Library is focused on vision features, it is a part of Elkyc ecosystem.

• Features
• Component Libraries
• Requirements
• Installation
• Usage
• Predefined steps

Features

• Face Liveness detection
• Face Matching
• Face Capture

Component Libraries

ElkycFaceSDK does not have any components but it is dependent on ElkycCoreSDK

Requirements

• iOS 11.0+
• Xcode 11+
• Swift 5.1+

Permissions

Camera

This is achieved easily by adding the NSCameraUsageDescription key to the Info.plist along with usage description string. This usage string is displayed when the user is asked to allow access, so localization may be desired depending on your user base.

Installation

CocoaPods

CocoaPods is a dependency manager for Cocoa projects. For usage and installation instructions, visit their website. To integrate ElkycFaceSDK into your Xcode project using CocoaPods, specify it in your Podfile:

source 'git@github.com:elkyc/ElkycPodsRepo.git'

pod 'ElkycFaceSDK'

Swift Package Manager

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 ElkycFaceSDK as a dependency is as easy as adding it to the dependencies value of your Package.swift.

dependencies: [
    .package(url: "https://github.com/elkyc/ElkycCoreSDK.git", .branch("main")),
    .package(url: "https://github.com/elkyc/ElkycFaceSDK.git", .branch("main")),
    .package(url: "https://github.com/elkyc/ElkycDocumentTools.git", .branch("main"))
]

Manually

If you prefer not to use any of the aforementioned dependency managers, you can integrate ElkycFaceSDK into your project manually.

• Open up Terminal, cd into your directory, and run the following:

  $ git clone git@github.com:elkyc/ElkycFaceSDK ElkycFaceSDK

• Open the new ElkycFaceSDK folder, and drag the ElkycFaceSDK.xcframework into the Project Navigator of your application's Xcode project.

Usage

Introduction

ElkycFaceSDK will help you to verify the person in comparison to his documents for example, the goal is to build easy steps which you can run and get the result to your system or in your application.

Don't forget that framework depends on ElkycCoreSDK. Please read the documentation there first.

The whole process is going synchronously from the first to the last step. During the process, data will be sent to our or your backend. The process will stop if any of the steps will return an error.

Predefined steps

In this section, I will describe all available steps in the current framework, their configs and will show how they look like.

Right now all steps localized in Russian and English.

FaceCapturing

Use this step if you want to capture person face.

Output:

UIImage with person's face.

FaceMatching

This step matches two faces. You as well can specify sourceType for the image. This step does not have any UI and does async work, be aware of this, maybe you want to show some additional progress indicator.

Input:

• firstImage: InputImage, secondImage: InputImage

public struct InputImage {
	public enum `Type` {
		case printed
		case rfid
		case live
		case liveWithDoc
	}

	public let image: UIImage
	public let type: Type
}

Output:

Response struct with input images, isMatched flag and similarity value.

public struct Response {
	public let firstImage: UIImage
	public let secondImage: UIImage
	public let isMatched: Bool
	public let similarity: Double
}

FaceLiveness

If you want to understand is person alive or not, then this step is for you. It will ask person to do two pictures and returns the result for you.

Input:

• attemptsCount, the number of attempts to try.
• isRequired, if false after number of attempts user can skip this step.

Output:

Response struct with person's photo and isLive flag

public struct Response {
	public let image: UIImage?
	public let isLive: Bool
  public let guid: String?
}