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https://github.com/philoj/tree-palette
An indexed color palette implementation in Go on top of a k-d tree for fast color lookups. Also rank a palette against an image to identify prominent colors.
https://github.com/philoj/tree-palette
color color-analysis dominant-color go golang image-procesing image-processing kd-tree nearest-neighbor-search palette prominent-colors rgba tree-structure
Last synced: about 2 months ago
JSON representation
An indexed color palette implementation in Go on top of a k-d tree for fast color lookups. Also rank a palette against an image to identify prominent colors.
- Host: GitHub
- URL: https://github.com/philoj/tree-palette
- Owner: philoj
- License: apache-2.0
- Created: 2021-02-03T07:24:01.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2021-02-05T08:39:16.000Z (almost 4 years ago)
- Last Synced: 2024-08-03T23:30:32.115Z (5 months ago)
- Topics: color, color-analysis, dominant-color, go, golang, image-procesing, image-processing, kd-tree, nearest-neighbor-search, palette, prominent-colors, rgba, tree-structure
- Language: Go
- Homepage:
- Size: 275 KB
- Stars: 6
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-golang-repositories - tree-palette - d tree for fast color lookups. Also rank a palette against an image to identify prominent colors. (Repositories)
README
# treepalette
[](https://godoc.org/github.com/philoj/tree-palette)
[](https://travis-ci.com/github/philoj/tree-palette)
[](https://codecov.io/gh/philoj/tree-palette)
[](https://goreportcard.com/report/github.com/philoj/tree-palette)
[](https://github.com/kyroy/kdtree/blob/master/LICENSE)
An indexed color palette implementation in Go on top of a [k-d tree](https://en.wikipedia.org/wiki/K-d_tree) for fast color lookups. Also rank a palette against an image to identify prominent colors.
- Transparent(RGBA) and opaque(RGB) palettes
- Direct image conversion
- Image pixel counting and color ranking, for prominent color analysis
kd-tree implementation adapted from: [kyroy/kdtree](https://github.com/kyroy/kdtree)
## Usage
```bash
go get github.com/philoj/tree-palette
```
```go
import "github.com/philoj/tree-palette"
````
### Create a color model for color lookups.
```go
m := NewPalettedColorModel([]color.Color{
// list of colors in the palette
}, false // ignore alpha values
)
equivalentColor := m.Convert(someColor)
```
### Color ranking and image color analysis
Start by implementing `treepalette.PaletteColor` and `treepalette.Color` interfaces:
```go
// Color express A color as A n-dimensional point in the RGBA space for usage in the kd-tree search algorithm.
type Color interface {
// Dimensions returns the total number of dimensions(3 for RGB, 4 for RGBA).
Dimensions() int
// Dimension returns the value of the i-th dimension, say R,G,B and/or A.
Dimension(i int) uint32
}
// PaletteColor is A Color inside an indexed color palette.
type PaletteColor interface {
Color
// Index returns palette index of the color
Index() int
}
```
Or use included implementations `treepalette.ColorRGBA` and `treepalette.IndexedColorRGBA` respectively:
```go
// Unknown color
c := treepalette.NewOpaqueColor(121,201,10)
// Palette colors
p1 := treepalette.NewOpaquePaletteColor(255, 130, 1, 2, "DARK ORANGE") // R,G,B, unique-id, name
p2 := treepalette.NewOpaquePaletteColor(1, 128, 181, 11, "PACIFIC BLUE")
// Create palette
palette := treepalette.NewPalette([]treepalette.PaletteColor{p1,p2}, false)
// Equivalent color
equivalent := palette.Convert(c)
// Convert an image.Image
palettedImage := palette.ApplyPalette(img)
// Rank the palette against all the pixels in an image.Image
colors, colorCount := palette.Rank(img)
fmt.Printf("Most frequent color is %s. It appears %d times.", colors[0], colorCount[colors[0].Index()])
```