemanager is using the DLL is problematic.
Q: How do I install everything?
A: You do not want to do this! This will install an enormous number of packagesthat you will never use, including debuginfo and source for every package.
If you really must do this, clicking on the 'Default' label next to the'All' category to change it to 'Install' will mark every Cygwin package forinstallation. Be advised that this will download and install tens of gigabytesof files to your computer.
Q: How do I verify the signature of setup?
TUTORIAL 03 Using CMake.js Based Native Modules With NW.js
A: e.g.
Q: What's the hash of setup?
A: See here
Q: How do I help improve setup?
A: See the setupproject page for more information.
Motivation
Modern GPU accelerators has become powerful and featured enough to be capable to perform general purpose computations (GPGPU). It is a very fast growing area that generates a lot of interest from scientists, researchers and engineers that develop computationally intensive applications. Despite of difficulties reimplementing algorithms on GPU, many people are doing it to check on how fast they could be. To support such efforts, a lot of advanced languages and tool have been available such as CUDA, OpenCL, C++ AMP, debuggers, profilers and so on.
Significant part of Computer Vision is image processing, the area that graphics accelerators were originally designed for. Other parts also suppose massive parallel computations and often naturally map to GPU architectures. So it’s challenging but very rewarding to implement all these advantages and accelerate OpenCV on graphics processors.
History
OpenCV includes GPU module that contains all GPU accelerated stuff. Supported by NVIDIA the work on the module, started in 2010 prior to the first release in Spring of 2011. It includes accelerated code for siginifcant part of the library, still keeps growing and is being adapted for the new computing technologies and GPU architectures.
Goals
- Provide developers with a convenient computer vision framework on the GPU, maintain conceptual consistency with the current CPU functionality.
- Achieve the best performance with GPUs (efficient kernels tuned for modern architectures, optimized dataflow like async. execution, copy overlaps, zero-copy)
- Completeness (implement as much as possible, even if speed-up is not fantastic; such allows to run an algorithm entirely on GPU and save on coping overheads)
Gerhard Berger- Custom CMake Parameter Support, Silent And Out Parameters
Performance
Tesla C2050 versus Core i5-760 2.8Ghz, SSE, TBB
Design considerations
OpenCV GPU module is written using CUDA, therefore it benefits from the CUDA ecosystem. There is a large community, conferences, publications, many tools and libraries developed such as NVIDIA NPP, CUFFT, Thrust.
The GPU module is designed as host API extension. This design provides the user an explicit control on how data is moved between CPU and GPU memory. Although the user has to write some additional code to start using the GPU, this approach is both flexible and allows more efficient computations.
GPU modules includes class cv::gpu::GpuMat which is a primary container for data kept in GPU memory. It’s interface is very similar with cv::Mat, its CPU counterpart. All GPU functions receive GpuMat as input and output arguments. This allows to invoke several GPU algorithms without downloading data. GPU module API interface is also kept similar with CPU interface where possible. So developers who are familiar with Opencv on CPU could start using GPU straightaway.
Short sample
In the sample below an image is loaded from png0file, next it is uploaded to GPU, thresholded, downloaded and displayed.