Perceptual Losses for Neural Networks: Caffe implementation of loss layers based on perceptual image quality metrics.
Switch branches/tags
Nothing to show
Clone or download
Permalink
Failed to load latest commit information.
src Initial commit of the loss layer function May 25, 2017
README.txt Updated the readme file. May 25, 2017

README.txt

# Copyright (c) 2017, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#  * Redistributions of source code must retain the above copyright
#    notice, this list of conditions and the following disclaimer.
#  * Redistributions in binary form must reproduce the above copyright
#    notice, this list of conditions and the following disclaimer in the
#    documentation and/or other materials provided with the distribution.
#  * Neither the name of NVIDIA CORPORATION nor the names of its
#    contributors may be used to endorse or promote products derived
#    from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Perceptual Losses for Neural Networks (PL4NN)

A Caffe implementation of the perceptual loss functions described in the paper:
"Loss Functions for Neural Networks for Image Processing", Hang Zhao, Orazio Gallo, Iuri Frosio, and Jan Kautz, IEEE Transactions on Computational Imaging, 2017.

Assuming that CAFFE_ROOT is Caffe's installation folder:

1) Copy loss.py to $CAFFE_ROOT/python
2) Add $CAFFE_ROOT/python to your Python path