内容字号:默认大号超大号

段落设置:段首缩进取消段首缩进

字体设置:切换到微软雅黑切换到宋体

CoreImage实现人脸识别iOS

2018-06-08 19:08 出处:清屏网 人气: 评论(0

前言

因需求需要,需要实现人脸检测功能,这次正好将这个功能整理了一下,简单的写了一个Demo。代码有点乱,不过,也不怎么想花时间去改了,感觉层次方面还算比较清晰的,好了,进入正题。

一、导入框架,实现自定义相机

1. 导入框架

#import <AVFoundation/AVFoundation.h>
#import <CoreImage/CoreImage.h>

2. 实现自定义相机

  • 初始化相机
#pragma mark - 初始化相机
- (void)getCameraSession
{
    //初始化会话
    _captureSession=[[AVCaptureSession alloc]init];
    if ([_captureSession canSetSessionPreset:AVCaptureSessionPreset1280x720]) {//设置分辨率
        _captureSession.sessionPreset = AVCaptureSessionPreset1280x720;
    }
    //获得输入设备
    AVCaptureDevice *captureDevice=[self getCameraDeviceWithPosition:AVCaptureDevicePositionFront];//取得前置摄像头
    if (!captureDevice) {
        NSLog(@"取得前置摄像头时出现问题.");
        return;
    }

    NSError *error=nil;
    //根据输入设备初始化设备输入对象,用于获得输入数据
    _captureDeviceInput=[[AVCaptureDeviceInput alloc]initWithDevice:captureDevice error:&error];
    if (error) {
        NSLog(@"取得设备输入对象时出错,错误原因:%@",error.localizedDescription);
        return;
    }
    [_captureSession addInput:_captureDeviceInput];

    //初始化设备输出对象,用于获得输出数据
    _captureStillImageOutput=[[AVCaptureStillImageOutput alloc]init];
    NSDictionary *outputSettings = @{AVVideoCodecKey:AVVideoCodecJPEG};
    [_captureStillImageOutput setOutputSettings:outputSettings];//输出设置

    //将设备输入添加到会话中
    if ([_captureSession canAddInput:_captureDeviceInput]) {
        [_captureSession addInput:_captureDeviceInput];
    }

    //将设备输出添加到会话中
    if ([_captureSession canAddOutput:_captureStillImageOutput]) {
        [_captureSession addOutput:_captureStillImageOutput];
    }

    //创建视频预览层,用于实时展示摄像头状态
    _captureVideoPreviewLayer=[[AVCaptureVideoPreviewLayer alloc]initWithSession:self.captureSession];

    CALayer *layer=self.videoMainView.layer;
    layer.masksToBounds=YES;
    _captureVideoPreviewLayer.frame=layer.bounds;
    _captureVideoPreviewLayer.videoGravity=AVLayerVideoGravityResizeAspectFill;//填充模式

    //将视频预览层添加到界面中
    [layer addSublayer:_captureVideoPreviewLayer];
    [layer insertSublayer:_captureVideoPreviewLayer below:self.focusCursor.layer];
}

三、获取相机数据流

因为我需要动态进行人脸识别,所以需要启用数据流,在这里需要设置并遵守代理

// 遵守代理
<AVCaptureVideoDataOutputSampleBufferDelegate>
AVCaptureVideoDataOutput *captureOutput = [[AVCaptureVideoDataOutput alloc] init];
    captureOutput.alwaysDiscardsLateVideoFrames = YES;
    dispatch_queue_t queue;
    queue = dispatch_queue_create("myQueue", DISPATCH_QUEUE_SERIAL);
    [captureOutput setSampleBufferDelegate:self queue:queue];

    NSString *key = (NSString *)kCVPixelBufferPixelFormatTypeKey;
    NSNumber *value = [NSNumber numberWithUnsignedInt:kCVPixelFormatType_32BGRA];
    NSDictionary *settings = @{key:value};
    [captureOutput setVideoSettings:settings];
    [self.captureSession addOutput:captureOutput];

四、实现相机数据流的代理方法

#pragma mark - Samle Buffer Delegate
// 抽样缓存写入时所调用的委托程序
- (void)captureOutput:(AVCaptureOutput *)captureOutput
didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer
       fromConnection:(AVCaptureConnection *)connection
{

}
// 这个方法是将数据流的帧转换成图片
//在该代理方法中,sampleBuffer是一个Core Media对象,可以引入Core Video供使用
// 通过抽样缓存数据创建一个UIImage对象
- (UIImage *)imageFromSampleBuffer:(CMSampleBufferRef) sampleBuffer
{
    CVImageBufferRef imageBuffer = CMSampleBufferGetImageBuffer(sampleBuffer);
    CIImage *ciImage = [CIImage imageWithCVPixelBuffer:imageBuffer];
    CIContext *temporaryContext = [CIContext contextWithOptions:nil];
    CGImageRef videoImage = [temporaryContext createCGImage:ciImage fromRect:CGRectMake(0, 0, CVPixelBufferGetWidth(imageBuffer), CVPixelBufferGetHeight(imageBuffer))];
    UIImage *result = [[UIImage alloc] initWithCGImage:videoImage scale:1.0 orientation:UIImageOrientationLeftMirrored];
    CGImageRelease(videoImage);
    return result;
}

五、对图片进行处理

在这里需要说明一下,因为上面的方法转换出来的图片都是反过来的,所以需要再转一下

/**
 *  用来处理图片翻转90度
 *
 *  @param aImage
 *
 *  @return
 */
- (UIImage *)fixOrientation:(UIImage *)aImage
{
    // No-op if the orientation is already correct
    if (aImage.imageOrientation == UIImageOrientationUp)
        return aImage;

    CGAffineTransform transform = CGAffineTransformIdentity;

    switch (aImage.imageOrientation) {
        case UIImageOrientationDown:
        case UIImageOrientationDownMirrored:
            transform = CGAffineTransformTranslate(transform, aImage.size.width, aImage.size.height);
            transform = CGAffineTransformRotate(transform, M_PI);
            break;

        case UIImageOrientationLeft:
        case UIImageOrientationLeftMirrored:
            transform = CGAffineTransformTranslate(transform, aImage.size.width, 0);
            transform = CGAffineTransformRotate(transform, M_PI_2);
            break;

        case UIImageOrientationRight:
        case UIImageOrientationRightMirrored:
            transform = CGAffineTransformTranslate(transform, 0, aImage.size.height);
            transform = CGAffineTransformRotate(transform, -M_PI_2);
            break;
        default:
            break;
    }

    switch (aImage.imageOrientation) {
        case UIImageOrientationUpMirrored:
        case UIImageOrientationDownMirrored:
            transform = CGAffineTransformTranslate(transform, aImage.size.width, 0);
            transform = CGAffineTransformScale(transform, -1, 1);
            break;

        case UIImageOrientationLeftMirrored:
        case UIImageOrientationRightMirrored:
            transform = CGAffineTransformTranslate(transform, aImage.size.height, 0);
            transform = CGAffineTransformScale(transform, -1, 1);
            break;
        default:
            break;
    }

    // Now we draw the underlying CGImage into a new context, applying the transform
    // calculated above.
    CGContextRef ctx = CGBitmapContextCreate(NULL, aImage.size.width, aImage.size.height,
                                             CGImageGetBitsPerComponent(aImage.CGImage), 0,
                                             CGImageGetColorSpace(aImage.CGImage),
                                             CGImageGetBitmapInfo(aImage.CGImage));
    CGContextConcatCTM(ctx, transform);
    switch (aImage.imageOrientation) {
        case UIImageOrientationLeft:
        case UIImageOrientationLeftMirrored:
        case UIImageOrientationRight:
        case UIImageOrientationRightMirrored:
            // Grr...
            CGContextDrawImage(ctx, CGRectMake(0,0,aImage.size.height,aImage.size.width), aImage.CGImage);
            break;

        default:
            CGContextDrawImage(ctx, CGRectMake(0,0,aImage.size.width,aImage.size.height), aImage.CGImage);
            break;
    }

    // And now we just create a new UIImage from the drawing context
    CGImageRef cgimg = CGBitmapContextCreateImage(ctx);
    UIImage *img = [UIImage imageWithCGImage:cgimg];
    CGContextRelease(ctx);
    CGImageRelease(cgimg);
    return img;
}

六、利用CoreImage中的detectFace进行人脸检测

/**识别脸部*/
-(NSArray *)detectFaceWithImage:(UIImage *)faceImag
{
    //此处是CIDetectorAccuracyHigh,若用于real-time的人脸检测,则用CIDetectorAccuracyLow,更快
    CIDetector *faceDetector = [CIDetector detectorOfType:CIDetectorTypeFace
                                                  context:nil
                                                  options:@{CIDetectorAccuracy: CIDetectorAccuracyHigh}];
    CIImage *ciimg = [CIImage imageWithCGImage:faceImag.CGImage];
    NSArray *features = [faceDetector featuresInImage:ciimg];
    return features;
}

总结

我的思路是将相机里获取的数据,通过代理方法,将帧转换成每一张图片,拿到图片,去实现人脸识别。功能没问题,但是很耗性能,但是暂时我不太清楚还有什么好的方法来实现,如果有什么好的方法,也可以留言告诉我,感谢!

 
分享给小伙伴们:
本文标签: CoreImage人脸识别iOS

相关文章

发表评论愿您的每句评论,都能给大家的生活添色彩,带来共鸣,带来思索,带来快乐。

CopyRight © 2015-2016 QingPingShan.com , All Rights Reserved.

清屏网 版权所有 豫ICP备15026204号