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Utility library for processing image data in TensorFlow

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knielbo/kartina

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KARTINA - Image Search for Culture Analytics

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

For running in virtual environment (recommended) and assuming python3.6+ is installed.

sudo pip3 install virtualenv
virtualenv -p /usr/bin/python3.6 venv
source venv/bin/activate

Installing

Clone repository and install requirements

git clone https://github.com/knielbo/kartina.git
pip install -r requirements.txt

To run train model and generate graph

./main.sh

Running the tests

Explain how to run the automated tests for this system

Break down into end to end tests

./test.sh

And coding style tests

Explain what these tests test and why

Give an example

Deployment

Add additional notes about how to deploy this on a live system

Built With

Contributing

  1. Fork it!
  2. Create your feature branch: git checkout -b my-new-feature
  3. Commit your changes: git commit -am 'Add some feature'
  4. Push to the branch: git push origin my-new-feature
  5. Submit a pull request :D

Versioning

Authors

Kristoffer L. Nielbo
Ross D. Kristensen-McLachlan

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

Adrian Rosebrock, pyimagesearch

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