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Wadas Inference Runtime

Project description

WADAS Runtime

Description

WADAS Runtime is a library designed to facilitate inference using OpenVINO for the Wild Animals Detection and Alert System (WADAS) project. It provides tools and utilities to streamline the decryption and execution of AI models.

Usage

To use the WADAS Runtime library, follow these steps:

  1. Install the library locally:

    pip install wadas_runtime
    
  2. Import the library in your Python project:

    import wadas_runtime as wadas
    
  3. Load and compile the model. The library will decrypt the model in real time

    import wadas_runtime as wadas
    
    xml, bin = # Path to the model XML and encrypted binary file
    compiled_model = wadas.load_and_compile_model(xml, bin, "GPU")
    

Developer Guide

It is suggested to install the package locally by using pip install -e .[dev]. OpenSSL is required to build the package and needs to be installed separately.

Git hooks

All developers should install the git hooks that are tracked in the .githooks directory. We use the pre-commit framework for hook management. The recommended way of installing it is using pip:

pre-commit install

If you want to manually run all pre-commit hooks on a repository, run pre-commit run --all-files. To run individual hooks use pre-commit run <hook_id>.

Uninstalling the hooks can be done using

pre-commit uninstall

Testing the library

Python test uses pytest library. Type

cd test && pytest

to run the full test suite.

Generate Python packets

To create packets run the following commands

python -m build --sdist
cibuildwheel --platform windows --output-dir dist

Publishing packets

Then check on the built sdist and wheel that are properly formatted (all files should return a green PASSED)

twine check dist/*

Upload the packets to testpypi

twine upload --repository testpypi dist/*

To upload them to the real index (verify first with testpypi)

twine upload dist/*

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