这段时间抽空做了下人脸识别功能，人脸识别有很多第三方的SDK，例如：Face++，腾讯、讯飞、opencv等，但其实iOS 原生已经支持人脸识别，网上也有很多人脸识别的demo，但基本检测到人脸后就没后续操作了，因此这里分享下识别到人脸后获取识别到的人脸图片。
识别的原理是：客户端检测到人脸，然后将识别到的人脸照片请求后台接口，让后台做人脸校验，成功后返回相关信息！
下面给出基于AVFoundation框架搭建人脸检测功能代码:
一、导入 <AVFoundation/AVFoundation.h>框架，并设置相关代理和属性
#import <AVFoundation/AVFoundation.h>
#define kWidth [UIScreen mainScreen].bounds.size.width
#define kHeight [UIScreen mainScreen].bounds.size.height
#define WS(weakSelf) __weak __typeof(&*self) weakSelf = self
@interface FaceViewController ()<AVCaptureVideoDataOutputSampleBufferDelegate>
@property (nonatomic,strong) AVCaptureSession *session;
@property (nonatomic,strong) AVCaptureVideoPreviewLayer *previewLayer;
@property (nonatomic,strong) AVCaptureDeviceInput*input;
@property (nonatomic,strong) AVCaptureVideoDataOutput *videoOutput;
@property(nonatomic,strong) UIImageView *faceImgView;
@property(nonatomic,assign)BOOL isFirst;
@end
二、界面初始化
- (void)viewDidLoad {
[super viewDidLoad];
self.title = @"人脸识别";
_isFirst = YES;
[self deviceInit];
[self initUI];
}
-(void)initUI{
_faceImgView = [[UIImageView alloc] initWithFrame:CGRectMake(kWidth - 120 , 64, 120, 120)];
_faceImgView.backgroundColor = [UIColor blueColor];
[self.view addSubview:_faceImgView];
UILabel *titleLab = [[UILabel alloc] initWithFrame:CGRectMake(52, 100, kWidth - 108, 18)];
titleLab.text = @"请对准脸部拍摄 提高认证成功率";
titleLab.textAlignment = NSTextAlignmentCenter;
titleLab.textColor = [UIColor redColor];
titleLab.font = [UIFont systemFontOfSize:17];
[self.view addSubview:titleLab];
}
三、相机设备初始化
-(void)deviceInit{
// 获取输入设备（摄像头）
NSArray *devices = [AVCaptureDeviceDiscoverySession discoverySessionWithDeviceTypes:@[AVCaptureDeviceTypeBuiltInWideAngleCamera] mediaType:AVMediaTypeVideo position:AVCaptureDevicePositionBack].devices;
AVCaptureDevice *deviceF = devices[0];
// 根据输入设备创建输入对象
self.input = [[AVCaptureDeviceInput alloc] initWithDevice:deviceF error:nil];
// 设置代理监听输出对象输出的数据
self.videoOutput = [[AVCaptureVideoDataOutput alloc] init];
// 对实时视频帧进行相关的渲染操作,指定代理
[_videoOutput setSampleBufferDelegate:self queue:dispatch_get_main_queue()];
self.session = [[AVCaptureSession alloc] init];
// 设置输出质量(高像素输出)
if ([self.session canSetSessionPreset:AVCaptureSessionPreset640x480]) {
[self.session setSessionPreset:AVCaptureSessionPreset640x480];
}
// 添加输入和输出到会话
[self.session beginConfiguration];
if ([self.session canAddInput:_input]) {
[self.session addInput:_input];
}
if ([self.session canAddOutput:_videoOutput]) {
[self.session addOutput:_videoOutput];
}
[self.session commitConfiguration];
AVCaptureSession *session = (AVCaptureSession *)self.session;
//8.创建预览图层
_previewLayer = [[AVCaptureVideoPreviewLayer alloc] initWithSession:session];
_previewLayer.videoGravity = AVLayerVideoGravityResizeAspectFill;
_previewLayer.frame = self.view.bounds;
[self.view.layer insertSublayer:_previewLayer atIndex:0];
//10. 开始扫描
[self.session startRunning];
}
四、将CMSampleBufferRef转为NSImage
- (void )imageFromSampleBuffer:(CMSampleBufferRef) sampleBuffer
{
//CIImage -> CGImageRef -> UIImage
CVImageBufferRef imageBuffer = CMSampleBufferGetImageBuffer(sampleBuffer); //拿到缓冲区帧数据
CIImage *ciImage = [CIImage imageWithCVPixelBuffer:imageBuffer]; //创建CIImage对象
CIContext *temporaryContext = [CIContext contextWithOptions:nil]; //创建上下文
//识别脸部
CIDetector *detector=[CIDetector detectorOfType:CIDetectorTypeFace context:temporaryContext options:@{CIDetectorAccuracy: CIDetectorAccuracyLow}]; //CIDetectorAccuracyLow：识别精度低，但识别速度快、性能高
//CIDetectorAccuracyHigh：识别精度高、但识别速度比较慢
NSArray *faceArray = [detector featuresInImage:ciImage
options:nil];
//得到人脸图片的尺寸
if (faceArray.count) {
NSLog(@"faceArray == %@",faceArray);
WS(weakSelf);
for (CIFaceFeature * faceFeature in faceArray) {
if (faceFeature.hasLeftEyePosition && faceFeature.hasRightEyePosition && faceFeature.hasMouthPosition) {
NSLog(@"_isFirst == %d",_isFirst);
//这个布尔值用于判断检测到人脸后，获取到人脸照片，不用再进行持续检测
if (_isFirst) {
//因为刚开始扫描到的人脸是模糊照片，所以延迟几秒获取
dispatch_after(dispatch_time(DISPATCH_TIME_NOW, (int64_t)(2.0 * NSEC_PER_SEC)), dispatch_get_main_queue(), ^{
CGImageRef cgImageRef = [temporaryContext createCGImage:ciImage fromRect:faceFeature.bounds];
//resultImg即为获得的人脸图片
UIImage *resultImg = [[UIImage alloc] initWithCGImage:cgImageRef scale:0.1 orientation:UIImageOrientationLeftMirrored];
//显示人脸图片，这里可以将图片转为NSdata类型后，请求后台接口
[self uploadFaceImg:resultImg];
//置为NO
weakSelf.isFirst = NO;
});
}
}
}
}
}
六、 显示捕捉到的人脸图片
//显示图片，这里可以请求后台接口
-(void)uploadFaceImg:(UIImage *)image{
_faceImgView.image = image;
WS(weakSelf);
//这里设置为2秒后可以进行继续检测
dispatch_after(dispatch_time(DISPATCH_TIME_NOW, (int64_t)(2.0 * NSEC_PER_SEC)), dispatch_get_main_queue(), ^{
weakSelf.isFirst = YES;
});
}
七、实现 AVCaptureVideoDataOutput获取实时图像的代理
#pragma mark - AVCaptureVideoDataOutputSampleBufferDelegate
//AVCaptureVideoDataOutput获取实时图像，这个代理方法的回调频率很快，几乎与手机屏幕的刷新频率一样快
- (void)captureOutput:(AVCaptureOutput*)output didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer fromConnection:(AVCaptureConnection*)connection{
[self imageFromSampleBuffer:sampleBuffer];
}
结语：
以上就是人脸识别功能代码, 如有问题请下方留言指正！
如有帮助请👍支持一下 😄
Demo地址: https://github.com/zhwIdea/FaceDetect
下一篇文章：基于GPUImage框架进行人脸识别
