An image compositing framework written in Swift.

An asynchronous, multithreaded, image compositing framework written in Swift.

Installation

CocoaPods

Add Overlay to your Podfile:

pod 'OverlayComposite'

And run pod install

Usage

Quick Start

Creating Layers

Overlay works using the concept of layered images. Each layer represents an individual image that can then be added atop another layer. You can think of this like layers in Photoshop, or similar image editor.

For example, take the following model:

• Layer 0: A large blue square
• Layer 1: A medium orange triangle
• Layer 2: A small green polygon

Technical Note: For this guide, we will assume that these images are named "Square", "Triangle", and "Polygon" in our app's Asset Catalog, and they are all formatted as PNG images with a transparent background.

A collection of images organized into layers is represented in code using the Layers class.

// Create a dictionary of all the images and layers we want to create.
// This will then be passed to Layers
let layerDictionary: [Int: String] =
[
  0: "Square",
  1: "Triangle",
  2: "Polygon"
]

// Create the new layers object.
guard let layers = try? Layers(named: layerDictionary) else {
  // Some error occurred
  return
}

Alternatively, you could create a dictionary using UIImage objects:

let layerDictionary: [Int: UIImage]

And pass it to Layers.init(with:)

Now we have a layered image represented in Swift!

Rendering Layers

Of course, we want to be able to use our new composite image. To do that we use OverlayRenderer

// Create a new renderer
let renderer = OverlayRenderer()

renderer.composite(from: layers) { result in
  // Here we can access the completed render
}

The result:

To see this in action, check out the Sample App included in the source code.

Layer Operations

You can insert, append, and remove layers from a Layers object. See the Layers Guide

API Documentation

Contributing

Pull Requests

If you wish to contribute to Overlay, create a new branch, implement your feature or fix, and then submit a pull request.

Documentation

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