https://github.com/jrosebr1/color_transfer

Performs color transfer between two images. Loosely based on the "Color Transfer between Images" paper by Reinhard et al., 2001.
https://github.com/jrosebr1/color_transfer

Last synced: 4 months ago
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Performs color transfer between two images. Loosely based on the "Color Transfer between Images" paper by Reinhard et al., 2001.

• Host: GitHub
• URL: https://github.com/jrosebr1/color_transfer
• Owner: jrosebr1
• License: mit
• Created: 2014-06-24T20:06:00.000Z (about 11 years ago)
• Default Branch: master
• Last Pushed: 2020-01-06T23:46:34.000Z (over 5 years ago)
• Last Synced: 2025-03-05T01:06:14.002Z (4 months ago)
• Language: Python
• Homepage: http://www.pyimagesearch.com/2014/06/30/super-fast-color-transfer-images/
• Size: 2.89 MB
• Stars: 501
• Watchers: 20
• Forks: 148
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
Super fast color transfer between images

==============

The color_transfer package is an OpenCV and Python implementation based (loosely) on [*Color Transfer between Images*](http://www.thegooch.org/Publications/PDFs/ColorTransfer.pdf) [Reinhard et al., 2001] The algorithm itself is extremely efficient (much faster than histogram based methods), requiring only the mean and standard deviation of pixel intensities for each channel in the L\*a\*b\* color space.

For more information, along with a detailed code review, [take a look at this post on my blog](http://www.pyimagesearch.com/2014/06/30/super-fast-color-transfer-images/).

#Requirements

- OpenCV

- NumPy

#Install

To install, make sure you have installed NumPy and compiled OpenCV with Python bindings enabled.

From there, there easiest way to install is via pip:

$ pip install color_transfer

#Examples

Below are some examples showing how to run the example.py demo and the associated color transfers between images.

$ python example.py --source images/autumn.jpg --target images/fallingwater.jpg

![Autumn and Fallingwater screenshot](docs/images/autumn_fallingwater.png?raw=true)

$ python example.py --source images/woods.jpg --target images/storm.jpg

![Woods and Storm screenshot](docs/images/woods_storm.png?raw=true)

$ python example.py --source images/ocean_sunset.jpg --target images/ocean_day.jpg

![Sunset and Ocean screenshot](docs/images/sunset_ocean.png?raw=true)