IOS 通过摄像头读取每一帧的图片，并且做识别做人脸识别(swift)

最近帮别人做一个项目，主要是使用摄像头做人脸识别

github地址：https://github.com/qugang/AVCaptureVideoTemplate

要使用IOS的摄像头，需要使用AVFoundation 库，库里面的东西我就不介绍。

启动摄像头需要使用AVCaptureSession 类。

然后得到摄像头传输的每一帧数据，需要使用AVCaptureVideoDataOutputSampleBufferDelegate 委托。

首先在viewDidLoad 里添加找摄像头设备的代码，找到摄像头设备以后，开启摄像头

captureSession.sessionPreset = AVCaptureSessionPresetLow let devices = AVCaptureDevice.devices() for device in devices {  if (device.hasMediaType(AVMediaTypeVideo)) {   if (device.position == AVCaptureDevicePosition.Front) {    captureDevice = device as?AVCaptureDevice    if captureDevice != nil {     println("Capture Device found")     beginSession()    }   }  } } 

beginSession,开启摄像头：

func beginSession() {  var err : NSError? = nil  captureSession.addInput(AVCaptureDeviceInput(device: captureDevice, error: &err))  let output = AVCaptureVideoDataOutput()  let cameraQueue = dispatch_queue_create("cameraQueue", DISPATCH_QUEUE_SERIAL)  output.setSampleBufferDelegate(self, queue: cameraQueue)  output.videoSettings = [kCVPixelBufferPixelFormatTypeKey: kCVPixelFormatType_32BGRA]  captureSession.addOutput(output)  if err != nil {   println("error: /(err?.localizedDescription)")  }  previewLayer = AVCaptureVideoPreviewLayer(session: captureSession)  previewLayer?.videoGravity = "AVLayerVideoGravityResizeAspect"  previewLayer?.frame = self.view.bounds  self.view.layer.addSublayer(previewLayer)  captureSession.startRunning() } 

开启以后，实现captureOutput 方法：

func captureOutput(captureOutput: AVCaptureOutput!, didOutputSampleBuffer sampleBuffer: CMSampleBuffer!, fromConnection connection: AVCaptureConnection!) {  if(self.isStart)  {   let resultImage = sampleBufferToImage(sampleBuffer)   let context = CIContext(options:[kCIContextUseSoftwareRenderer:true])   let detecotr = CIDetector(ofType:CIDetectorTypeFace,  context:context, options:[CIDetectorAccuracy: CIDetectorAccuracyHigh])   let ciImage = CIImage(image: resultImage)   let results:NSArray = detecotr.featuresInImage(ciImage,options: ["CIDetectorImageOrientation" : 6])   for r in results {    let face:CIFaceFeature = r as! CIFaceFeature;    let faceImage = UIImage(CGImage: context.createCGImage(ciImage, fromRect: face.bounds),scale: 1.0, orientation: .Right)    NSLog("Face found at (%f,%f) of dimensions %fx%f", face.bounds.origin.x, face.bounds.origin.y,pickUIImager.frame.origin.x, pickUIImager.frame.origin.y)    dispatch_async(dispatch_get_main_queue()) {     if (self.isStart)     {      self.dismissViewControllerAnimated(true, completion: nil)      self.didReceiveMemoryWarning()      self.callBack!(face: faceImage!)     }     self.isStart = false    }   }  } } 

在每一帧图片上使用CIDetector 得到人脸，CIDetector 还可以得到眨眼，与微笑的人脸，如果要详细使用去官方查看API

上面就是关键代码，设置了有2秒的延迟，2秒之后开始人脸检测。

全部代码：

// //  ViewController.swift //  AVSessionTest // //  Created by qugang on 15/7/8. //  Copyright (c) 2015年 qugang. All rights reserved. //  import UIKit import AVFoundation class AVCaptireVideoPicController: UIViewController,AVCaptureVideoDataOutputSampleBufferDelegate {  var callBack :((face: UIImage) ->())?  let captureSession = AVCaptureSession()  var captureDevice : AVCaptureDevice?  var previewLayer : AVCaptureVideoPreviewLayer?  var pickUIImager : UIImageView = UIImageView(image: UIImage(named: "pick_bg"))  var line : UIImageView = UIImageView(image: UIImage(named: "line"))  var timer : NSTimer!  var upOrdown = true  var isStart = false  override func viewDidLoad() {   super.viewDidLoad()   captureSession.sessionPreset = AVCaptureSessionPresetLow   let devices = AVCaptureDevice.devices()   for device in devices {    if (device.hasMediaType(AVMediaTypeVideo)) {     if (device.position == AVCaptureDevicePosition.Front) {      captureDevice = device as?AVCaptureDevice      if captureDevice != nil {       println("Capture Device found")       beginSession()      }     }    }   }   pickUIImager.frame = CGRect(x: self.view.bounds.width / 2 - 100, y: self.view.bounds.height / 2 - 100,width: 200,height: 200)   line.frame = CGRect(x: self.view.bounds.width / 2 - 100, y: self.view.bounds.height / 2 - 100, width: 200, height: 2)   self.view.addSubview(pickUIImager)   self.view.addSubview(line)   timer =  NSTimer.scheduledTimerWithTimeInterval(0.01, target: self, selector: "animationSate", userInfo: nil, repeats: true)      NSTimer.scheduledTimerWithTimeInterval(2, target: self, selector: "isStartTrue", userInfo: nil, repeats: false)  }  func isStartTrue(){   self.isStart = true  }  override func didReceiveMemoryWarning(){   super.didReceiveMemoryWarning()   captureSession.stopRunning()  }    func animationSate(){   if upOrdown {    if (line.frame.origin.y >= pickUIImager.frame.origin.y + 200)    {     upOrdown = false    }    else    {     line.frame.origin.y += 2    }   } else {    if (line.frame.origin.y <= pickUIImager.frame.origin.y)    {     upOrdown = true    }    else    {     line.frame.origin.y -= 2    }   }  }  func beginSession() {   var err : NSError? = nil   captureSession.addInput(AVCaptureDeviceInput(device: captureDevice, error: &err))   let output = AVCaptureVideoDataOutput()   let cameraQueue = dispatch_queue_create("cameraQueue", DISPATCH_QUEUE_SERIAL)   output.setSampleBufferDelegate(self, queue: cameraQueue)   output.videoSettings = [kCVPixelBufferPixelFormatTypeKey: kCVPixelFormatType_32BGRA]   captureSession.addOutput(output)   if err != nil {    println("error: /(err?.localizedDescription)")   }   previewLayer = AVCaptureVideoPreviewLayer(session: captureSession)   previewLayer?.videoGravity = "AVLayerVideoGravityResizeAspect"   previewLayer?.frame = self.view.bounds   self.view.layer.addSublayer(previewLayer)   captureSession.startRunning()  }  func captureOutput(captureOutput: AVCaptureOutput!, didOutputSampleBuffer sampleBuffer: CMSampleBuffer!, fromConnection connection: AVCaptureConnection!) {   if(self.isStart)   {    let resultImage = sampleBufferToImage(sampleBuffer)    let context = CIContext(options:[kCIContextUseSoftwareRenderer:true])    let detecotr = CIDetector(ofType:CIDetectorTypeFace,  context:context, options:[CIDetectorAccuracy: CIDetectorAccuracyHigh])    let ciImage = CIImage(image: resultImage)    let results:NSArray = detecotr.featuresInImage(ciImage,options: ["CIDetectorImageOrientation" : 6])    for r in results {     let face:CIFaceFeature = r as! CIFaceFeature;     let faceImage = UIImage(CGImage: context.createCGImage(ciImage, fromRect: face.bounds),scale: 1.0, orientation: .Right)     NSLog("Face found at (%f,%f) of dimensions %fx%f", face.bounds.origin.x, face.bounds.origin.y,pickUIImager.frame.origin.x, pickUIImager.frame.origin.y)     dispatch_async(dispatch_get_main_queue()) {      if (self.isStart)      {       self.dismissViewControllerAnimated(true, completion: nil)       self.didReceiveMemoryWarning()       self.callBack!(face: faceImage!)      }      self.isStart = false     }    }   }  }  private func sampleBufferToImage(sampleBuffer: CMSampleBuffer!) -> UIImage {   let imageBuffer: CVImageBufferRef = CMSampleBufferGetImageBuffer(sampleBuffer)   CVPixelBufferLockBaseAddress(imageBuffer, 0)   let baseAddress = CVPixelBufferGetBaseAddressOfPlane(imageBuffer, 0)   let bytesPerRow = CVPixelBufferGetBytesPerRow(imageBuffer)   let width = CVPixelBufferGetWidth(imageBuffer)   let height = CVPixelBufferGetHeight(imageBuffer)   let colorSpace: CGColorSpaceRef = CGColorSpaceCreateDeviceRGB()   let bitsPerCompornent = 8   var bitmapInfo = CGBitmapInfo((CGBitmapInfo.ByteOrder32Little.rawValue | CGImageAlphaInfo.PremultipliedFirst.rawValue) as UInt32)   let newContext = CGBitmapContextCreate(baseAddress, width, height, bitsPerCompornent, bytesPerRow, colorSpace, bitmapInfo) as CGContextRef   let imageRef: CGImageRef = CGBitmapContextCreateImage(newContext)   let resultImage = UIImage(CGImage: imageRef, scale: 1.0, orientation: UIImageOrientation.Right)!   return resultImage  }  func imageResize (imageObj:UIImage, sizeChange:CGSize)-> UIImage{   let hasAlpha = false   let scale: CGFloat = 0.0       UIGraphicsBeginImageContextWithOptions(sizeChange, !hasAlpha, scale)   imageObj.drawInRect(CGRect(origin: CGPointZero, size: sizeChange))   let scaledImage = UIGraphicsGetImageFromCurrentImageContext()   return scaledImage  } }