I was unable to launch Navigator on Mac OS X, so I tried uninstalling Anaconda to try a fresh install. But on doing conda install anaconda-clean, I got the following error: ImportError: No module named mimetools Using Anaconda API: https.
![Anaconda download mac os x 10.8 Anaconda download mac os x 10.8](/uploads/1/2/4/6/124620082/682637507.jpg)
- This is a rebuild of the standard conda cmake package. That one doesn't work on Mac OS X 10.6, and is an older version for Python 2.7 on Windows. This is rebuilt on an OS X 10.6 machine, so we can build IMP for older Macs (and Windows).
- Download Anaconda. Anaconda Community. Anaconda Community Open Source NumFOCUS Support Developer Blog. PRIVACY POLICY EULA (Anaconda Cloud v2.33.29.
Review the system requirements listed below before installing Anaconda Individual Edition. If you don’t want the hundreds of packages included with Anaconda, you can install Miniconda, amini version of Anaconda that includes just conda, its dependencies, and Python.
System requirements
- License: Free use and redistribution under the terms of the End User License Agreement - Anaconda® Individual Edition.
- Operating system: Windows 8 or newer, 64-bit macOS 10.13+, or Linux, including Ubuntu, RedHat, CentOS 6+, and others.
- If your operating system is older than what is currently supported, you can find older versions of the Anaconda installers in our archive that might work for you. See Using Anaconda on older operating systems for version recommendations.
- System architecture: Windows- 64-bit x86, 32-bit x86; MacOS- 64-bit x86; Linux- 64-bit x86, 64-bit Power8/Power9.
- Minimum 5 GB disk space to download and install.
On Windows, macOS, and Linux, it is best to install Anaconda for the local user,which does not require administrator permissions and is the most robust type ofinstallation. However, if you need to, you can install Anaconda system wide,which does require administrator permissions.
Silent mode install
You can use silent mode toautomatically accept default settings and have no screen prompts appear duringinstallation.
Using Anaconda on older operating systems
We recommend upgrading your operating system. Most OS that are no longersupported in the latest Anaconda are no longer getting security updates.Upgrading your OS allows you to get the latest packages, performanceimprovements, bug fixes, etc.
To use Anaconda on older operating systems, download from our archive.You will not be able to use conda to update or install packages beyondthe Anaconda version noted in the table below, unless you limit it toversions available at the time that particular version of Anacondawas released.You can see what was available by checking the package table archives.
Operating system | How to install Anaconda |
---|---|
macOS 10.10-10.12; Windows 7 | Use the command line or graphical installers for Anaconda versions 2019.10 and earlier. Download from our archive. |
macOS 10.9 | Use the command line or graphical installers for Anaconda versions5.1 and earlier. Note Qt and other packages released after Anaconda Distribution 5.1 (February 15th, 2018)may not work on macOS 10.9, so it may be necessary to not update certain packages beyond this point. |
macOS 10.7 and 10.8 | Use the command line installers for Anaconda versions 4.2 and earlier. |
macOS 10.5 and 10.6 | Use the command line installers for Anaconda versions 1.8 and earlier. |
Windows XP | Use Anaconda versions 2.2 and earlier. |
Centos5 (or equivalent) | Use Anaconda versions 4.3 and earlier. |
Installing Anaconda on a non-networked machine (air gap)
- Obtain a local copy of the appropriate Anaconda installer for the non-networked machine. You can copy the Anaconda installer to the target machine using many different methods including a portable hard drive, USB drive, or CD.
- After copying the installer to the non-networked machine, follow the detailed installation instructions for your operating system.
Note
You can install offline copies of both docs.anaconda.com and enterprise-docs.anaconda.com by installing the conda package anaconda-docs:
condainstallanaconda-docs
You can install offline copies of documentation for many of Anaconda’s open-source packages by installing the conda package anaconda-oss-docs:
condainstallanaconda-oss-docs
Other ways to get Anaconda or Miniconda
You can find the official Anaconda or Miniconda AMIs on the AWS Marketplace.
You can find the official Anaconda and Miniconda Docker images on Docker Hub.
Idvd software download for mac. If you have a CDH cluster, you can install the Anaconda parcel using Cloudera Manager. The Anaconda parcel provides a static installation of Anaconda, based on Python 2.7, that can be used with Python and PySpark jobs on the cluster.
Troubleshooting
If you experience errors during the installation process,review our Troubleshooting topics.
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!
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.
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
(2) Make an Anaconda virtual environment
Anaconda has great documentation if you ever get lost using their tools, but otherwise they’re pretty easy to use. Free video editing software. To create a virtual python 2.7 environment called “py27,” run this:
To enter this virtual environment, we use Conda’s
source activate
function:Anaconda Terminal Mac
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.Where Can I Download Mac Os X
(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:
Anaconda Python Mac
(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
!