/shoreline-species-identification

Clam Species classification using pytorch and transfer learning

Primary LanguagePython

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Shoreline Species Identification

A app that can distiguish between an Atlantic Bay Scallop and a Hard Clam! (For now)
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Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments

About The Project

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Started of as an ELRO Community project, the purpose of the APP is to explore ways for citizen scientist to contribute to the development of a shoreline park. In a shoreline park scientist would want to know how their park is impacting the ecological enviroment. This app will help track animal sightings in the park while providing a fun activity for the visitor.

What can it do:

  • Classify the sighted animal.
  • Display information of the animal to the user.
  • Create a form for the user to submit their sighting and contribute to a database for the park agents.

Of course, there are already apps that can do this but we were trying to learn and develope something fun and intresting ourselves.

A list of resources we used to learn are listed in the acknowledgements.

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Built With

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Usage

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Upload a photo of the animal.

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Roadmap

  • Feature 1
  • Feature 2
  • Feature 3
    • Nested Feature

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Ryan Zhang - ryanz22@nycstudents.net

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Acknowledgements

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