Pailead works just like the Palette library on Android and other tools like node-vibrant but is completely written in Swift and optimized for macOS, iOS, tvOS, and even watchOS.
CocoaPods is a dependency manager for Cocoa projects. For usage and installation instructions, visit their website. To integrate Pailead into your Xcode project using CocoaPods, specify it in your Podfile:
pod "Pailead"
The Swift Package Manager is a tool for automating the distribution of Swift code and is integrated into the swift
compiler.
Once you have your Swift package set up, adding Pailead as a dependency is as easy as adding it to the dependencies
value of your Package.swift
.
dependencies: [
.package(url: "https://github.com/pducks32/Pailead.git", from: "1.4.0")
]
Carthage is a decentralized dependency manager that builds your dependencies and provides you with binary frameworks. To integrate Pailead into your Xcode project using Carthage, specify it in your Cartfile:
github "pducks32/Pailead"
All images are resized to 1000 pixels to speed up extraction, but don't worry this hasn't been shown to degrade the quality of the palette.
let image = <#Image#>
Pailead.extractPalette(from: image) { palette in
<#Do Something with Palette#>
}
The generated palette generates useful swatches to use in your UI or as a loading background perhaps. All swatches are actual colors found in the MMCQ calculation though it will generate some if no suitable ones can be found. These are:
That's a big word. The image's pixels are grouped and counted. Then they are laid out in RGB space. From there the quantizer finds RGB boxes that encapsulate the pixels equally. From these boxes the average color is generated and then sorted by how common it is in the image.
If palette is pronounced pa-let then Pailead is pronounced pa-lid.
The word comes from the Irish word paileΓ‘d meaning palette which is what this library extracts.
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