============= color-matcher

Description

color-matcher enables color transfer across images which comes in handy for automatic color-grading of photographs, paintings and film sequences as well as light-field and stopmotion corrections. The methods behind the mappings are based on the approach from Reinhard et al., the Monge-Kantorovich Linearization (MKL) as proposed by Pitie et al. and our analytical solution to a Multi-Variate Gaussian Distribution (MVGD) transfer in conjunction with classical histogram matching. As shown below our HM-MVGD-HM compound outperforms existing methods.

|release| |license| |build_github| |coverage| |pypi_total| |pypi|

|binder|

Results

|vspace|

.. list-table:: :widths: 1 2 2 2 :header-rows: 1 :stub-columns: 1

• • Source
  • Target
  • Result
• • Photograph
  • |src_photo|
  • |ref_photo|
  • |res_photo|
• • Film sequence
  • |src_seq|
  • |ref_seq|
  • |res_seq|
• • Light-field correction
  • |src_lfp|
  • |ref_lfp|
  • |res_lfp|
• • Paintings
  • |src_paint|
  • |ref_paint|
  • |res_paint|

|

Installation

• via pip:

  1. install with pip3 install color-matcher
  2. type color-matcher -h to the command line once installation finished

• from source:

  1. install Python from https://www.python.org/
  2. download the source_ using git clone https://github.com/hahnec/color-matcher.git
  3. go to the root directory cd color-matcher
  4. load dependencies $ pip3 install -r requirements.txt
  5. install with python3 setup.py install
  6. if installation ran smoothly, enter color-matcher -h to the command line

CLI Usage

From the root directory of your downloaded repo, you can run the tool on the provided test data by

color-matcher -s './tests/data/scotland_house.png' -r './tests/data/scotland_plain.png'

on a UNIX system where the result is found at ./tests/data/. A windows equivalent of the above command is

color-matcher --src=".\\tests\\data\\scotland_house.png" --ref=".\\tests\\data\\scotland_plain.png"

Alternatively, you can specify the method or select your images manually with

color-matcher --win --method='hm-mkl-hm'

Note that batch processing is possible by passing a source directory, e.g., via

color-matcher -s './tests/data/' -r './tests/data/scotland_plain.png'

More information on optional arguments, can be found using the help parameter

color-matcher -h

API Usage

.. code-block:: python

from color_matcher import ColorMatcher
from color_matcher.io_handler import load_img_file, save_img_file, FILE_EXTS
from color_matcher.normalizer import Normalizer
import os

img_ref = load_img_file('./tests/data/scotland_plain.png')

src_path = '.'
filenames = [os.path.join(src_path, f) for f in os.listdir(src_path)
                     if f.lower().endswith(FILE_EXTS)]

cm = ColorMatcher()
for i, fname in enumerate(filenames):
    img_src = load_img_file(fname)
    img_res = cm.transfer(src=img_src, ref=img_ref, method='mkl')
    img_res = Normalizer(img_res).uint8_norm()
    save_img_file(img_res, os.path.join(os.path.dirname(fname), str(i)+'.png'))

.. Hyperlink aliases

.. _source: https://github.com/hahnec/color-matcher/archive/master.zip

.. |src_photo| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/scotland_house.png" max-width="100%">

.. |ref_photo| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/scotland_plain.png" max-width="100%">

.. |res_photo| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/scotland_pitie.png" max-width="100%">

.. |src_paint| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/parismusees/cezanne_paul_trois_baigneuses.png" max-width="100%">

.. |ref_paint| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/parismusees/cezanne_paul_portrait_dambroise_vollard.png" max-width="100%">

.. |res_paint| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/parismusees/cezanne_paul_trois_baigneuses_mvgd.png" max-width="100%">

.. |src_seq| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/wave.gif" max-width="100%">

.. |ref_seq| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/sunrise.png" max-width="100%">

.. |res_seq| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/wave_mvgd.gif" max-width="100%">

.. |src_lfp| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/view_animation_7px.gif" max-width="100%">

.. |ref_lfp| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/bee_2.png" max-width="100%">

.. |res_lfp| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/master/tests/data/view_animation_7px_hm-mkl-hm.gif" max-width="100%">

.. |vspace| raw:: latex

\vspace{1mm}

.. |metric_chart| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/develop/docs/img/hist+wasser_dist.svg" max-width="100%" align="center">

.. |metric_latex| raw:: latex

W_1 = \int_{0}^{\infty} \left| F\left(\mathbf{r}^{(g)}\right) - F\left(\mathbf{z}^{(g)}\right) \right|_1 \, \mathrm{d}k

D_2 = \left\| f(\mathbf{r}) - f(\mathbf{z}) \right\|_2

.. |metric_eqs| raw:: html

<img src="https://raw.githubusercontent.com/hahnec/color-matcher/develop/docs/img/distance_metrics.svg" max-width="100%" align="center">

.. Image substitutions

.. |release| image:: https://img.shields.io/github/v/release/hahnec/color-matcher?style=square :target: https://github.com/hahnec/color-matcher/releases/ :alt: release

.. |license| image:: https://img.shields.io/badge/License-GPL%20v3.0-orange.svg?style=square :target: https://www.gnu.org/licenses/gpl-3.0.en.html :alt: License

.. |build_travis| image:: https://img.shields.io/travis/com/hahnec/color-matcher?style=square :target: https://travis-ci.com/github/hahnec/color-matcher

.. |build_github| image:: https://img.shields.io/github/actions/workflow/status/hahnec/color-matcher/gh_actions.yml?branch=master&style=square :target: https://github.com/hahnec/color-matcher/actions :alt: GitHub Workflow Status

.. |coverage| image:: https://img.shields.io/coveralls/github/hahnec/color-matcher?style=square :target: https://coveralls.io/github/hahnec/color-matcher

.. |pypi| image:: https://img.shields.io/pypi/dm/color-matcher?label=PyPI%20downloads&style=square :target: https://pypi.org/project/color-matcher/ :alt: PyPI Downloads

.. |pypi_total| image:: https://pepy.tech/badge/color-matcher?style=flat-square :target: https://pepy.tech/project/color-matcher :alt: PyPi Dl2

.. |binder| image:: https://mybinder.org/badge_logo.svg :target: https://mybinder.org/v2/gh/hahnec/color-matcher/master?labpath=01_api_demo.ipynb

.. |paper| image:: http://img.shields.io/badge/paper-arxiv.2010.11687-red.svg?style=flat-square :target: https://arxiv.org/pdf/2010.11687.pdf :alt: arXiv link

Experimental results

|metric_chart|

The above diagram illustrates light-field color consistency from Wasserstein metric :math:W_1 and histogram distance :math:D_2 where low values indicate higher similarity between source :math:\mathbf{r} and target :math:\mathbf{z}. These distance metrics are computed as follows

|metric_eqs|

where :math:f(k,\cdot) and :math:F(k,\cdot) represent the Probability Density Function (PDF) and Cumulative Density Function (CDF) at intensity level :math:k, respectively. More detailed information can be found in our IEEE paper <https://arxiv.org/pdf/2010.11687.pdf>__.

|vspace|

Citation

.. code-block:: BibTeX

@ARTICLE{plenopticam,
    author={Hahne, Christopher and Aggoun, Amar},
    journal={IEEE Transactions on Image Processing},
    title={PlenoptiCam v1.0: A Light-Field Imaging Framework},
    year={2021},
    volume={30},
    number={},
    pages={6757-6771},
    doi={10.1109/TIP.2021.3095671}
}

Author

Christopher Hahne <http://www.christopherhahne.de/>__