Data2Image

Data2Image is a state-of-the-art library that wraps the most important techniques for the construction of Synthetic Images from Sorted Data (also known as Tabular Data).

Features

• Input data formats (2 options):

  • Pandas Dataframe
  • Files with the following format
    • Tabular files: The input data must be in CSV, taking into account the Tidy Data format.
    • Tidy Data: The target (variable to be predicted) should be set as the last column of the dataset. Therefore, the first columns will be the features.
    • All data must be in numerical form.

• Runs on Linux, Windows and macOS systems.

• Compatible with Python 3.7 or higher.

Models

Model	Class	Features	Hyperparameters
TINTO	tinto()	blur	problem algorithm pixels blur amplification distance steps option seed times verbose
SuperTML	SuperTML()		problem verbose
IGTD	IGTD()		problem scale fea_dost_method save_image_size max_step val_step error switch_t min_gain seed verbose

Documentation

Read the documentation.

Getting Started

You can install Data2Image using Pypi(test):

    pip install data2image-alpha

To import a specific model use

    from data2Image.models import tinto

Create the model. If you don't set any hyperparameter, the model will use the default values (read documentation).

    model = tinto(blur=True)

To generate the synthetic images use .genereateImages(data,folder) method.

    model.generateImages(data, resultsFolderPath)

License

Data2Image is available under the Apache License 2.0.

Authors

• Borja Reinoso - [email protected]
• Manuel Castillo-Cara - [email protected]
• Raúl García-Castro