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Setup and training

Setup

In theory, everything is very simple:

  • Install Python 3.7+ (optionally, you can use Anaconda).
  • Install TensorFlow by following the instructions on the official website, and don't forget about GPU drivers, etc.
  • Install the necessary packages by executing pip install -r requirements.txt at the root of the project.

Unfortunately, in reality, things can be a bit more complicated. For example, I had to use TensorFlow version 2.7.0, as newer versions didn't recognize my GTX 1070 Ti graphics card.

Training (Local)

To train the model on your computer, you would need a sufficiently powerful GPU. However, I personally prefer using Google Colab since my GPU is too weak for model training. The sequence of steps for training the model on your computer is quite straightforward:

  1. Run python3 scripts/preprocess-dataset.py
  2. Run python3 scripts/create-test-dataset.py
  3. Run python3 scripts/train.py

This should be sufficient for training a model, which will be saved as Data/simple-model-best.h5. This model will be automatically used by all other scripts.

Training (Google Colab)

For training the model on Google Colab, you need to follow these steps:

  1. Create a folder named alternative-input in your Google Drive.
  2. Archive the contents of the project's root folder into alternative-input.zip.
  3. Upload alternative-input.zip to the alternative-input folder on Google Drive.
  4. Open this notebook, make a copy, and run all code cells (Menu: Runtime -> Run all).
  5. At the beginning of the notebook, you will be prompted for permission to access your Google Drive. Once you grant permission, the model training process should begin.

I use Google Colab Pro, which costs around $10 per month at minimum. This subscription tier should be sufficient for training 5-15 models, allowing you to iteratively train models for a single person. After training is complete, the simple-model-best.h5 file will appear in Google Drive, which you'll need to download and place in your project folder.