pyiqa.archs.mad_arch
====================

.. py:module:: pyiqa.archs.mad_arch

.. autoapi-nested-parse::

   MAD Metric

   Created by: https://github.com/dingkeyan93/IQA-optimization/blob/master/IQA_pytorch/MAD.py

   Modified by: Jiadi Mo (https://github.com/JiadiMo)

   .. note::

      Official matlab code is not available;
      Pytorch version >= 1.8.0;









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

.. py:data:: MAX

.. py:function:: extract_patches_2d(img: torch.Tensor, patch_shape: list = [64, 64], step: list = [27, 27], batch_first: bool = True, keep_last_patch: bool = False) -> torch.Tensor

.. py:function:: make_csf(rows, cols, nfreq)

.. py:function:: get_moments(d, sk=False)

.. py:function:: ical_stat(x, p=16, s=4)

.. py:function:: ical_std(x, p=16, s=4)

.. py:function:: hi_index(ref_img, dst_img)

.. py:function:: gaborconvolve(im)

.. py:function:: lo_index(ref, dst)

.. py:class:: MAD(channels=3, test_y_channel=False)

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


   :param - channel: Number of input channel.
   :param - test_y_channel: bool, whether to use y channel on ycbcr which mimics official matlab code.

   .. rubric:: References

   Larson, Eric Cooper, and Damon Michael Chandler. "Most apparent distortion: full-reference
   image quality assessment and the role of strategy." Journal of electronic imaging 19, no. 1
   (2010): 011006.


   .. py:method:: mad(ref, dst)

      Compute MAD for a batch of images.
      :param ref: An reference tensor. Shape :math:`(N, C, H, W)`.
      :param dst: A distortion tensor. Shape :math:`(N, C, H, W)`.



   .. py:method:: forward(X, Y)

      Computation of CW-SSIM metric.
      :param X: An input tensor. Shape :math:`(N, C, H, W)`.
      :param Y: A target tensor. Shape :math:`(N, C, H, W)`.

      :returns: Value of MAD metric in [0, 1] range.