This is a simple ongoing image aesthetic assessment task.

Thanks to the coworker: Kun Xiong. We also thank all the advisers!

git clone https://github.com/dieuroi/SimAesthetics.git
cd SimAesthetics
virtualenv -p python3.8 env
source ./env/bin/activate

The model was trained on the AVA (Aesthetic Visual Analysis) dataset. You can get it from here. The meta data can be found from here.

• NIMA: NIMA: Neural Image Assessment.
• MLSP: Effective Aesthetics Prediction with Multi-Level Spatially Pooled Features.

Usage: cli.py [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  get_image_score  Get image scores
  prepare_dataset  Parse, clean and split dataset
  train_model      Train model
  validate_model   Validate model

Contributing are welcome

This project is licensed under the MIT License - see the LICENSE file for details

• Most of this code is borrowed heavily from the Pytorch NIMA PyTorch NIMA: Neural IMage Assessment
• pytorch-mobilenet-v2
• origin NIMA article
• origin MobileNetV2 article
• Post at Google Research Blog
• origin MLSP article
• MLSP (tensorflow)