FaceAI

This package is aim to make using Computer Vision simple as possible. FaceAI use 2 main features.

1. Creating a Vision Operations Pipe.
2. Creating a Stack Operation over desired photos.

Requirement

• iOS 13.0+
• Swift 5.1+
• Xcode 12.0+

Install

SPM:

dependencies: [
  .package(
      url:  "https://github.com/LA-Labs/FaceAI.git",
      .branch("master")
  )
]

Import

import FaceAI

Usage

Basic Usage

Fetch options

Firstly, FaceAI provides useful initializers to create asset fetching options using AssetFetchingOptions

// Create default fetch options
let options = AssetFetchingOptions()

We can custom AssetFetchingOptions with 3 properties:

• sortDescriptors: Ascending\Descending.
• assetCollection: Photos source.
• fetchLimit: Limit the amount of photos we are fetching.

let options = AssetFetchingOptions(sortDescriptors: [NSSortDescriptor]?,
                                   assetCollection: AssetCollection,
                                   fetchLimit: Int)

Asset Collections

public enum AssetCollection {
    case allAssets
    case albumName(_ name: String)
    case assetCollection(_ collection: PHAssetCollection)
    case identifiers(_ ids: [String])
}

Create filter

Next we need to create detection request with VFilter.

// Create image processing request
let faceRectangle = VFilter.faceRectangle()

Face detection

Call FaceAI detecotor with the filter request and fetch options.

FaceAI.detect(faceRectangle, with: options) { (result) in
   switch result {
   // The result type is ProcessedAsset
   // Containt all photos with face recatangle detection
   // photos[0].boundingBoxes
      case .success(let photos):
          print(photos)
      case .failure(let error):
          print(error)
   }
}

Multiple Requests

Creating a pipe process

// Creating Face rectangle dection
let faceRectangle = VFilter.faceRectangle()
        
// Creation Object Dection.
// Sky, flower, water etc.
let objectDetecting = VFilter.objectDetecting()

// Combine to pipe processing
// Every image will go through the pipe.
let pipeProcessing = faceRectangle |>> objectDetecting
FaceAI.detect(pipeProcessing, with: options) { (result) in
switch result {
   // The result type is ProcessedAsset
   // Containt all photos with face recatangle detection
   // photos[0].boundingBoxes
   // photos[0].tags
      case .success(let photos):
          print(photos)
      case .failure(let error):
          print(error)
   }
}

Face Grouping

Collect people faces into groups

// Create photo fetech options
let options = AssetFetchingOptions()
        
// Create cluster options
let clusterOptions = ClusterOptions()
FaceAI.cluster(fetchOptions: options,
               culsterOptions: clusterOptions) { (result) in
     // Result contian group faces
     // [Int: [Face]]
     // Key = group id
     // Value = Same people faces
     switch result {
        case .success(let faces):
           print(faces)
        case .failure(_):
           break
     }
}

Contributing

We don't have any contributing guidelines at the moment, but feel free to submit pull requests & file issues within GitHub!