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Sophoappeal

This repository summarizes the work done in the DFG project Sophoappeal (437543412).

Important use git clone --recursive for the checkout, and have ssh keys for your git cloning activated.

Structure

  • images: all images used in the project

  • aesthetics_srv: evaluation web service used for lab and crowd tests, for a generic framework checkout AVRateVoyager

  • models for appeal prediction:

    • appeal_prediction_dnn_transferlearning
    • appeal_prediction_models

  • features:

    • dnn_features
    • image_features_tool

  • extracted maps for images:

    • depth_segmentation_maps
    • saliency_maps

  • photo rule prediction:

    • rule_prediction
    • rule_prediction_extension

  • subjective lab and crowd tests:

    • evaluation_image_appeal_test_1
    • evaluation_image_appeal_test_2

  • additional: follow up work, such as appeal of AI generated images, and AVRateVoyager

Requirements

The provided software is tested under Ubuntu 20.04 and 22.04.

  • python3, python3-pip

The subfolders have dedicated README.md files with instructions.

Acknowledgments

If you use this software or data in your research, please include a link to the repository and reference the following paper.

@article{goering2023imageappeal,
  title={Image Appeal Revisited: Analysis, new Dataset and Prediction Models},
  author={Steve G\"oring and Alexander Raake},
  journal={IEEE Access},
  year={2023},
  publisher={IEEE},
  note={to appear},
  volume={11},
  number={},
  pages={69563-69585},
  doi={10.1109/ACCESS.2023.3292588},
}

License

GNU General Public License v3. See LICENSE.md file in this repository.