Exercise notebooks for CVND.
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:
minicondaon your computer, by selecting the latest Python version for your operating system. If you already have
minicondainstalled, you should be able to skip this step and move on to step 2.
* Each time you wish to work on any exercises, activate your
Download the latest version of
minicondathat 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
| | 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:
For Windows users, these following commands need to be executed from the Anaconda prompt as opposed to a Windows terminal window. For Mac, a normal terminal window will work.
These instructions also assume you have
gitinstalled for working with Github from a terminal window, but if you do not, you can download that first with the command:
conda install git
If you'd like to learn more about version control and using
gitfrom the command line, take a look at our free course: Version Control with Git.
Now, we're ready to create our local environment!
Clone the repository, and navigate to the downloaded folder. This may take a minute or two to clone due to the included image data.
git clone https://github.com/udacity/CVND_Exercises.git cd CVND_Exercises
Create (and activate) a new environment, named
cv-ndwith Python 3.6. If prompted to proceed with the install
(Proceed [y]/n)type y.
- __Linux__ or __Mac__: ``` conda create -n cv-nd python=3.6 source activate cv-nd ``` - __Windows__: ``` conda create --name cv-nd python=3.6 activate cv-nd ```
At this point your command line should look something like:
(cv-nd) <user>:CVND_Exercises <user>$. The
(cv-nd)indicates that your environment has been activated, and you can proceed with further package installations.
- __Linux__ or __Mac__: ``` conda install pytorch torchvision -c pytorch ``` - __Windows__: ``` conda install pytorch-cpu -c pytorch pip install torchvision ```
Install a few required pip packages, which are specified in the requirements text file (including OpenCV).
pip install -r requirements.txt
Now all of the
cv-ndlibraries are available to you. Assuming you're environment is still activated, you can navigate to the Exercises repo and start looking at the notebooks:
cd cd CVND_Exercises jupyter notebook
To exit the environment when you have completed your work session, simply close the terminal window.
Verify that the
cv-ndenvironment was created in your environments:
conda info --envs
Cleanup downloaded libraries (remove tarballs, zip files, etc):
conda clean -tp
Uninstall the environment (if you want); you can remove it by name:
conda env remove -n cv-nd