Pytorch version of IEEE Transactions on Image Processing 2019 : J. Kim, A. Nguyen and S. Lee, "Deep CNN-Based Blind Image Quality Predictor," in IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 1, pp. 11-24, Jan. 2019, doi: 10.1109/TNNLS.2018.2829819.
- Some training details differ from the original paper, if you want to be consistent with the original pape, make some changes.
- This training progress only support on LIVE II database now, the training progress on TID2013, CSIQ, LIVEMD, CLIVE will be released soon.
- For the Step 1 training, run
python train_step1.py - For the Step 2 training, run
python train_step2.py
- Cross dataset test code will be published
- Train on different distortion types on LIVE, TID2013, CSIQ will be published
- Code of evaluations on Waterloo Exploration Database (D-test, L-test, P-test and gMAd competition) will be published