🎲 Histogramo Dice Model Zoo
A collection of TensorFlow Lite Object Detection models that recognize dice. All models are supported by the Histogramo app and will collect dice statistics on the dice the models are trained to recognize. Model files are provided in the TensorFlow Lite FlatBuffers format (.tflite).
While Histogramo can load any TensorFlow Lite object detection model, it only supports the following labels for recognizing dice:
one
two
three
four
five
six
For Cities and Knights, Histogramo can distinguish red die and also the special "boat" die used for events:
red_one
red_two
red_three
red_four
red_five
red_six
boat
green
yellow
blue
We invite you to make and submit your own dice detection model. The model should be a TensorFlow Lite Object Detection model trained with the supported labels.
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Fork the Repository: Fork the repository to your GitHub account so that you can make changes to it without affecting the original repository.
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Clone the Repository: Clone the repository to your local machine using git clone https://github.com/your-username/dice-model-zoo.git
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Create a New Branch: Create a new branch in which you will make your changes using git checkout -b branch-name.
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Make Changes: Make changes to the code and/or documentation in the repository. Ensure that your changes follow the coding style and conventions used in the project.
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Test Changes: Test your changes thoroughly to ensure they are functioning as expected.
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Commit Changes: Commit your changes to your local repository using git commit -m "Your commit message here".
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Push Changes: Push your changes to your forked repository using git push origin branch-name.
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Create Pull Request: Navigate to the original repository and create a pull request from your forked repository's branch to the original repository's branch. Be sure to include a detailed description of the changes you made and why they are necessary.
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Wait for Review: Wait for feedback from the repository maintainers and make any requested changes.
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Merge Changes: Once your changes have been approved, they will be merged into the original repository.
Remember to be respectful and professional in your interactions with other contributors and maintainers. Happy contributing!
Models in this repository are available for use under the MIT license.