Computer Vision Nanodegree Program, Exercises

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.

Configure and Manage Your Environment with Anaconda

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.

Overview

Using Anaconda consists of the following:

1. Install miniconda on your computer. If you already have conda or miniconda installed, you should be able to skip this step and move on to step 2.
2. Create a new conda environment using the files in this repository.
3. Each time you wish to work on any exercises, activate your conda environment!

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1. Installation

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

2. Create the Environment

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

Uninstalling

If you ever want to uninstall the environment, you can remove it by name:

conda env remove -n cv-nd

3. Use and Activate the Environment

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:

OS X and Linux

$ source activate cv-nd

Windows

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.