Fine-tune EfficientNet

1. Fine-tune a pre-trained TF-EfficientNet-Lite4 model on a custom image dataset.

Note

It's recommended to use Python 3.11.x

1. Create a dataset folder.
2. Create subfolders (example: dog, cat, fish, bird) and populate them.
3. Run python src/fine_tune_from_base.py.

When its finished it will return a checkpoint file.

2. Create a tflite model

1. Run python src/convert_to_tflite.py.

This will return a tflite and labels.txt file.

3. Add metadata to tflite model

1. Run python src/add_metadata_to_tflite.py.

Tip

Fine-tuned models are used in conjunction with the Vision Classification project, utilizing its Mediapipe Image Classification task.

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Notice: This project was initally created to be used in-house, as such the development is first and foremost aligned with the internal requirements.