- 近几年随着移动设备硬件设备越来越优各种美颜相机App应运而生，美颜、瘦脸、添加挂件等等一系列的功能,这其中的原理一定离不开一个关键的技术，那就是人脸识别
一般的检测流程
(1) 人脸检测
检测图片中是否有人脸，或者有多少个人脸，同时会给出人脸的位置信息
(2) 人脸关键点检测
第一步我们找出来图中是否有人脸的信息，然后通过人脸的位置，与图片信息，获取人脸的关键点
(3) 处理信息
通过关键点，来做一些你需要的东西
扫盲：什么是关键点
我们来看一张图
image.png这张图通过 68 个点描述了人脸的轮廓，这 68 个点 就是关键点，也有 5 个点的关键点和其他的规格;
人脸检测
今天我们来通过iOS系统本身的AVFoundation 框架 来检测视频流中出现的人脸，并把检测出来的框绘制到视频流中，我们先看一下效果是什么样子的
IMB_hHOF7t.GIF
Mars 可能太酷 都检测不到！
原料
- AVFoundation
- opencv2.framework 下载opencv2
ps:opencv 有的库带有iOS 用的一些方法 有的版本不带，我忘记了 大家自行下载查阅，没有的话也可以自己写方法，主要是做转换用的，你的controller的.m文件要换成.mm
#import "ViewController.h"
#import <AVFoundation/AVFoundation.h>
#import <opencv2/imgproc/types_c.h>
#import <opencv2/imgproc/imgproc_c.h>
#import <opencv2/imgcodecs/ios.h>
#import <opencv2/opencv.hpp>
@interface ViewController ()<AVCaptureVideoDataOutputSampleBufferDelegate, AVCaptureMetadataOutputObjectsDelegate>
@property (nonatomic,strong) AVCaptureSession *session;
@property (nonatomic,strong) UIImageView *cameraView;
@property (nonatomic,strong) dispatch_queue_t sample;
@property (nonatomic,strong) dispatch_queue_t faceQueue;
@property (nonatomic,copy) NSArray *currentMetadata; //?< 如果检测到了人脸系统会返回一个数组 我们将这个数组存起来
@end
@implementation ViewController
- (void)viewDidLoad {
[super viewDidLoad];
_currentMetadata = [NSMutableArray arrayWithCapacity:0];
[self.view addSubview: self.cameraView];
_sample = dispatch_queue_create("sample", NULL);
_faceQueue = dispatch_queue_create("face", NULL);
NSArray *devices = [AVCaptureDevice devicesWithMediaType:AVMediaTypeVideo];
AVCaptureDevice *deviceF;
for (AVCaptureDevice *device in devices )
{
if ( device.position == AVCaptureDevicePositionFront )
{
deviceF = device;
break;
}
}
AVCaptureDeviceInput*input = [[AVCaptureDeviceInput alloc] initWithDevice:deviceF error:nil];
AVCaptureVideoDataOutput *output = [[AVCaptureVideoDataOutput alloc] init];
[output setSampleBufferDelegate:self queue:_sample];
AVCaptureMetadataOutput *metaout = [[AVCaptureMetadataOutput alloc] init];
[metaout setMetadataObjectsDelegate:self queue:_faceQueue];
self.session = [[AVCaptureSession alloc] init];
[self.session beginConfiguration];
if ([self.session canAddInput:input]) {
[self.session addInput:input];
}
if ([self.session canSetSessionPreset:AVCaptureSessionPreset640x480]) {
[self.session setSessionPreset:AVCaptureSessionPreset640x480];
}
if ([self.session canAddOutput:output]) {
[self.session addOutput:output];
}
if ([self.session canAddOutput:metaout]) {
[self.session addOutput:metaout];
}
[self.session commitConfiguration];
NSString *key = (NSString *)kCVPixelBufferPixelFormatTypeKey;
NSNumber *value = [NSNumber numberWithUnsignedInt:kCVPixelFormatType_32BGRA];
NSDictionary *videoSettings = [NSDictionary dictionaryWithObject:value forKey:key];
[output setVideoSettings:videoSettings];
//这里 我们告诉要检测到人脸 就给我一些反应，里面还有QRCode 等 都可以放进去，就是 如果视频流检测到了你要的 就会出发下面第二个代理方法
[metaout setMetadataObjectTypes:@[AVMetadataObjectTypeFace]];
AVCaptureSession* session = (AVCaptureSession *)self.session;
//前置摄像头一定要设置一下 要不然画面是镜像
for (AVCaptureVideoDataOutput* output in session.outputs) {
for (AVCaptureConnection * av in output.connections) {
//判断是否是前置摄像头状态
if (av.supportsVideoMirroring) {
//镜像设置
av.videoOrientation = AVCaptureVideoOrientationPortrait;
av.videoMirrored = YES;
}
}
}
[self.session startRunning];
}
#pragma mark - AVCaptureSession Delegate -
- (void)captureOutput:(AVCaptureOutput *)output didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer fromConnection:(AVCaptureConnection *)connection
{
NSMutableArray *bounds = [NSMutableArray arrayWithCapacity:0];
//每一帧，我们都看一下 self.currentMetadata 里面有没有东西，然后将里面的
//AVMetadataFaceObject 转换成 AVMetadataObject，其中AVMetadataObject 的bouns 就是人脸的位置 ，我们将bouns 存到数组中
for (AVMetadataFaceObject *faceobject in self.currentMetadata) {
AVMetadataObject *face = [output transformedMetadataObjectForMetadataObject:faceobject connection:connection];
[bounds addObject:[NSValue valueWithCGRect:face.bounds]];
}
}
- (void)captureOutput:(AVCaptureOutput *)output didOutputMetadataObjects:(NSArray<__kindof AVMetadataObject *> *)metadataObjects fromConnection:(AVCaptureConnection *)connection
{
//当检测到了人脸会走这个回调
_currentMetadata = metadataObjects;
}
- (UIImage*)imageFromPixelBuffer:(CMSampleBufferRef)p {
CVImageBufferRef buffer;
buffer = CMSampleBufferGetImageBuffer(p);
CVPixelBufferLockBaseAddress(buffer, 0);
uint8_t *base;
size_t width, height, bytesPerRow;
base = (uint8_t *)CVPixelBufferGetBaseAddress(buffer);
width = CVPixelBufferGetWidth(buffer);
height = CVPixelBufferGetHeight(buffer);
bytesPerRow = CVPixelBufferGetBytesPerRow(buffer);
CGColorSpaceRef colorSpace;
CGContextRef cgContext;
colorSpace = CGColorSpaceCreateDeviceRGB();
cgContext = CGBitmapContextCreate(base, width, height, 8, bytesPerRow, colorSpace, kCGBitmapByteOrder32Little | kCGImageAlphaPremultipliedFirst);
CGColorSpaceRelease(colorSpace);
CGImageRef cgImage;
UIImage *image;
cgImage = CGBitmapContextCreateImage(cgContext);
image = [UIImage imageWithCGImage:cgImage];
CGImageRelease(cgImage);
CGContextRelease(cgContext);
CVPixelBufferUnlockBaseAddress(buffer, 0);
return image;
}
- (UIImageView *)cameraView
{
if (!_cameraView) {
_cameraView = [[UIImageView alloc] initWithFrame:self.view.bounds];
//不拉伸
_cameraView.contentMode = UIViewContentModeScaleAspectFill;
}
return _cameraView;
}
注意的地方
- 1.output的设置一定在添加之后
- 2.info.plist 要设置相机权限 Privacy - Camera Usage Description
现在我们视频流拿到了 但是还没有显示出来，下面我们会通过opencv 将人脸框绘制在视频流上，并通过UIImageView 将 处理后的图像显示出来
将人脸框绘制到显示的视频流上
(1). 转换
我们先写一个方法 将CMSampleBufferRef 转换成 UIImage(其实也可以直接CMSampleBufferRef 转换成cv::Mat)
- (UIImage*)imageFromPixelBuffer:(CMSampleBufferRef)p {
CVImageBufferRef buffer;
buffer = CMSampleBufferGetImageBuffer(p);
CVPixelBufferLockBaseAddress(buffer, 0);
uint8_t *base;
size_t width, height, bytesPerRow;
base = (uint8_t *)CVPixelBufferGetBaseAddress(buffer);
width = CVPixelBufferGetWidth(buffer);
height = CVPixelBufferGetHeight(buffer);
bytesPerRow = CVPixelBufferGetBytesPerRow(buffer);
CGColorSpaceRef colorSpace;
CGContextRef cgContext;
colorSpace = CGColorSpaceCreateDeviceRGB();
cgContext = CGBitmapContextCreate(base, width, height, 8, bytesPerRow, colorSpace, kCGBitmapByteOrder32Little | kCGImageAlphaPremultipliedFirst);
CGColorSpaceRelease(colorSpace);
CGImageRef cgImage;
UIImage *image;
cgImage = CGBitmapContextCreateImage(cgContext);
image = [UIImage imageWithCGImage:cgImage];
CGImageRelease(cgImage);
CGContextRelease(cgContext);
CVPixelBufferUnlockBaseAddress(buffer, 0);
return image;
}
(2).绘制
我们在继续在 AVCaptureVideoDataOutputSampleBufferDelegate 去处理视频流，已经可以拿到 有关人脸的信息了 我们直接绘制上去就可以了
- (void)captureOutput:(AVCaptureOutput *)output didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer fromConnection:(AVCaptureConnection *)connection
{
NSMutableArray *bounds = [NSMutableArray arrayWithCapacity:0];
for (AVMetadataFaceObject *faceobject in self.currentMetadata) {
AVMetadataObject *face = [output transformedMetadataObjectForMetadataObject:faceobject connection:connection];
[bounds addObject:[NSValue valueWithCGRect:face.bounds]];
}
//转换成UIImage
UIImage *image = [self imageFromPixelBuffer:sampleBuffer];
cv::Mat mat;
//转换成cv::Mat
UIImageToMat(image, mat);
for (NSValue *rect in bounds) {
CGRect r = [rect CGRectValue];
//画框
cv::rectangle(mat, cv::Rect(r.origin.x,r.origin.y,r.size.width,r.size.height), cv::Scalar(255,0,0,1));
}
//这里不考虑性能 直接怼Image
dispatch_async(dispatch_get_main_queue(), ^{
self.cameraView.image = MatToUIImage(mat);
});
}
忘记一个东西 依赖库 大家别忘记 点一波
image.png
终于传上去了 觉得不错别忘记Star-demoGitHub
