- Install Fportfolio Anaconda For Mac Os X 10 11
- Install Fportfolio Anaconda For Mac Os X El Capitan
- Install Fportfolio Anaconda For Mac Os X Update
This tutorial will help you to install Anaconda for Mac OS.
Dec 27, 2019 Installing Anaconda. Anaconda is available for Windows, Mac OS X, and Linux, you can find the installation file in the anaconda official site. I suggest you choose the Python version 3.7 64-bit installer if you have a 64-bit machine, otherwise choose the 32-bit installer, instead. Double-click the downloaded file and click continue to start the installation. Answer the prompts on the Introduction, Read Me, and License screens. Click the Install button to install Anaconda in your /opt directory (recommended): OR, click the Change Install Location button to install in another location (not recommended). R for Mac OS X. This directory contains binaries for a base distribution and packages to run on Mac OS X (release 10.6 and above). Mac OS 8.6 to 9.2 (and Mac OS X 10.1) are no longer supported but you can find the last supported release of R for these systems (which is R 1.7.1) here.
Anaconda is both a package manager, python distribution and is incredibly useful for data tasks as it comes bundled with many scientific packages including sci-kit learn, SciPy, Pandas and NumPy.
Additionally it’s the recommended method for installing Jupyter Notebooks.
Installing Anaconda
Personally I prefer to install Python via the graphical interface because it’s a friendly and easy method.
1. Firstly visit the Anaconda website where you will have the choice to install either Python 2.7 or Python 3. I would recommend downloading the Python 3x. because this will be more supported in the future.
2. After successfully downloading Anaconda, locate it within your download folder and double click on the .pkg file.
3. Click continue.
4 -- You will now start the Anaconda3 installer process, click continue.
5. The installer provides a notification saying that it will update your bash profile and will install Anaconda3 within your PATH. Click continue.
6. Click continue to reveal the License Agreement.
7. Now you will need to read and click Agree for the Anaconda licensing agreement, then click continue.
7. Click on the install button.
8. You will need to enter your password which is the same as your Mac login password. Then click Install Software.
9. Click on Continue.
10. After completing the installation simply click close. Then you can move the Anaconda installer file to the trash bin.
Anaconda Frequently Answered Questions
To see whether Anaconda is installed on your Mac operating system, simply visit the Mac terminal and type Conda info. If Anaconda is installed you will see detailed information for both the Anaconda distribution and Python version.
To check the current version of Python open a new terminal on your Mac. Now type the following command into your terminal python--version if you do chosen to select the python3 distribution you will have received received something that looks like this on your screen that shows you the exact Python version that you’re using and if it has anaconda then you can safely know that anaconda is your main Python distribution
Anaconda does automatically install with Python anaconda is an environment and package distribution software for python and therefore you can choose between either Python 2.7 or a python 3 x
You do not need to install Python before installing or running anaconda.
To find where python has installed on your Mac simply open a new terminal window. Then type echo $PATH . You can activate any customised Conda environments with the following command: Conda activate environment name
What’s OpenCV?
Ahhh, computer vision, such a cool field! Lately, I’ve been trying to become more knowledgeable about CV and image processing in python. OpenCV (CV = ‘computer vision’) is an excellent open source computer vision software library written in C++ that supports C++, C, Python, Java, and Matlab API’s. OpenCV will supply you with functions that will let you detect faces in images, track objects in a video, and perform any number of image processing tasks.
The only problem is: how the hell do I install OpenCV so that I can use it in conjunction with a Jupyter notebook? Let’s be honest, most likely you’re either you’re using a Jupyter notebook, Spyder, or the ipython terminal (if you’re a real sadist) to test your python code. And especially if you’re coding for image processing, you’re going to want to view your progress without having (a) a million separate images open and (b) having to wait for Spyder to inevitably crash. That’s the beauty of a Jupyter notebook - when you’re using it with Matplotlib, you can just display your images and videos in a living document!
![Fportfolio Fportfolio](/uploads/1/2/6/5/126539140/479022991.jpg)
For me, my ideal OpenCV situation would be for me to be able to simply type and evaluate the following
import
statements with zero errors or package conficts:Problems with traditional installation methods
There are many ways to install OpenCV. The standard approach is to download it from the OpenCV website and then compile and install OpenCV using the software building utility “CMake” all within a virutal Python environment. I’ve gone down this route according to Adrian Rosebrock’s fabulous installation walkthrough, and if you just want to have access to OpenCV 3.0, I suggest you consider it. But, at the end of the day, there are even more steps required after Adrian’s 9 steps to get OpenCV compatible with a Jupyter notebook. Other installation walkthroughs I’ve found tend to be generally convoluted and assume that you have Homebrew, XCode, maybe MacPorts, or just experience in general with installing and building software packages. Wouldn’t it be great if we could just run something analogous to
pip install opencv
?If you’re like me (maybe you’re not) I often think that
pip install
‘ing a Python package is the same thing as R’s install.packages
function - while we get similar functionality, R packages come with the luxury of basically never interfering with other R package dependencies! If one package needs a newer or older version of some other package you’ve already installed, install.packages
will most likely just take care of everything for you. Python packages, on the other hand, will often have dependencies on specific versions of other packages, so if you pip install
one package, other package may fail to import because their dependent packages have been updated. That’s why we use virtual environments; my favorite method for creating and running virtual environments is with Anaconda, a Python distribution that comes with Sklearn, Scipy, NumPy, Jupyter notebook, and most of the other essential tools a data scientist needs when using Python.Overall, I installed OpenCV cleanly in just a few steps:
- Install Anaconda, make Anaconda’s Python your system’s default Python (skip if you already have this).
- Create a virtual environment.
- Make sure all Conda packages are up-to-date.
- Run
conda install -c https://conda.binstar.org/menpo opencv
- Test.
(1) Install Anaconda. (Skip if you already have Anaconda).
First off, I’m still a python 2 guy. Yeah, there’s python 3, but I grew up on Py 2.7 and it’ll take a lot to pry it from my cold, dead hands. So I have a python 2.7 Anaconda environment running on my computer. Your choice.
Install Fportfolio Anaconda For Mac Os X 10 11
I went to the Anaconda downloads page and got the Python 2.7 Mac OS X 64-Bit command-line installer, so that we can install everything from Terminal.
After downloading that, navigate to your Downloads directory (if you’re new to the Terminal, just open the Terminal application and type
cd $HOME/Downloads
).While still in Terminal, enter
Awesome, now you’ve downloaded and installed Anaconda.
(1.b) Make Anaconda your default python installation.
For data science, Anaconda rules. Ideally, when you’re in Terminal and you type
python
, you’d like for the Anaconda python installation to be the default python that starts running instead of what comes installed by default on a typical Macbook. Why? Well, using Anaconda we can just import NumPy, import any Scikit Learn funciton, import Matplotlib, etc.To see what I’m talking about, type this in Terminal:
If you get
/usr/bin/python2.7
, you’re not using the Anaconda installation. To change this, you’ll need to change your bash_profile so that the default path to the python installation in the Anaconda directory. If you don’t have a .bash_profile file in your home directory, do this:This just created that file. Next, open the .bash_profile page and add this line:
export PATH=”~/anaconda/bin:$PATH”
Finally, you have to make your system update python path the with your new settings, so in Terminal type
Install Fportfolio Anaconda For Mac Os X El Capitan
(2) Make an Anaconda virtual environment
Install Fportfolio Anaconda For Mac Os X Update
Anaconda has great documentation if you ever get lost using their tools, but otherwise they’re pretty easy to use. To create a virtual python 2.7 environment called “py27,” run this:
To enter this virtual environment, we use Conda’s
source activate
function:If the environment is running properly, you should see
(py27)
preceding the $
sign at the command prompt in Terminal. In this environment we have access to Anaconda’s python package installer, conda install
, so that we can install packages at will in this “bubble” without messing up dependencies (basically breaking python) in any other environment. Side note: if you want to exit this py27 environment, just enter source deactivate
in Terminal.(3) Update packages
Just to be safe, I updated all of my python packages while inside of my py27 environment. It’s ridiculously easy with Anaconda:
(4) Install OpenCV
With Anconda we can install python packages within a specific Conda environment using
conda install
instead of pip
, the typical python package management system.Next, I would normally suggest just typing
conda install opencv
at the command prompt, but this (unsurprisingly) lead me to a package conflict with NumPy! Yep, the version of OpenCV that Conda installed relied on a specific release of the NumPy package that was actually in conflict with the one that was just updated in step (3). OK, to be honest, maybe I brought that upon myself with updating the packages the way I did. But, there’s a work around that functions with this latest update of NumPy: install OpenCV directly from the Menpo project:(5) Fire up a Jupyter notebook and test!
The Anaconda environment should now have everything we need to start analyzing images in a self-contained little Jupyter notebook. Test it out. First, launch a Jupyter notebook from the terminal:
Next, see if everything is installed correctly; hopefully you’ll be able to run this sans errors:
If successful, you’ll be able to readily access OpenCV functions with the package prefix
cv2
!Back in April Canon released its EOS webcam utility application for Windows, and now they have released a MacOS version.The EOS Webcam Utility Beta software solution requires one single USB plug (which may need to be purchased separately) to connect the camera to a Windows. Canon eos utility mac os x el capitan.