https://github.com/shameempk/pyciede2000

Python library to calculate CIEDE2000 color difference.
https://github.com/shameempk/pyciede2000

ciede2000 color color-difference numpy pyciede2000 python

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Python library to calculate CIEDE2000 color difference.

• Host: GitHub
• URL: https://github.com/shameempk/pyciede2000
• Owner: shameempk
• License: mit
• Created: 2021-05-15T13:24:46.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2022-03-07T15:11:11.000Z (almost 3 years ago)
• Last Synced: 2025-01-14T12:38:58.029Z (2 days ago)
• Topics: ciede2000, color, color-difference, numpy, pyciede2000, python
• Language: Python
• Homepage:
• Size: 15.6 KB
• Stars: 14
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
**About**

Python implementation of CIEDE2000 color difference calculation based on this paper:

[The CIEDE2000 Color-Difference Formula: Implementation Notes, Supplementary Test Data, and Mathematical Observations](http://www2.ece.rochester.edu/~gsharma/ciede2000/ciede2000noteCRNA.pdf).

More info: http://www2.ece.rochester.edu/~gsharma/ciede2000/

Use this BibTeX to cite:

```BibTeX

@article{Sharma2005TheObservations,

    title = {{The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations}},

    year = {2005},

    journal = {Color Research {\&} Application},

    author = {Sharma, Gaurav and Wu, Wencheng and Dalal, Edul N},

    number = {1},

    month = {2},

    pages = {21--30},

    volume = {30},

    publisher = {Wiley Subscription Services, Inc., A Wiley Company},

    url = {http://dx.doi.org/10.1002/col.20070},

    doi = {10.1002/col.20070},

    issn = {1520-6378},

    keywords = {CIE, CIE94, CIEDE2000, CIELAB, CMC, color-difference metrics}

}

```

**Install**

`pip install pyciede2000`

**Usage**

```python

from pyciede2000 import ciede2000

res = ciede2000((50.0000,2.6772,-79.7751), (50.0000,0.0000,-82.7485))

print(res)

```

`ciede2000` accepts two color values as tuples in _Lab_ representation. Also supports optional keyword parameters for para-metric weighting factor `k_L`, `k_C` and `k_H`.

**Output format**

`ciede2000()` returns a dict with all significant fields in CIEDE2000 calculation.

```python

res = {

	"a_1_dash": a_1_dash,

	"a_2_dash": a_2_dash,

	"C_1_dash": C_1_dash,

	"C_2_dash": C_2_dash,

	"h_1_dash": h_1_dash,

	"h_2_dash": h_2_dash,

	"h_bar_dash": h_bar_dash,

	"G": G,

	"T": T,

	"S_L": S_L,

	"S_H": S_H,

	"S_C": S_C,

	"R_T": R_T,

	"delta_E_00": delta_E_00

}

```

You might be only interested in the final delta value, `delta_E_00`.

```

print(res['delta_E_00'])

```