Templates for Machine Learning and Computer Vision Projects

This week-long program introduces a number of projects related to computer vision and machine learning using Python and JavaScript.

This repository will be updated as week progresses.

Inital setup is

pipenv install

This will install all requirements for the projects in a new Python virtual environment.

Then activate the virtual environment with

pipenv shell

Installation on a new computer

We are using Python 3.7.4, P5.js, VS Code, Git for Windows, and Github Desktop. The repository contains a number of template files that include p5.js and other dependencies. Python dependencies are managed with Pipenv.

Download links:

• Python 3.7.4
• VS Code
• Git for Windows
• Github Desktop

Installation Steps:

Python 3.7

Install Python 3.7 64 bit version. Make sure to add the Python installation directory to the system Path during installation.

Windows Prerequisites for face_recognition and dlib

• Install CMake and add to the system path.
• Install Visual Studio
• Select "Desktop development with C++" during installation

Mac Prerequisites

pip install cmake

VS Code

Select default shell. Ctrl-Shift-P, select default shell, choose bash. Open a terminal and run these commands:

Install pipenv

pip install pipenv 

Clone this git repository

git clone https://github.com/holyokecodes/ML-CV-Templates.git 

Change to the new directory

cd ML-CV-Templates 

Make a New Github Repo on Github.com

Setup Origin and Upstream

git remote remove origin
git remote add origin YOUR_GITHUB_REPO_URL.git

git remote add upstream https://github.com/holyokecodes/ML-CV-Templates.git

Install dependencies

pipenv install 

Activate Python virtual environment

pipenv shell 

Install NLTK data

python
import nltk
nltk.download('punkt')
nltk.download('wordnet')
exit()