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The programmers are responsible for feature selection and updation of library. Package Manager is also responsible for taking care of library updation. The package manager will do the work on behalf of programmer. The programmers must have strong knowledge about packages present in the library because fast performance can be achieved through the fine selection of features during installation. This installation is well suited for beginners and those who want to complete their job at the earliest. The programmers are not expected to have knowledge about the library. Here, the programmer has all the rights to add or remove the features during the installation of library. The programmers can neither add nor remove features provided in the installation done by pip. The programmer can select the optimization flags during the compilation of packages which are responsible for the fast performance of library. In terms of performance, the packages installed might run slower because of the hidden conflicts between features. Installation location is provided by the programmer. Installation is done at the default location where all the python packages resides. This will allow you to select your own features and parameters to be installed. This will install the features which are already build from source i.e., installation of general features and parameters will be carried out. Note: All the points in the table are written with respect to OpenCV but they can also be generalized for other libraries and packages. The difference between installing a python package from source and through pip are given in the following table: pip is the package manager which is used to install the packages written in python. At this stage, there can be two pathways of installing OpenCV in your system namely – (a) Using pip (b) Source Installation.
CONDA INSTALL OPENCV 2.4.3 DOWNLOAD
The programmers have to download and load the model using OpenCV instructions in order to do the task of inference on their own dataset.įirstly, you need to install OpenCV library in your system prior to using it for your own dataset. In addition to image processing, it provides various pre-trained deep learning models which can be directly used to solve simple tasks at hand. on linuxOpenCV is an open source computer vision library which is very popular for performing basic image processing tasks such as blurring, image blending, enhancing image as well as video quality, thresholding etc. Type "help", "copyright", "credits" or "license" for more information. Installed Python-3.5.0 to ~/.pyenv/versions/3.5.0Ģ.4 Check the installed version. 2.2 Check the version that can be installed. See `pyenv help ' for information on a specific command.
![conda install opencv 2.4.3 conda install opencv 2.4.3](https://i.stack.imgur.com/OIo5w.png)
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Whence List all Python versions that contain the given executable
CONDA INSTALL OPENCV 2.4.3 FULL
Which Display the full path to an executable Versions List all Python versions available to pyenv Version Show the current Python version and its origin Rehash Rehash pyenv shims (run this after installing executables) Uninstall Uninstall a specific Python version Install Install a Python version using python-build Shell Set or show the shell-specific Python version Global Set or show the global Python version Local Set or show the local application-specific Python version $ echo 'eval "$(pyenv init -)"' > ~/.bash_profileĬommands List all available pyenv commands $ echo 'export PATH="$PYENV_ROOT/bin:$PATH"' > ~/.bash_profile $ echo 'export PYENV_ROOT="$HOME/.pyenv"' > ~/.bash_profile $ sudo yum install gcc zlib-devel bzip2-devel openssl-devel readline-devel ncurses-devel sqlite-devel gdbm-devel db4-devel expat-devel libpcap-devel xz-devel pcre-devel Install what you think you need $ sudo yum groupinstall "Development tools"