jjhickman/tensorflow-lite repository overview

Table of Contents

1. About The Project⁠
   • Built With⁠
2. Getting Started⁠
   • Prerequisites⁠
   • Installation⁠
3. Roadmap⁠
4. Contributing⁠
5. License⁠
6. Contact⁠
7. Acknowledgments⁠

⁠About The Project

This is the repository to build images for the Docker Hub repository⁠, jjhickman/tensorflow-lite.

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⁠Built With

• Tensorflow⁠
• C++⁠
• Python⁠

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⁠Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

⁠Prerequisites

Just plain old Docker and git. NOTE: Current supported architectures:

1. arm64 - aarch64/arm64
2. amd64 - x86_64/amd64

⁠Installation

1. For development, either use remote-containers extension in VS Code to run jjhickman/tensorflow-lite:[TAG]or run the following

   docker run -it -v ./workspace:/tensorflow-lite jjhickman/tensorflow-lite:[TAG] bash
   

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2. Examples can be found under /coral/pycoral.

   cd coral/pycoral \
   && python3 examples/classify_image.py \
    --model test_data/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite \
    --labels test_data/inat_bird_labels.txt \
    --input test_data/parrot.jpg
   

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⁠Roadmap

• Dual Edge TPU and PCIE Support
• Libcoral C++ API support
• Smaller production images
• More examples

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 for more information.

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⁠Contact

Project Link: https://github.com/jjhickman/tensorflow-lite⁠

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⁠Acknowledgments

• Google Coral Docs⁠
• Tensorflow Lite Docs⁠

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