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。
如果有更好的实现策略和我讨论或者想拿源码和思维导图资料的, 请联系我时，备注一下CoreImage实现人脸识别-iOS 加我技术交流QQ群：656315826
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>
复制代码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];
}
复制代码三、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>
复制代码 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];
复制代码四、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;
}
复制代码五、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;
}
复制代码六、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;
}
复制代码总结
Demo源码
想要获取案例源码可以加我技术交流群：656315826，亦或者对 我写的有些疑问也可以在群里联系我，我看到会第一时间回复的
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！