pyiqa.archs.psnr_arch
=====================

.. py:module:: pyiqa.archs.psnr_arch

.. autoapi-nested-parse::

   Peak signal-to-noise ratio (PSNR) Metric

   Created by: https://github.com/photosynthesis-team/piq

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

   Refer to:
       Wikipedia from https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio
       QIQA from https://github.com/francois-rozet/piqa/blob/master/piqa/psnr.py







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

.. py:function:: psnr(x, y, test_y_channel=False, data_range=1.0, eps=1e-08, color_space='yiq')

   Compute Peak Signal-to-Noise Ratio for a batch of images.
   Supports both greyscale and color images with RGB channel order.
   :param - x: An input tensor. Shape :math:`(N, C, H, W)`.
   :param - y: A target tensor. Shape :math:`(N, C, H, W)`.
   :param - test_y_channel: Convert RGB image to YCbCr format and computes PSNR
   :type - test_y_channel: Boolean
   :param only on luminance channel if `True`. Compute on all 3 channels otherwise.:
   :param - data_range: Maximum value range of images (default 1.0).

   :returns: PSNR Index of similarity between two images.


.. py:class:: PSNR(test_y_channel=False, crop_border=0, **kwargs)

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


   :param - X: distorted image and reference image tensor with shape (B, 3, H, W)
   :type - X: torch.Tensor
   :param Y: distorted image and reference image tensor with shape (B, 3, H, W)
   :type Y: torch.Tensor
   :param - test_y_channel: Convert RGB image to YCbCr format and computes PSNR
                            only on luminance channel if `True`. Compute on all 3 channels otherwise.
   :type - test_y_channel: Boolean
   :param - kwargs: other parameters, including
                    - data_range: maximum numeric value
                    - eps: small constant for numeric stability

   :returns: (B, 1)
   :rtype: score (torch.Tensor)


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