This repository contains code exercises and materials for Udacity's Computer Vision Nanodegree program. It consists of tutorial notebooks that demonstrate, or challenge you to complete, various computer vision applications and techniques. These notebooks depend on a number of software packages to run, and so, we suggest that you create a local environment with these dependencies by following the instructions below.
Per the Anaconda docs:
Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them. It works on Linux, OS X and Windows, and was created for Python programs but can package and distribute any software.
Using Anaconda consists of the following:
- Install
miniconda
on your computer. If you already haveconda
orminiconda
installed, you should be able to skip this step and move on to step 2. - Create a new
conda
environment using the files in this repository. - Each time you wish to work on any exercises, activate your
conda
environment!
Download the latest version of miniconda
that matches your system.
NOTE: There have been reports of issues creating an environment using miniconda v4.3.13
. If it gives you issues try versions 4.3.11
or 4.2.12
from here.
Linux | Mac | Windows | |
---|---|---|---|
64-bit | 64-bit (bash installer) | 64-bit (bash installer) | 64-bit (exe installer) |
32-bit | 32-bit (bash installer) | 32-bit (exe installer) |
Install miniconda on your machine. Detailed instructions:
- Linux: http://conda.pydata.org/docs/install/quick.html#linux-miniconda-install
- Mac: http://conda.pydata.org/docs/install/quick.html#os-x-miniconda-install
- Windows: http://conda.pydata.org/docs/install/quick.html#windows-miniconda-install
Setup the cv-nd
environment.
git clone https://github.com/udacity/CVND_Exercises.git
cd CVND_Exercises
If you are on Windows, rename
meta_windows_patch.yaml
to
meta.yaml
Create cv-nd. Running the command below will create a new conda
environment that has all libraries you need to be successful in this program. This step may take a while, since you the environment is installing all the necessary packages.
conda env create -f environment.yaml
Verify that the cv-nd environment was created in your environments:
conda info --envs
Cleanup downloaded libraries (remove tarballs, zip files, etc):
conda clean -tp
If you ever want to uninstall the environment, you can remove it by name:
conda env remove -n cv-nd
Now that you have created an environment, you will need to activate the environment to use it! This must be done each time you begin a new working session i.e. open a new terminal window.
Activate the cv-nd
environment:
$ source activate cv-nd
Depending on shell either:
$ source activate cv-nd
or
$ activate cv-nd
That's it. Now all of the cv-nd
libraries are available to you.
To exit the environment when you have completed your work session, simply close the terminal window.