Introduction to Computer Vision

1. Introduction to Computer Vision
2. The State of the Art, Applications, and Using Open Source Code - let's use slides for this.
3. (Optional/Review Session) Introduction to Jupyter + Python of Compter Vision
4. How to do things with fastai

Lectures

Notebook/Slides	Recommended Reading/Viewing	Additional Reading/Viewing	Key Topics
A Brief History of Neural Networks	The Summer Vision Project	-	-

Programming Challenge

Setup

The Python 3 Anaconda Distribution is the easiest way to get going with the notebooks and code presented here.

(Optional) You may want to create a virtual environment for this repository:

conda create -n cv python=3 
source activate cv

You'll need to install the jupyter notebook to run the notebooks:

conda install jupyter

# You may also want to install nb_conda (Enables some nice things like change virtual environments within the notebook)
conda install nb_conda

This repository requires the installation of a few extra packages, you can install them with:

conda install -c pytorch -c fastai fastai
conda install jupyter
conda install opencv
pip install jupyterthemes

(Optional) jupyterthemes can be nice when presenting notebooks, as it offers some cleaner visual themes than the stock notebook, and makes it easy to adjust the default font size for code, markdown, etc. You can install with pip:

pip install jupyterthemes

Recommend jupyter them for presenting these notebook (type into terminal before launching notebook):

jt -t grade3 -cellw=90% -fs=20 -tfs=20 -ofs=20 -dfs=20

Recommend jupyter them for viewing these notebook (type into terminal before launching notebook):

jt -t grade3 -cellw=90% -fs=14 -tfs=14 -ofs=14 -dfs=14