Ajak Final Project

This is our final project at Makers Academy, to be presented 24/5/19.

Visit our web app, Ajak Doodler!

Getting started | Project aims | Technologies | Manifesto | Learning documentation | Authors | Acknowledgements

Getting started

git clone https://github.com/jpalmerr/ajak-final-project
pip3 install -r requirements.txt # to install python dependencies
npm install # to install node dependencies

To download data

Download Crown, Camera and Rabbit from Google QuickDraw Dataset and save to /data folder in the project under crowns.npy, cameras.npy and rabbits.npy.

To train model

python3 model_config/train.py

When prompted by running the above command, save the model as cameras_rabbits_crowns_model. Move the saved model to the /models folder.

To see model predict random image from test data

python3 model_config/predict_on_command_line.py

To run tests

The pytest framework is used for unit testing.

To run tests:
pytest

To run test coverage:
pytest --cov=lib

To run linter

We are using a linter called pylint for this project.

To run the linter:

pylint [options] module_or_package
For example pylint lib

Project aims

Our program aims to receive a user's drawing of a:

• crown
• camera
• rabbit

and our AI machine will return a prediction of the drawing.

Technologies

• Python
• Pytest
• Splinter
• Flask
• SKLearn library
• Keras API
• TensorFlow
• Google QuickDraw Dataset
• JavaScript
• jQuery
• Fabric JS
• Travis CI
• Heroku

Manifesto

Our project manifesto.

Our Trello board.

Learning documentation

See our wiki.

Authors

Alex Chen, Amy Jordan, James Palmer, Kim Diep.

Acknowledgements

Makers Academy