Deep Learning Models for the KonIQ-10k Image Quality Assessment Database
This is part of the code for the paper "KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment". The included notebooks rely on the kutils library. Project data is available for download from osf.io.
Python 2.7 notebooks:
- Training and testing code for the KonCept512 and KonCept224 model (on KonIQ-10k).
- Ready-trained model weights for KonCept512 and KonCept224.
- Reimplementation of the DeepRN model trained on KonIQ-10k, following the advice of the original author, Domonkos Varga.
- Re-trained model weights (on SPP features) are available here.
- The features extracted from KonIQ-10k are available here.
- Contains image file names, scores, and train/validation/test split assignment (random).