Flagnet is a neural network for detecting country flags in photos. The detection is backed up by our very own dataset – the collection of photos of flags for 193 United Nations member countries.

• Getting started
  • Configuration
  • Dataset
• Contributing
• License

Flagnet is built in Python 3. Before cloning the project, make sure that you have downloaded and installed Python and Pipenv.

After downloading Python and Pipenv, you have to download all dependencies via Pipenv:

$ pipenv install

Now you're ready for the project!

All project configuration is controlled from a single place – the config.py file. Currently you can change these parameters:

MIN_IMAGE_SIZE = 416, 416         # minimum size of images in the dataset
SCREENSHOT_IMAGE_SIZE = 800, 600  # size of generated images from Flagwaver website
NUM_DOWNLOAD_WORKERS = 8          # number of parallel workers when downloading the dataset

The images which are part of the dataset are stored in the dataset folder and organized into the folders by country ISO 3166-1 alpha-2 codes. Inside every folder, there is a credits.yml (and its visual Markdown representation credits.md) which contains a list of images with its author name, license and download URL. To download the dataset, position yourself in the root of the project and run the downloader:

$ python -m download.download_dataset

Pull requests are welcome for both the dataset and the neural network.

Flagnet is released under the MIT license.