/CNNIQA

CVPR2014-Convolutional neural networks for no-reference image quality assessment

Primary LanguagePython

CNNIQA

PyTorch implementation of the following paper: Kang L, Ye P, Li Y, et al. Convolutional neural networks for no-reference image quality assessment[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2014: 1733-1740.

Note

The optimizer is chosen as Adam here, instead of the SGD with momentum in the paper.

Training

CUDA_VISIBLE_DEVICES=0 python CNNIQA.py 0 config.yaml LIVE CNNIQA

Before training, the im_dir in config.yaml must to be specified.

Visualization

tensorboard --logdir='./logs' --port=6006

Requirements

  • PyTorch
  • TensorFlow-TensorBoard if enableTensorboard in config.yaml is True.