# Copyright or © or Copr. IETR/INSA Rennes (2019)
#
# Contributors :
# Eduardo Fernandes-Montesuma eduardo.fernandes-montesuma@insa-rennes.fr (2019)
# Florian Lemarchand florian.lemarchand@insa-rennes.fr (2019)
#
#
# OpenDenoising is a computer program whose purpose is to benchmark image
# restoration algorithms.
#
# This software is governed by the CeCILL-C license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/ or redistribute the software under the terms of the CeCILL-C
# license as circulated by CEA, CNRS and INRIA at the following URL
# "http://www.cecill.info".
#
# As a counterpart to the access to the source code and rights to copy,
# modify and redistribute granted by the license, users are provided only
# with a limited warranty and the software's author, the holder of the
# economic rights, and the successive licensors have only limited
# liability.
#
# In this respect, the user's attention is drawn to the risks associated
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# software by the user in light of its specific status of free software,
# that may mean that it is complicated to manipulate, and that also
# therefore means that it is reserved for developers and experienced
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# encouraged to load and test the software's suitability as regards their
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# same conditions as regards security.
#
# The fact that you are presently reading this means that you have had
# knowledge of the CeCILL-C license and that you accept its terms.
from abc import ABC, abstractmethod
[docs]class AbstractDenoiser(ABC):
"""Common interface for Denoiser classes. This class defines the basic functionalities that a Denoiser needs to
have, such as __call__ function, which takes as input a noised image, and returns its reconstruction.
Attributes
----------
model_name : string
Model string identifier.
"""
[docs] def __init__(self, model_name="DenoisingModel"):
self.model_name = model_name
super().__init__()
[docs] def __str__(self):
"""Returns denoising model name."""
return self.model_name
[docs] @abstractmethod
def __call__(self, image):
"""Denoises a given image.
Parameters
----------
image : :class:`numpy.ndarray`
Batch of noisy images. Expected a 4D array with shape (batch_size, height, width, channels).
Returns
-------
"""
pass