https://github.com/dstein64/colortrans
An implementation of various color transfer algorithms.
https://github.com/dstein64/colortrans
color-transfer
Last synced: 9 months ago
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An implementation of various color transfer algorithms.
- Host: GitHub
- URL: https://github.com/dstein64/colortrans
- Owner: dstein64
- License: mit
- Created: 2022-03-03T01:03:30.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-03-17T00:14:06.000Z (over 2 years ago)
- Last Synced: 2024-10-23T03:26:54.941Z (over 1 year ago)
- Topics: color-transfer
- Language: Python
- Homepage:
- Size: 40 KB
- Stars: 17
- Watchers: 3
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
[![build][badge_thumbnail]][badge_link]
# colortrans
An implementation of various algorithms for transferring the colors from a reference image to a
content image while preserving the qualitative appearance of the content image (i.e., color
transfer).
Installation
------------
#### Requirements
- Python 3.8 or greater (earlier versions may work, but are not tested)
#### Install
```sh
$ pip3 install colortrans
```
#### Update
```sh
$ pip3 install --upgrade colortrans
```
Command-Line Usage
------------------
The program can be used from the command line.
The general command line usage is shown below.
```sh
$ colortrans [--method METHOD] [--single-precision] CONTENT REFERENCE OUTPUT
```
`CONTENT` is the path to the content image, `REFERENCE` is the path to the style image, and `OUTPUT`
is the path to save the output image.
`METHOD` specifies the color transfer algorithm. The following methods are supported:
1. `lhm` Linear Histogram Matching [1] (default)
2. `pccm` Principal Components Color Matching [2, 3]
3. `reinhard` Reinhard et al. [4]
If the optional `--single-precision` flag is present, 32-bit floats will be used instead of 64-bit floats.
If the launcher script was not installed within a directory on your PATH, colortrans can be launched by
passing its module name to Python.
```sh
$ python3 -m colortrans [--method METHOD] CONTENT REFERENCE OUTPUT
```
Library Usage
-------------
The algorithms can also be used directly from Python programs. Each of the methods listed above has
a corresponding function, `transfer_METHOD`, taking two NumPy arrays corresponding to the content
and reference image, respectively. The arrays have `HxWxC` data ordering (channels-last). The functions
also take an optional keyword argument, `single_precision`, a boolean that specifies whether 32-bit
floats will be used instead of 64-bit floats (defaults to `False`).
#### Example
```python
import colortrans
import numpy as np
from PIL import Image
# Load data
with Image.open('/path/to/content.jpg') as img:
content = np.array(img.convert('RGB'))
with Image.open('/path/to/reference.jpg') as img:
reference = np.array(img.convert('RGB'))
# Transfer colors using different algorithms
output_lhm = colortrans.transfer_lhm(content, reference)
output_pccm = colortrans.transfer_pccm(content, reference)
output_reinhard = colortrans.transfer_reinhard(content, reference)
# Save outputs
Image.fromarray(output_lhm).save('/path/to/output_lhm.jpg')
Image.fromarray(output_pccm).save('/path/to/output_pccm.jpg')
Image.fromarray(output_reinhard).save('/path/to/output_reinhard.jpg')
```
References
----------
[1] Hertzmann, Aaron. "Algorithms for Rendering in Artistic Styles." Ph.D., New York University,
2001.
[2] Kotera, Hiroaki, Hung-Shing Chen, and Tetsuro Morimoto. "Object-to-Object Color Mapping by Image
Segmentation." In Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts IV,
3648:148–57. SPIE, 1998.
[3] Kotera, Hiroaki. "A Scene-Referred Color Transfer for Pleasant Imaging on Display." In IEEE
International Conference on Image Processing 2005, 2:II–5, 2005.
[4] Reinhard, Erik, Michael Adhikhmin, Bruce Gooch, and Peter Shirley. "Color Transfer between
Images." IEEE Computer Graphics and Applications 21, no. 5 (July 2001): 34–41.
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