A farm animal sound classifier
This project holds the backend logic and the ML model to classify farm animals sound using a pre-trained TensorFlow model (YAMNet) as audio feature extractor and transfer leraning.
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├── README.md <- The top-level README.
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├── models <- Trained and serialized models.
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├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description.
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├── reports
│ └── figures <- Generated plots and figures.
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├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
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├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
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│ ├── inference.py <- Script to run inference with the model created. Holds SoundClassifier class
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│ ├── main.py <- Contain the code to run a REST API
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│ ├── config.py <- Contain static parameters
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│ ├── yamnet.py <- Contain YAMNet model
│ ├── features.py <- Contain code for feature creation for the original YAMNet model
│ ├── params.py <- Contain parametes to run YAMNet model
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├── Dockerfile.lambda <- Dockerfile to create a prod container to deploy in AWS Lambda
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└── Dockerfile <- Dockerfile to create a dev container
Project inspired by:
