GitHub地址：KJVisionDemo
人脸矩形检测
人脸特征识别
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API架构 一 Vision框架共包括以下类
VNRequestHandler ：继承自NSObject的VNImageRequestHandler 和 VNSequenceRequestHandler VNRequest ：图像分析请求的抽象超类 VNObservation ：图像分析结果的抽象超类 VNFaceLandmarks ：面部信息类 VNError ：错误信息类 VNUtils ：工具类 VNTypes 两个协议：VNRequestRevisionProviding 和 VNFaceObservationAccepting
Vison 的应用场景
1、图像配准 2、矩形检测 3、二维码/条形码检测 4、目标跟踪：脸部，矩形和通用模板 5、文字检测：监测文字外框和文字识别 6、人脸检测：支持检测笑脸、侧脸、局部遮挡脸部、戴眼镜和帽子等场景，可以标记出人脸的矩形区域 7、人脸特征点：可以标记出人脸和眼睛、眉毛、鼻子、嘴、牙齿的轮廓，以及人脸的中轴线
Vision 支持多种图片类型
CIImage、NSURL、NSData、CGImageRef、CVPixelBufferRef
框架整体介绍
作者信息作者其他库使用方法Bug总结
作者信息
Github地址：https://github.com/yangKJ 简书地址：https://www.jianshu.com/u/c84c00476ab6 博客地址：https://blog.csdn.net/qq_34534179
作者其他Pod库
播放器 - KJPlayer是一款视频播放器，AVPlayer的封装，继承UIView
pod 'KJPlayer' # 播放器功能区
pod 'KJPlayer/KJPlayerView' # 自带展示界面
实用又方便的Category和一些自定义控件
pod 'KJEmitterView'
pod 'KJEmitterView/Function'#
pod 'KJEmitterView/Control' # 自定义控件
轮播图 - 支持缩放 多种pagecontrol 支持继承自定义样式 自带网络加载和缓存
pod 'KJBannerView' # 轮播图，网络图片加载
菜单控件 - 下拉控件 选择控件
pod 'KJMenuView' # 菜单控件
加载Loading - 多种样式供选择
pod 'KJLoadingAnimation' # 加载控件
Issue
如果您在使用中有好的需求及建议，或者遇到什么bug，欢迎随时issue，我会及时的回复，有空也会不断优化更新这些库
使用方法
1、流程
给各种功能的 Request 提供给一个 RequestHandler
RequestHandler持有需要识别的图片信息
并将处理结果分发给每个 Request 的 completion Block 中
可以从 results 属性中得到 Observation 信息数组
2、代码示例
//
// ViewController.m
// KJVisionDemo
//
// Created by 杨科军 on 2019/10/31.
// Copyright © 2019 杨科军. All rights reserved.
//
#import "ViewController.h"
#import "KJVisionTool.h"
@interface ViewController ()
@property (nonatomic, strong) UIImageView *imageView;
@property (nonatomic, strong) NSMutableArray *temps;
@end
@implementation ViewController
- (void)viewDidLoad {
[super viewDidLoad];
// Do any additional setup after loading the view.
self.temps = [NSMutableArray array];
[self.view addSubview:self.imageView];
UIImage *image = [UIImage imageNamed:@"AAA"];
self.imageView.image = image;
[KJVisionTool kj_detectImageWithType:(KJDetectFaceTypeRectanglesRequest) Image:image Block:^(NSArray * _Nonnull datas) {
self.imageView.image = [KJVisionTool kj_drawImage:image Rects:datas];
}];
return;
// [KJVisionTool kj_detectImageWithType:(KJDetectFaceTypeLandmarksRequest) Image:image Block:^(NSArray * _Nonnull datas) {
// if (datas.count) {
// KJVisionModel *model = datas[0];
// self.imageView.image = [KJVisionTool kj_drawImage:image Observation:model.observation LandMarkPoints:model.allPoints];
// }
// }];
// return;
// [KJVisionTool kj_dynamicDetectFaceWithSuperView:self.view Block:^(NSArray * _Nonnull datas) {
// dispatch_async(dispatch_get_main_queue(), ^{
// //先移除之前的矩形框
// [self.temps makeObjectsPerformSelector:@selector(removeFromSuperlayer)];
AVCaptureDevicePosition position = [[self.avInput device] position];
// for (VNFaceObservation *faceObservation in datas) {
// //boundingBox
// CGRect transFrame = kj_convertRect(faceObservation.boundingBox, self.view.frame.size);
//前置摄像头的时候 记得转换
if (position == AVCaptureDevicePositionFront){
transFrame.origin.x = self.view.frame.size.width - transFrame.origin.x - transFrame.size.width;
}
// CALayer *rectLayer = [CALayer layer];
// rectLayer.frame = transFrame;
// rectLayer.borderColor = [UIColor purpleColor].CGColor;
// rectLayer.borderWidth = 2;
// [self.view.layer addSublayer:rectLayer];
// [self.temps addObject:rectLayer];
// }
// });
// }];
}
- (UIImageView *)imageView{
if (!_imageView) {
_imageView = [[UIImageView alloc]initWithFrame:self.view.bounds];
_imageView.contentMode = UIViewContentModeScaleAspectFit;
}
return _imageView;
}
@end
3、内部介绍
数据模型
@interface KJVisionModel : NSObject
// 包含该面部特征的的数组
@property (nonatomic, strong) NSMutableArray *allPoints;
//
@property (nonatomic, strong) VNFaceObservation *observation;
// 脸部轮廊
@property (nonatomic, strong) VNFaceLandmarkRegion2D *faceContour;
// 左眼，右眼
@property (nonatomic, strong) VNFaceLandmarkRegion2D *leftEye;
@property (nonatomic, strong) VNFaceLandmarkRegion2D *rightEye;
// 鼻子，鼻嵴
@property (nonatomic, strong) VNFaceLandmarkRegion2D *nose;
@property (nonatomic, strong) VNFaceLandmarkRegion2D *noseCrest;
@property (nonatomic, strong) VNFaceLandmarkRegion2D *medianLine;
// 外唇，内唇
@property (nonatomic, strong) VNFaceLandmarkRegion2D *outerLips;
@property (nonatomic, strong) VNFaceLandmarkRegion2D *innerLips;
// 左眉毛，右眉毛
@property (nonatomic, strong) VNFaceLandmarkRegion2D *leftEyebrow;
@property (nonatomic, strong) VNFaceLandmarkRegion2D *rightEyebrow;
// 左瞳,右瞳
@property (nonatomic, strong) VNFaceLandmarkRegion2D *leftPupil;
@property (nonatomic, strong) VNFaceLandmarkRegion2D *rightPupil;
@end
方法介绍
typedef NS_ENUM(NSUInteger,KJDetectFaceType) {
KJDetectFaceTypeRectanglesRequest = 0, // 人脸矩形检测
KJDetectFaceTypeLandmarksRequest, // 人脸特征识别
KJDetectFaceTypeTextRectangles, // 文字识别
};
typedef void (^KJVisionDatasBlock)(NSArray *datas);
@interface KJVisionTool : KJVisionModel
/// 识别图片
+ (void)kj_detectImageWithType:(KJDetectFaceType)type Image:(UIImage*)image Block:(KJVisionDatasBlock)block;
/// 在返回结果中的boundingBox中的坐标，我们并不能立即使用，而是需要进行转换
/// 因为这里是相对于image的一个比例，这里需要注意的是y坐标的转换，因为坐标系的y轴和UIView的y轴是相反的
/// 最后就是通过返回的坐标进行矩形的绘制
+ (UIImage*)kj_drawImage:(UIImage*)image Rects:(NSArray*)rects;
+ (UIImage *)kj_drawImage:(UIImage*)image Observation:(VNFaceObservation*)observation LandMarkPoints:(NSArray*)pointArray;
/// 动态识别
+ (void)kj_dynamicDetectFaceWithSuperView:(UIView*)view Block:(KJVisionDatasBlock)block;
@end
实现代码
@interface KJVisionTool ()<AVCaptureVideoDataOutputSampleBufferDelegate>
@property(nonatomic,copy,class) KJVisionDatasBlock xxblock;
@property(nonatomic,strong) UIView *superView;
@property(nonatomic,strong) AVCaptureSession *captureSession;
@property(nonatomic,strong) AVCaptureDevice *videoDevice;
@property(nonatomic,strong) AVCaptureDeviceInput *videoInput;
@property(nonatomic,strong) AVCaptureVideoDataOutput *dataOutput;
@property(nonatomic,strong) AVCaptureVideoPreviewLayer *captureVideoPreviewLayer;
@end
@implementation KJVisionTool
static KJVisionTool *tool = nil;
static KJVisionDatasBlock _xxblock = nil;
+ (KJVisionDatasBlock)xxblock{
if (_xxblock == nil) {
_xxblock = ^void(NSArray*datas){ };
}
return _xxblock;
}
+ (void)setXxblock:(KJVisionDatasBlock)xxblock{
if (xxblock != _xxblock) {
_xxblock = [xxblock copy];
}
}
/// 识别图片
+ (void)kj_detectImageWithType:(KJDetectFaceType)type Image:(UIImage*)image Block:(KJVisionDatasBlock)block{
self.xxblock = block;
// 转换CIImage，创建处理VNImageRequestHandler
VNImageRequestHandler *handler = [[VNImageRequestHandler alloc]initWithCIImage:[[CIImage alloc]initWithImage:image] options:@{}];
VNImageBasedRequest *request = [self detectRequestWithType:type Image:image];
// 发送识别请求
[handler performRequests:@[request] error:nil];
}
+ (VNImageBasedRequest*)detectRequestWithType:(KJDetectFaceType)type Image:(UIImage*)image{
VNImageBasedRequest *detectRequest = [[VNImageBasedRequest alloc]init];
__weak typeof(self) weakself = self;
if (type == KJDetectFaceTypeRectanglesRequest) {
detectRequest = [[VNDetectFaceRectanglesRequest alloc] initWithCompletionHandler:^(VNRequest * _Nonnull request, NSError * _Nullable error) {
[weakself VNDetectFaceRectanglesRequest:request image:image];
}];
}else if (type == KJDetectFaceTypeLandmarksRequest) {
detectRequest = [[VNDetectFaceLandmarksRequest alloc] initWithCompletionHandler:^(VNRequest * _Nonnull request, NSError * _Nullable error) {
[weakself VNDetectFaceLandmarksRequest:request];
}];
}else if (type == KJDetectFaceTypeTextRectangles) {
detectRequest = [[VNDetectTextRectanglesRequest alloc] initWithCompletionHandler:^(VNRequest * _Nonnull request, NSError * _Nullable error) {
}];
((VNDetectTextRectanglesRequest*)detectRequest).reportCharacterBoxes = YES;// 设置识别具体文字
}
return detectRequest;
}
/// 动态识别
+ (void)kj_dynamicDetectFaceWithSuperView:(UIView*)view Block:(KJVisionDatasBlock)block{
self.xxblock = block;
@synchronized (self) {
if (tool == nil) {
tool = [[KJVisionTool alloc]init];
}
}
// //顺时针 90°
// CGAffineTransform t = CGAffineTransformMakeTranslation(view.frame.size.height,.0);
// view.transform = mixedTransform;//CGAffineTransformRotate(t, M_PI_2);
tool.superView = view;
/// 权限检测
[tool getAuthorization];
}
#pragma mark - 处理相关
// 处理人脸识别回调
+ (void)VNDetectFaceRectanglesRequest:(VNRequest*)request image:(UIImage *)image{
_xxblock(({
NSMutableArray *temps = [NSMutableArray array];
for (VNFaceObservation *observation in request.results) {
NSValue *ractValue = [NSValue valueWithCGRect:kj_convertRect(observation.boundingBox, image.size)];
[temps addObject:ractValue];
}
temps;
}));
}
// 处理人脸特征回调
+ (void)VNDetectFaceLandmarksRequest:(VNRequest*)request{
_xxblock(({
NSMutableArray *temps = [NSMutableArray array];
NSArray *keys = kj_getAllKeys([VNFaceLandmarks2D class], true);
NSArray *modelKeys = kj_getAllKeys([KJVisionModel class], true);
for (VNFaceObservation *observation in request.results) {
// 创建特征存储对象
KJVisionModel *model = [[KJVisionModel alloc]init];
for (NSString *key in keys) {
// 过滤属性
if ([key isEqualToString:@"allPoints"] || [key isEqualToString:@"observation"] ||
![modelKeys containsObject:key]) continue;
// 得到对应细节具体特征
VNFaceLandmarkRegion2D *region2D = [observation.landmarks valueForKey:key];
[model.allPoints addObject:region2D];
// 特征存储对象进行存储
[model setValue:region2D forKey:key];
}
model.observation = observation;
[temps addObject:model];
}
temps;
}));
}
#pragma mark - 内部方法
static inline CGRect kj_convertRect(CGRect rect,CGSize size){
CGFloat w = rect.size.width * size.width;
CGFloat h = rect.size.height * size.height;
CGFloat x = rect.origin.x * size.width;
CGFloat y = size.height - (rect.origin.y * size.height) - h;
return CGRectMake(x, y, w, h);
}
/// 获取对象属性keys
static inline NSArray * kj_getAllKeys(Class clazz,bool isProperty){
NSMutableArray *keys = [NSMutableArray array];
unsigned int count = 0;
Ivar *vars = NULL;
objc_property_t *propertys = NULL;
const char *name;
if (isProperty) {
propertys = class_copyPropertyList(clazz, &count);
}else{
vars = class_copyIvarList(clazz, &count);
}
for (int i = 0; i < count; i++) {
name = isProperty ? property_getName(propertys[i]) : ivar_getName(vars[i]);
[keys addObject:[NSString stringWithUTF8String:name]];
}
free(vars);
return keys.copy;
}
#pragma mark - 公用方法
/// 在返回结果中的boundingBox中的坐标，我们并不能立即使用，而是需要进行转换
/// 因为这里是相对于image的一个比例，这里需要注意的是y坐标的转换，因为坐标系的y轴和UIView的y轴是相反的
/// 最后就是通过返回的坐标进行矩形的绘制
+ (UIImage*)kj_drawImage:(UIImage*)image Rects:(NSArray*)rects{
UIImage *newImage = nil;
UIGraphicsBeginImageContextWithOptions(image.size, NO, [UIScreen mainScreen].scale);
CGContextRef context = UIGraphicsGetCurrentContext();
CGContextSetLineCap(context,kCGLineCapRound); //边缘样式
CGContextSetLineJoin(context,kCGLineJoinRound);
CGContextSetLineWidth(context,2); //线宽
CGContextSetAllowsAntialiasing(context,YES); //打开抗锯齿
CGContextSetStrokeColorWithColor(context,UIColor.redColor.CGColor); /// 边框颜色
CGContextSetFillColorWithColor(context,UIColor.clearColor.CGColor); /// 填充颜色
//绘制图片
[image drawInRect:CGRectMake(0, 0,image.size.width, image.size.height)];
CGContextBeginPath(context);
for (int i = 0; i < rects.count; i ++) {
CGRect rect = [rects[i] CGRectValue];
CGPoint sPoints[4];//坐标点
sPoints[0] = CGPointMake(rect.origin.x , rect.origin.y);//坐标1
sPoints[1] = CGPointMake(rect.origin.x + rect.size.width, rect.origin.y);//坐标2
sPoints[2] = CGPointMake(rect.origin.x + rect.size.width, rect.origin.y + rect.size.height);//坐标3
sPoints[3] = CGPointMake(rect.origin.x , rect.origin.y + rect.size.height);
CGContextAddLines(context, sPoints, 4);//添加线
CGContextClosePath(context); //封闭
}
CGContextDrawPath(context, kCGPathFillStroke); //根据坐标绘制路径
newImage = UIGraphicsGetImageFromCurrentImageContext();
UIGraphicsEndImageContext();
return newImage;
}
+ (UIImage *)kj_drawImage:(UIImage*)image Observation:(VNFaceObservation*)observation LandMarkPoints:(NSArray*)points{
UIImage *newImage = image;
// 遍历所有特征
for (VNFaceLandmarkRegion2D *landmarks2D in points) {
CGPoint points[landmarks2D.pointCount];
// 转换特征的所有点
for (int i=0; i<landmarks2D.pointCount; i++) {
CGPoint point = landmarks2D.normalizedPoints[i];
CGFloat rectWidth = newImage.size.width * observation.boundingBox.size.width;
CGFloat rectHeight = newImage.size.height * observation.boundingBox.size.height;
points[i] = CGPointMake(point.x * rectWidth + observation.boundingBox.origin.x * newImage.size.width, observation.boundingBox.origin.y * newImage.size.height + point.y * rectHeight);
}
UIGraphicsBeginImageContextWithOptions(newImage.size, false, 1);
CGContextRef context = UIGraphicsGetCurrentContext();
[UIColor.greenColor set]; // 线条颜色
CGContextSetLineWidth(context, 2);//线宽
// 设置翻转
CGContextTranslateCTM(context, 0, newImage.size.height);
CGContextScaleCTM(context, 1.0, -1.0);
// 设置线类型
CGContextSetLineJoin(context, kCGLineJoinRound);
CGContextSetLineCap(context, kCGLineCapRound);
// 设置抗锯齿
CGContextSetShouldAntialias(context, true);
CGContextSetAllowsAntialiasing(context, true);
// 绘制
CGRect rect = CGRectMake(0, 0, newImage.size.width, newImage.size.height);
CGContextDrawImage(context, rect, newImage.CGImage);
CGContextAddLines(context, points, landmarks2D.pointCount);
CGContextDrawPath(context, kCGPathStroke);
// 结束绘制
newImage = UIGraphicsGetImageFromCurrentImageContext();
UIGraphicsEndImageContext();
}
return newImage;
}
#pragma mark - 动态识别相关
/// 初始化相关内容
- (void)initCapture{
[self addSession];
[_captureSession beginConfiguration];
[self addVideo];
[self addPreviewLayer];
[_captureSession commitConfiguration];
[_captureSession startRunning];
}
/// 获取权限
- (void)getAuthorization{
AVAuthorizationStatus videoStatus = [AVCaptureDevice authorizationStatusForMediaType:AVMediaTypeVideo];
if (videoStatus == AVAuthorizationStatusAuthorized || videoStatus == AVAuthorizationStatusNotDetermined) {
[self initCapture];
}else if (videoStatus == AVAuthorizationStatusDenied || videoStatus == AVAuthorizationStatusRestricted) {
NSLog(@"相机未授权");
}
}
/// 获取设备
- (AVCaptureDevice*)deviceWithMediaType:(NSString *)mediaType preferringPosition:(AVCaptureDevicePosition)position{
AVCaptureDeviceDiscoverySession *session = [AVCaptureDeviceDiscoverySession discoverySessionWithDeviceTypes:@[AVCaptureDeviceTypeBuiltInWideAngleCamera] mediaType:AVMediaTypeVideo position:position];
for (AVCaptureDevice *device in session.devices) {
if ([device position] == position) return device;
}
return nil;
}
/// 添加预览视图
- (void)addPreviewLayer{
// 通过会话 (AVCaptureSession) 创建预览层
_captureVideoPreviewLayer = [[AVCaptureVideoPreviewLayer alloc] initWithSession:_captureSession];
_captureVideoPreviewLayer.frame = self.superView.bounds;
//有时候需要拍摄完整屏幕大小的时候可以修改这个
_captureVideoPreviewLayer.videoGravity = AVLayerVideoGravityResizeAspectFill;
_captureVideoPreviewLayer.connection.videoOrientation = 3;
// 显示在视图表面的图层
CALayer *layer = self.superView.layer;
layer.masksToBounds = true;
[layer addSublayer:_captureVideoPreviewLayer];
}
/// 添加video
- (void)addVideo{
/// AVCaptureDevicePositionBack后置摄像头
_videoDevice = [self deviceWithMediaType:AVMediaTypeVideo preferringPosition:AVCaptureDevicePositionBack];
[self addVideoInput];
[self addDataOutput];
}
/// 添加videoinput
- (void)addVideoInput{
_videoInput = [[AVCaptureDeviceInput alloc] initWithDevice:_videoDevice error:NULL];
// 将视频输入对象添加到会话 (AVCaptureSession) 中
if ([_captureSession canAddInput:_videoInput]) {
[_captureSession addInput:_videoInput];
}
}
/// 添加数据输出
- (void)addDataOutput{
// 拍摄视频输出对象
// 初始化输出设备对象，用户获取输出数据
_dataOutput = [[AVCaptureVideoDataOutput alloc] init];
[_dataOutput setSampleBufferDelegate:self queue:dispatch_queue_create("CameraCaptureSampleBufferDelegateQueue", NULL)];
if ([_captureSession canAddOutput:_dataOutput]) {
[_captureSession addOutput:_dataOutput];
//需要重新进行配置输出 特别是下面的输出方向
AVCaptureConnection *captureConnection = [_dataOutput connectionWithMediaType:AVMediaTypeVideo];
if ([captureConnection isVideoOrientationSupported]) {
[captureConnection setVideoOrientation:AVCaptureVideoOrientationPortrait];
}
// 视频稳定设置
if ([captureConnection isVideoStabilizationSupported]) {
captureConnection.preferredVideoStabilizationMode = AVCaptureVideoStabilizationModeAuto;
}
// 设置输出图片方向
captureConnection.videoOrientation = AVCaptureVideoOrientationPortrait;
}
}
- (void)addSession{
_captureSession = [[AVCaptureSession alloc] init];
//设置视频分辨率
//注意,这个地方设置的模式/分辨率大小将影响你后面拍摄照片/视频的大小,
if ([_captureSession canSetSessionPreset:AVCaptureSessionPresetHigh]) {
[_captureSession setSessionPreset:AVCaptureSessionPresetHigh];
}
}
#pragma mark - AVCaptureVideoDataOutputSampleBufferDelegate
/// 获取输出
- (void)captureOutput:(AVCaptureFileOutput *)output didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer fromConnection:(AVCaptureConnection *)connection{
CVPixelBufferRef BufferRef = CMSampleBufferGetImageBuffer(sampleBuffer);
VNDetectFaceRectanglesRequest *detectFaceRequest = [[VNDetectFaceRectanglesRequest alloc] init];
VNImageRequestHandler *detectFaceRequestHandler = [[VNImageRequestHandler alloc]initWithCVPixelBuffer:BufferRef options:@{}];
[detectFaceRequestHandler performRequests:@[detectFaceRequest] error:nil];
/// 输出数据
_xxblock(detectFaceRequest.results);
}
@end
Vision 图像识别框架人脸识别介绍就到此完毕，后面有相关再补充，写文章不容易，还请点个**小星星**传送门
