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Eductional material on deep learning applications in computer vision

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CVCA-X: Computer Vision 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/cvca-x.git
pip install -r requirements.txt

To train model


To run model


Running the tests

Explain how to run the automated tests for this system

Break down into end to end tests

todo

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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