YotiFaceCapture

YotiFaceCapture provides a simplified way of capturing a face. It performs face detection from the front facing camera, analyses those frames and produces an optimised cropped image of the captured face.

Requirements

• iOS 13.0+
• Swift 5.5+
• ~75KB • YotiFaceCapture uses native APIs for feature detection and image processing, thus keeping our library small

Installation

Make sure you've installed and are running the latest version of:

• CocoaPods (Optional)
• Carthage (Optional)

CocoaPods

Add the following to your Podfile and run pod install from its directory:

platform :ios, '13.0'

target 'TargetName' do
  use_frameworks!
  pod 'YotiFaceCapture'
end

Carthage

1. Locate the necessary files

Please refer to the Installation folder of this repository, and locate the Cartfile, Input.xcfilelist and Output.xcfilelist.

2. Build dependencies

Add the Cartfile to the root of your project directory, and run carthage bootstrap from there.

3. Copy frameworks

On your application targets' Build Phases tab:

• Click + icon and choose New Run Script Phase
• Create a script with a shell of your choice (e.g. /bin/sh)
• Add the following to the script area below the shell:

/usr/local/bin/carthage copy-frameworks

• Add the Input.xcfilelist to the Input File Lists section of the script
• Add the Output.xcfilelist to the Output File Lists section of the script

Integration

1. Import frameworks

Import the framework in your implementation:

import YotiFaceCapture

2. Create FaceCaptureViewController

Fetch FaceCaptureViewController from framework and set delegate

let faceCaptureViewController = FaceCapture.faceCaptureViewController()
faceCaptureViewController.delegate = self

3. Start camera feed and analysis

Start the camera feed

faceCaptureViewController.startCamera()

Start the analysis

faceCaptureViewController.startAnalyzing(withConfiguration: .default)

Whenever required, both camera feed and analysis process can be stopped

faceCaptureViewController.stopCamera()
faceCaptureViewController.stopAnalyzing()

4. Receive the capture state and analysis results

Conform to FaceCaptureViewDelegate

func faceCaptureStateDidChange(to state: FaceCaptureState) {
    switch state {
        case .cameraReady:
            break
        case .analyzing:
            break
        case .cameraStopped:
            break
    }
}

func faceCaptureStateFailed(withError error: FaceCaptureStateError) {
    switch error {
        case .cameraNotAccessible:
            break
        case .cameraInitializingError:
            break
        case .invalidState:
            break
    }
}

func faceCaptureDidAnalyzeImage(_ originalImage: UIImage?, withAnalysis analysis: FaceCaptureAnalysis) {

}

func faceCaptureDidAnalyzeImage(_ originalImage: UIImage?, withError error: FaceCaptureAnalysisError) {
    switch error {
        case .faceAnalysisFailed:
            break
        case .noFaceDetected:
            break
        case .multipleFaces:
            break
        case .eyesNotOpen:
            break
        case .faceTooSmall:
            break
        case .faceTooBig:
            break
        case .faceNotCentered:
            break
        case .faceNotStable:
            break
        case .faceNotStraight:
            break
        case .environmentTooDark:
            break
    }
}

5. Configure the capture

Provide a Configuration instance when calling the startAnalyzing method

let faceCaptureConfiguration = Configuration(faceCenter: CGPoint(x: 0.5, y: 0.5),
                                             imageQuality: .medium,
                                             validationOptions: [.faceNotStraight])
faceCaptureViewController.startAnalyzing(withConfiguration: faceCaptureConfiguration)    

The faceCenter parameter is the normalised point, in relation to faceCaptureViewController.view, where you expect the centre of the detected face to be.
The frame of the detected face is returned by FaceCaptureViewDelegate in originalImageFaceCoordinates as part of FaceCaptureAnalysis.
The analysis will return a faceNotCentered error if the distance between the two points is significant.

Examples:

1. The faceCenter is configured to be CGPoint(x: 0.5, y: 0.45), represented by the intersection of the red and blue lines in the image below.
   The centre of the detected face should be positioned in the vicinity of that point to result in a valid capture.

2. The reference shape has been moved up and the faceCenter is now configured to CGPoint(x: 0.5, y: 0.35).

The validation options available are:

case eyesNotOpen
case faceNotStraight
case faceNotStable(requiredFrames: Int)
case environmentTooDark

Support

If you have any other questions please do not hesitate to contact [email protected]. Once we have answered your question we may contact you again to discuss Yoti products and services. If you'd prefer us not to do this, please let us know when you e-mail us.