https://github.com/mccutchen/palettor
Yet another way to extract the color palette from an image using k-means clustering
https://github.com/mccutchen/palettor
color-palette golang image-processing kmeans-clustering
Last synced: 3 months ago
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Yet another way to extract the color palette from an image using k-means clustering
- Host: GitHub
- URL: https://github.com/mccutchen/palettor
- Owner: mccutchen
- License: mit
- Created: 2015-07-18T01:07:51.000Z (almost 10 years ago)
- Default Branch: main
- Last Pushed: 2023-03-17T17:32:19.000Z (over 2 years ago)
- Last Synced: 2024-06-19T02:11:06.494Z (about 1 year ago)
- Topics: color-palette, golang, image-processing, kmeans-clustering
- Language: Go
- Homepage: https://pkg.go.dev/github.com/mccutchen/palettor
- Size: 310 KB
- Stars: 19
- Watchers: 2
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Palettor
Yet another way to extract dominant colors from an image using [k-means clustering][1].
[](https://pkg.go.dev/github.com/mccutchen/palettor)
[](https://github.com/mccutchen/palettor/actions/workflows/test.yaml)
[](https://codecov.io/gh/mccutchen/palettor)
[](https://goreportcard.com/report/github.com/mccutchen/palettor)
## Tests
### Unit tests
```
make test
```
### Benchmarks
```
make benchmark
```
## Usage as a library
```
go get -u github.com/mccutchen/palettor
```
```go
package main
import (
"image"
_ "image/gif"
_ "image/jpeg"
_ "image/png"
"log"
"os"
"github.com/mccutchen/palettor"
"github.com/nfnt/resize"
)
func main() {
// Read an image from STDIN
originalImg, _, err := image.Decode(os.Stdin)
if err != nil {
log.Fatal(err)
}
// Reduce it to a manageable size
img := resize.Thumbnail(200, 200, originalImg, resize.Lanczos3)
// Extract the 3 most dominant colors, halting the clustering algorithm
// after 100 iterations if the clusters have not yet converged.
k := 3
maxIterations := 100
palette, err := palettor.Extract(k, maxIterations, img)
// Err will only be non-nil if k is larger than the number of pixels in the
// input image.
if err != nil {
log.Fatalf("image too small")
}
// Palette is a mapping from color to the weight of that color's cluster,
// which can be used as an approximation for that color's relative
// dominance
for _, color := range palette.Colors() {
log.Printf("color: %v; weight: %v", color, palette.Weight(color))
}
// Example output:
// 2015/07/19 10:27:52 color: {44 120 135}; weight: 0.17482142857142857
// 2015/07/19 10:27:52 color: {140 103 150}; weight: 0.39558035714285716
// 2015/07/19 10:27:52 color: {189 144 118}; weight: 0.42959821428571426
}
```
## The `palettor` command line application
An example command line application is provided, which reads an input image and
either a) overlays the dominant palette on the bottom of the image or b)
generates a JSON representation of the dominant color palette:
```
$ go get -u github.com/mccutchen/palettor/cmd/palettor
$ palettor -help
Usage: palettor [OPTIONS] [INPUT]
-json
Output color palette in JSON format
-k int
Palette size (default 3)
-max int
Maximum k-means iterations (default 500)
$ cat /Library/Desktop\ Pictures/Beach.jpg | palettor -json | jq .
[
{
"color": {
"R": 70,
"G": 134,
"B": 154,
"A": 255
},
"weight": 0.19080357142857143
},
{
"color": {
"R": 175,
"G": 187,
"B": 183,
"A": 255
},
"weight": 0.26852678571428573
},
{
"color": {
"R": 210,
"G": 208,
"B": 199,
"A": 255
},
"weight": 0.5406696428571428
}
]
```
[1]: https://en.wikipedia.org/wiki/K-means_clustering#Standard_algorithm