pyiqa.archs.liqe_arch

LIQE Model

github repo link: https://github.com/zwx8981/LIQE

Cite as: @inproceedings{zhang2023liqe,

title={Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective}, author={Zhang, Weixia and Zhai, Guangtao and Wei, Ying and Yang, Xiaokang and Ma, Kede}, booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={14071–14081}, year={2023}

}

Module Contents

pyiqa.archs.liqe_arch.qualitys = ['bad', 'poor', 'fair', 'good', 'perfect']

pyiqa.archs.liqe_arch.scenes = ['animal', 'cityscape', 'human', 'indoor', 'landscape', 'night', 'plant', 'still_life', 'others']

pyiqa.archs.liqe_arch.dists_map = ['jpeg2000 compression', 'jpeg compression', 'noise', 'blur', 'color', 'contrast',...

pyiqa.archs.liqe_arch.default_model_urls

class pyiqa.archs.liqe_arch.LIQE(model_type='liqe', backbone='ViT-B/32', step=32, num_patch=15, pretrained=True, pretrained_model_path=None, mtl=False)

Bases: torch.nn.Module

get_text_features(x)

forward(x)