pyiqa.archs.dists_arch
======================

.. py:module:: pyiqa.archs.dists_arch

.. autoapi-nested-parse::

   DISTS metric introduced in

   @article{ding2020iqa,
     title={Image Quality Assessment: Unifying Structure and Texture Similarity},
     author={Ding, Keyan and Ma, Kede and Wang, Shiqi and Simoncelli, Eero P.},
     journal = {CoRR},
     volume = {abs/2004.07728},
     year={2020},
     url = {https://arxiv.org/abs/2004.07728}
   }

   Created by: https://github.com/dingkeyan93/DISTS/blob/master/DISTS_pytorch/DISTS_pt.py
   Re-implemented by: Jiadi Mo (https://github.com/JiadiMo)







Module Contents
---------------

.. py:data:: default_model_urls

.. py:class:: L2pooling(filter_size=5, stride=2, channels=None, pad_off=0)

   Bases: :py:obj:`torch.nn.Module`


   .. py:method:: forward(input)


.. py:class:: DISTS(pretrained=True, pretrained_model_path=None, **kwargs)

   Bases: :py:obj:`torch.nn.Module`


   DISTS model.
   :param pretrained_model_path: Pretrained model path.
   :type pretrained_model_path: String


   .. py:method:: forward_once(x)


   .. py:method:: forward(x, y)

      Compute IQA using DISTS model.

      :param - x: An input tensor with (N, C, H, W) shape. RGB channel order for colour images.
      :param - y: An reference tensor with (N, C, H, W) shape. RGB channel order for colour images.

      :returns: Value of DISTS model.