作为一个好奇心非常重的人，面对未知的世界都想去一探到底。
于是做了个人脸识别的demo。
眼下国内的关于opencv技术文章非常少。都是互相抄袭。关键是抄个一小部分还不全。时间又是非常久之前的了，和如今的一些东西对不上。
没事，我是个实在人，啥也不多说，直接上開始。期间參考了国内很多opencv的文章，代码部分參考http://m.blog.csdn.net/blog/u013810454/27868973。大家能够查看。只是他那个项目下载下来有问题。
我这个融合了全部的长处，更加全面。从配置到使用。
首先我们来配置opencv在xcodeproject。
1.opencv官网下载ios下的框架，先把opencv2.framework下载下来。
然后直接拖到先前创建好的工程中。
然后
然后
如今主要的配置已经完毕。是时候展现真正的技术了。当然别忘记把.m改成.mm。以便使用c++。
#import "ViewController.h"
#import <Foundation/Foundation.h>
int currentvalue = 9;
@interface ViewController ()<UIImagePickerControllerDelegate,UINavigationControllerDelegate>
{
//显示图片
UIImageView *_imageView;
UIImage *image;
}
@end
@implementation ViewController
- (void)viewDidLoad {
[super viewDidLoad];
// Do any additional setup after loading the view.
[self createButton];
//创建一个UIImagePickerController对象
UIImagePickerController *ctrl = [[UIImagePickerController alloc] init];
//设置类型
ctrl.sourceType = UIImagePickerControllerSourceTypePhotoLibrary;
//设置代理
ctrl.delegate = self;
//显示
[self presentViewController:ctrl animated:YES completion:nil];
self.view.backgroundColor = [UIColor whiteColor];
//创建一个UIImageView，用来显示选择的图片
_imageView = [[UIImageView alloc] initWithFrame:CGRectMake(50, 100, 300, 400)];
[self.view addSubview:_imageView];
}
#pragma mark - UIImagePickerController代理
-(void)imagePickerController:(UIImagePickerController *)picker didFinishPickingMediaWithInfo:(NSDictionary *)info
{
//取到选择的图片
image = info[UIImagePickerControllerOriginalImage];
UIImageOrientation imageOrientation=image.imageOrientation;
if(imageOrientation!=UIImageOrientationUp)
{
// 原始图片能够依据照相时的角度来显示，但UIImage无法判定，于是出现获取的图片会向左转９０度的现象。
// 下面为调整图片角度的部分
UIGraphicsBeginImageContext(image.size);
[image drawInRect:CGRectMake(0, 0, image.size.width, image.size.height)];
image = UIGraphicsGetImageFromCurrentImageContext();
UIGraphicsEndImageContext();
// 调整图片角度完成
}
//处理图片
_imageView.image = image;
[picker dismissViewControllerAnimated:YES completion:nil];
}
-(void)imagePickerControllerDidCancel:(UIImagePickerController *)picker
{
[picker dismissViewControllerAnimated:YES completion:nil];
}
//把image转化成opencv的图片格式
- (IplImage *)CreateIplImageFromUIImage:(UIImage *)image {
CGImageRef imageRef = image.CGImage;
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
IplImage *iplimage = cvCreateImage(cvSize(image.size.width, image.size.height), IPL_DEPTH_8U, 4);
CGContextRef contextRef = CGBitmapContextCreate(iplimage->imageData, iplimage->width, iplimage->height,
iplimage->depth, iplimage->widthStep,
colorSpace, kCGImageAlphaPremultipliedLast|kCGBitmapByteOrderDefault);
CGContextDrawImage(contextRef, CGRectMake(0, 0, image.size.width, image.size.height), imageRef);
CGContextRelease(contextRef);
CGColorSpaceRelease(colorSpace);
IplImage *ret = cvCreateImage(cvGetSize(iplimage), IPL_DEPTH_8U, 3);
cvCvtColor(iplimage, ret, CV_RGBA2BGR);
cvReleaseImage(&iplimage);
return ret;
}
- (void) opencvFaceDetect {
UIImage* img = [image copy];
if(img) {
cvSetErrMode(CV_ErrModeParent);
IplImage *image = [self CreateIplImageFromUIImage:img];
IplImage *grayImg = cvCreateImage(cvGetSize(image), IPL_DEPTH_8U, 1); //先转为灰度图
cvCvtColor(image, grayImg, CV_BGR2GRAY);
//将输入图像缩小4倍以加快处理速度
int scale = 4;
IplImage *small_image = cvCreateImage(cvSize(image->width/scale,image->height/scale), IPL_DEPTH_8U, 1);
cvResize(grayImg, small_image);
//载入分类器
NSString *path = [[NSBundle mainBundle] pathForResource:@"haarcascade_frontalface_alt2" ofType:@"xml"];
CvHaarClassifierCascade* cascade = (CvHaarClassifierCascade*)cvLoad([path cStringUsingEncoding:NSASCIIStringEncoding], NULL, NULL, NULL);
CvMemStorage* storage = cvCreateMemStorage(0);
cvClearMemStorage(storage);
//关键部分。使用cvHaarDetectObjects进行检測。得到一系列方框
CvSeq* faces = cvHaarDetectObjects(small_image, cascade, storage ,1.1, currentvalue, CV_HAAR_DO_CANNY_PRUNING, cvSize(0,0), cvSize(0, 0));
NSLog(@"faces:%d",faces->total);
//创建画布将人脸部分标记出
CGImageRef imageRef = img.CGImage;
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
CGContextRef contextRef = CGBitmapContextCreate(NULL, img.size.width, img.size.height,8, img.size.width * 4,colorSpace, kCGImageAlphaPremultipliedLast|kCGBitmapByteOrderDefault);
CGContextDrawImage(contextRef, CGRectMake(0, 0, img.size.width, img.size.height), imageRef);
CGContextSetLineWidth(contextRef, 4);
CGContextSetRGBStrokeColor(contextRef, 1.0, 0.0, 0.0, 1);
//对人脸进行标记
for(int i = 0; i < faces->total; i++) {
// Calc the rect of faces
CvRect cvrect = *(CvRect*)cvGetSeqElem(faces, i);
CGRect face_rect = CGContextConvertRectToDeviceSpace(contextRef, CGRectMake(cvrect.x*scale, cvrect.y*scale , cvrect.width*scale, cvrect.height*scale));
CGContextStrokeRect(contextRef, face_rect);
}
_imageView.image = [UIImage imageWithCGImage:CGBitmapContextCreateImage(contextRef)];
}
}
//检測略耗时，开一个新线程来处理吧
-(void)btn
{
[NSThread detachNewThreadSelector:@selector(opencvFaceDetect) toTarget:self withObject:nil];
}
-(void)createButton
{
UIButton *btn = [[UIButton alloc]init];
btn.backgroundColor = [UIColor redColor];
btn.frame = CGRectMake(0, 100, 30, 30);
[btn addTarget:self action:@selector(btn) forControlEvents:UIControlEventTouchUpInside];
[self.view addSubview:btn];
}
@endok，如今能够检測人脸了。
是不是非常奇妙。非常好玩？赶紧动手试一试吧。