Photo Tagger - A Django Tensor Flow Project

This project is based off of the following tutorial and base template https://docs.djangoproject.com/en/2.1/intro/tutorial01/

Setting up your environment

If you don't already have conda, install conda Take some time to learn about conda:

You can clone this repository, install all dependencies and try it in your browser quite easily:

git clone https://github.com/PhotoTagger/django-initial.git
cd django-initial
conda env create -n photoTaggerEnv -f=./environment.yml
source activate photoTaggerEnv
python manage.py runserver

Rules for committing new code

Lets agree on a short list of leading active verbs:

add: Create a capability e.g. feature, test, dependency.
delete: Remove a capability e.g. feature, test, dependency.
fix: Fix an issue e.g. bug, typo, accident, misstatement.
build: Change the build process, or tooling, or infra.
refactor: A code change that MUST be just a refactoring.
docs: Refactor of documentation, e.g. help files.

Ex: git commit -m "Add: Added API to urls.py"

Useful Conda Commands

Installing dependencies that were added to the environment.yml file

conda env update environment.yml
conda activate photoTaggerEnv or source activate photoTaggerEnv

Viewing current dependencies installed within an environment conda list

###Sharing dependencies

Instead of doing a conda install <package> you should manually add it to the environment.yml file and then follow the instructions above to perform a conda update

Testing

Unit tests for this module only can be run using this command from the project root /django-initial:

python manage.py test imageprocessor.tagservice

This module's tests will also be included automatically as part of overally django test suite by running this command from the project root /django-initial:

python manage.py test