参考：Face Detection in iOS Using Core Image
面部识别API不仅可以是识别面部，也可识别面部的特殊细节，例如微笑甚至眨眼睛。
建立初始项目
原文建好了初始项目，我自己新建了初始项目
- 新建项目Detector
- 删除IB中原本View Controller Scene。
- 拖动
UITabBarController到IB中，得到三个Scene。选择UITabBarController的Is Initial View Controller，使其作为初始控制器。 - 修改Item 1的title和其Bar Item都为Photo，修改其
Class为ViewController。 - 向Assets中添加几张人物图片
- 想Photo Scene中添加一个Image View，
Content Mode改为Aspect Fit，选择一个图片。在ViewController添加图片对应@IBOutlet：
@IBOutlet var personPic: UIImageView! - 选中Item 2，点击菜单栏EDitor > Embed In > Navigation Controller，新生成一个与之关联的Scene。
- 新建
CameraViewController类，继承至UIViewController。修改上面生成的Scene的Class属性为CameraViewController。 - 拖动一个
UIBarButtonItem到Camera View Controller Scene的UINavigationItem的右边，并选择System Item为Camera - 在
CameraViewController中建立outlet和Action
识别照片的面部
- 在
ViewController.swift中引入CoreImage:
import CoreImage - 在
ViewController.swift中添加函数detect():
func detect() {
// 1
guard let personciImage = CIImage(image: personPic.image!) else {
return
}
// 2
let accuracy = [CIDetectorAccuracy: CIDetectorAccuracyHigh]
let faceDetector = CIDetector(ofType: CIDetectorTypeFace, context: nil, options: accuracy)
let faces = faceDetector?.features(in: personciImage)
// 3
for face in faces as! [CIFaceFeature] {
print("Found bounds are \(face.bounds)")
let faceBox = UIView(frame: face.bounds)
faceBox.layer.borderWidth = 3
faceBox.layer.borderColor = UIColor.red.cgColor
faceBox.backgroundColor = UIColor.clear
personPic.addSubview(faceBox)
// 4
if face.hasLeftEyePosition {
print("Left eye bounds are \(face.leftEyePosition)")
}
if face.hasRightEyePosition {
print("Right eye bounds are \(face.rightEyePosition)")
}
}
}
- 1 根据
UIImage获取CoreImage中图片对象。guard与if功能类似，区别可查看以撸代码的形式学习Swift-5：Control Flow的6 guard 与 if。 - 2 初始化检测器
CIDetector，accuray是检查器配置选项，表示精确度；因为CIDetector可以进行几种类型的检测，所以CIDetectorTypeFace用来表示面部检测；features方法返回具体的检测结果 - 3 给每个检测到的脸添加红色框
- 4 检测是否有左眼位置
- 在
viewDidLoad中添加detect()，运行结果类似：
打印结果，显示检测到的面部位置是不对的：
Found bounds are (177.0, 416.0, 380.0, 380.0)
这是因为UIKit的坐标系统与Core Image的坐标系统是不同的：
- 把Core Image的坐标系统转换为UIKit的坐标系统，修改
detect()为：
func detect() {
guard let personciImage = CIImage(image: personPic.image!) else {
return
}
let accuracy = [CIDetectorAccuracy: CIDetectorAccuracyHigh]
let faceDetector = CIDetector(ofType: CIDetectorTypeFace, context: nil, options: accuracy)
let faces = faceDetector?.features(in: personciImage)
//
let ciImageSize = personciImage.extent.size
var transform = CGAffineTransform(scaleX: 1, y: -1)
transform = transform.translatedBy(x: 0, y: -ciImageSize.height)
for face in faces as! [CIFaceFeature] {
print("Found bounds are \(face.bounds)")
// Apply the transform to convert the coordinates
var faceViewBounds = face.bounds.applying(transform)
// Calculate the actual position and size of the rectangle in the image view
let viewSize = personPic.bounds.size
let scale = min(viewSize.width / ciImageSize.width,
viewSize.height / ciImageSize.height)
let offsetX = (viewSize.width - ciImageSize.width * scale) / 2
let offsetY = (viewSize.height - ciImageSize.height * scale) / 2
faceViewBounds = faceViewBounds.applying(CGAffineTransform(scaleX: scale, y: scale))
faceViewBounds.origin.x += offsetX
faceViewBounds.origin.y += offsetY
let faceBox = UIView(frame: faceViewBounds)
faceBox.layer.borderWidth = 3
faceBox.layer.borderColor = UIColor.red.cgColor
faceBox.backgroundColor = UIColor.clear
personPic.addSubview(faceBox)
if face.hasLeftEyePosition {
print("Left eye bounds are \(face.leftEyePosition)")
}
if face.hasRightEyePosition {
print("Right eye bounds are \(face.rightEyePosition)")
}
}
}
运行可看到正确识别位置：
相机拍照后的脸部识别
之前是项目中照片识别，现在是拍完照再识别，原理是相同的，就是多一个拍完照，取照片的过程。
- 更新
CameraViewController类的代码
// 1
class CameraViewController: UIViewController, UIImagePickerControllerDelegate, UINavigationControllerDelegate {
@IBOutlet var imageView: UIImageView!
// 2
let imagePicker = UIImagePickerController()
override func viewDidLoad() {
super.viewDidLoad()
imagePicker.delegate = self
}
@IBAction func takePhoto(_ sender: AnyObject) {
// 3
if !UIImagePickerController.isSourceTypeAvailable(.camera) {
return
}
imagePicker.allowsEditing = false
imagePicker.sourceType = .camera
present(imagePicker, animated: true, completion: nil)
}
// 4
//MARK: -UIImagePickerControllerDelegate
func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {
if let pickedImage = info[UIImagePickerControllerOriginalImage] as? UIImage {
imageView.contentMode = .scaleAspectFit
imageView.image = pickedImage
}
dismiss(animated: true, completion: nil)
self.detect()
}
// 5
func imagePickerControllerDidCancel(_ picker: UIImagePickerController) {
dismiss(animated: true, completion: nil)
}
}
- 1 实现
UIImagePickerControllerDelegate协议，用于拍照相关代理。 - 2 初始化
UIImagePickerController。UIImagePickerController是照相或摄影界面和功能管理的类。 - 3 判断设备照相机是否可用。
- 4 实现一个
UIImagePickerControllerDelegate中的代理方法，当拍摄完备确实使用照片时调用。 - 5 也是
UIImagePickerControllerDelegate中的代理方法，取消拍摄时调用。
- 添加
detect()代码，与ViewController中不同的是，不用红色框框处识别出的面部，而是识别出面部的细节，并用UIAlertController弹出显示。
func detect() {
let imageOptions = NSDictionary(object: NSNumber(value: 5) as NSNumber, forKey: CIDetectorImageOrientation as NSString)
let personciImage = CIImage(cgImage: imageView.image!.cgImage!)
let accuracy = [CIDetectorAccuracy: CIDetectorAccuracyHigh]
let faceDetector = CIDetector(ofType: CIDetectorTypeFace, context: nil, options: accuracy)
let faces = faceDetector?.features(in: personciImage, options: imageOptions as? [String : AnyObject])
if let face = faces?.first as? CIFaceFeature {
print("found bounds are \(face.bounds)")
var message = "有个脸"
if face.hasSmile {
print("脸是笑的")
message += ",脸是笑的"
}
if face.hasMouthPosition {
print("有嘴唇")
message += ",有嘴唇"
}
if face.hasLeftEyePosition {
print("左眼镜的位置是 \(face.leftEyePosition)")
message += ",左眼镜的位置是 \(face.leftEyePosition)"
}
if face.hasRightEyePosition {
print("右眼镜的位置是 \(face.rightEyePosition)")
message += ",右眼镜的位置是 \(face.rightEyePosition)"
}
let alert = UIAlertController(title: "嘿嘿", message: message, preferredStyle: .alert)
alert.addAction(UIAlertAction(title: "OK", style: .default, handler: nil))
self.present(alert, animated: true, completion: nil)
} else {
let alert = UIAlertController(title: "没脸了", message: "没有检测到脸", preferredStyle: .alert)
alert.addAction(UIAlertAction(title: "OK", style: .default, handler: nil))
self.present(alert, animated: true, completion: nil)
}
}
运行就可以识别照片的面部具体细节
CIFaceFeature还提供了其他很多面部细节：
open var hasLeftEyePosition: Bool { get }
open var leftEyePosition: CGPoint { get }
open var hasRightEyePosition: Bool { get }
open var rightEyePosition: CGPoint { get }
open var hasMouthPosition: Bool { get }
open var mouthPosition: CGPoint { get }
open var hasTrackingID: Bool { get }
open var trackingID: Int32 { get }
open var hasTrackingFrameCount: Bool { get }
open var trackingFrameCount: Int32 { get }
open var hasFaceAngle: Bool { get }
open var faceAngle: Float { get }
open var hasSmile: Bool { get }
open var leftEyeClosed: Bool { get }
open var rightEyeClosed: Bool { get }
代码
Detector