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An openFrameworks addon for Faiss - "efficient similarity search and clustering of dense vectors."

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_This is under development currently so, your please post questions to the [issues](https://github.com/bakercp/ofxFAISS/issues) for now._

# ofxFAISS
An openFrameworks addon for FAISS - "efficient similarity search and clustering of dense vectors."

More on the library, including tutorials and lots of great documentation [here](https://github.com/facebookresearch/faiss).

## Features

Really fast approximate similarity search and clustering of dense vectors.

## Getting Started

### TL;DR
-   From the `scripts/` directory ...
    -   `./bootstrap.sh`
-   From the `example_cpu_Flat/` directory ...
    -   `make && make run`

For more, including some help with macOS, see [docs/GETTING_STARTED.md](docs/GETTING_STARTED.md).

## Troubleshooting

For more, see [docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md).

## Documentation

API documentation can be found here.

## Build Status

_TODO_

## Compatibility

The `stable` branch of this repository is meant to be compatible with the openFrameworks [stable branch](https://github.com/openframeworks/openFrameworks/tree/stable), which corresponds to the latest official openFrameworks release.

The `master` branch of this repository is meant to be compatible with the openFrameworks [master branch](https://github.com/openframeworks/openFrameworks/tree/master).

Some past openFrameworks releases are supported via tagged versions, but only `stable` and `master` branches are actively supported.

## Versioning

This project uses Semantic Versioning, although strict adherence will only come into effect at version 1.0.0.

## Licensing

See [LICENSE.md](LICENSE.md).

## Contributing

Pull Requests are always welcome, so if you make any improvements please feel free to float them back upstream :)

1.  Fork this repository.
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.  Create new Pull Request.

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