一、本文主要涉及到opencv的視頻幀抓拍和驗證的相關問題，不包含如何集成opencvios
二、主要講解涉及到opencv中的關鍵類及一些經常使用的方法git
三、着重講解代理方法：github
- (void)processImage:(cv::Mat &)image
四、集成過程當中的注意事項async
五、附上抓拍的小demo的下載地址ide
六、擴展，驗證抓拍的圖片中是否包含人臉學習
=====================================分割線==========================================
如下爲正文this
1、集成opencv須要添加的framework和靜態庫atom
2、OpenCV使用過程當中的關鍵類及一些經常使用的方法spa
一、cap_ios.h、如下爲此類的原始代碼代理
/* For iOS video I/O
* by Eduard Feicho on 29/07/12
* Copyright 2012. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
* 3. The name of the author may not be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
* MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
* EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
* WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
* OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
* ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
*/
#import <UIKit/UIKit.h>
#import <Accelerate/Accelerate.h>
#import <AVFoundation/AVFoundation.h>
#import <ImageIO/ImageIO.h>
#include "opencv2/core.hpp"
//! @addtogroup videoio_ios
//! @{
/////////////////////////////////////// CvAbstractCamera /////////////////////////////////////
@class CvAbstractCamera;
CV_EXPORTS @interface CvAbstractCamera : NSObject
{
UIDeviceOrientation currentDeviceOrientation;
BOOL cameraAvailable;
}
@property (nonatomic, strong) AVCaptureSession* captureSession;
@property (nonatomic, strong) AVCaptureConnection* videoCaptureConnection;
@property (nonatomic, readonly) BOOL running;
@property (nonatomic, readonly) BOOL captureSessionLoaded;
@property (nonatomic, assign) int defaultFPS;
@property (nonatomic, readonly) AVCaptureVideoPreviewLayer *captureVideoPreviewLayer;
@property (nonatomic, assign) AVCaptureDevicePosition defaultAVCaptureDevicePosition;
@property (nonatomic, assign) AVCaptureVideoOrientation defaultAVCaptureVideoOrientation;
@property (nonatomic, assign) BOOL useAVCaptureVideoPreviewLayer;
@property (nonatomic, strong) NSString *const defaultAVCaptureSessionPreset;
@property (nonatomic, assign) int imageWidth;
@property (nonatomic, assign) int imageHeight;
@property (nonatomic, strong) UIView* parentView;
- (void)start;
- (void)stop;
- (void)switchCameras;
- (id)initWithParentView:(UIView*)parent;
- (void)createCaptureOutput;
- (void)createVideoPreviewLayer;
- (void)updateOrientation;
- (void)lockFocus;
- (void)unlockFocus;
- (void)lockExposure;
- (void)unlockExposure;
- (void)lockBalance;
- (void)unlockBalance;
@end
///////////////////////////////// CvVideoCamera ///////////////////////////////////////////
@class CvVideoCamera;
CV_EXPORTS @protocol CvVideoCameraDelegate <NSObject>
#ifdef __cplusplus
// delegate method for processing image frames
- (void)processImage:(cv::Mat&)image;
#endif
@end
CV_EXPORTS @interface CvVideoCamera : CvAbstractCamera<AVCaptureVideoDataOutputSampleBufferDelegate>
{
AVCaptureVideoDataOutput *videoDataOutput;
dispatch_queue_t videoDataOutputQueue;
CALayer *customPreviewLayer;
CMTime lastSampleTime;
}
@property (nonatomic, weak) id<CvVideoCameraDelegate> delegate;
@property (nonatomic, assign) BOOL grayscaleMode;
@property (nonatomic, assign) BOOL recordVideo;
@property (nonatomic, assign) BOOL rotateVideo;
@property (nonatomic, strong) AVAssetWriterInput* recordAssetWriterInput;
@property (nonatomic, strong) AVAssetWriterInputPixelBufferAdaptor* recordPixelBufferAdaptor;
@property (nonatomic, strong) AVAssetWriter* recordAssetWriter;
- (void)adjustLayoutToInterfaceOrientation:(UIInterfaceOrientation)interfaceOrientation;
- (void)layoutPreviewLayer;
- (void)saveVideo;
- (NSURL *)videoFileURL;
- (NSString *)videoFileString;
@end
///////////////////////////////// CvPhotoCamera ///////////////////////////////////////////
@class CvPhotoCamera;
CV_EXPORTS @protocol CvPhotoCameraDelegate <NSObject>
- (void)photoCamera:(CvPhotoCamera*)photoCamera capturedImage:(UIImage *)image;
- (void)photoCameraCancel:(CvPhotoCamera*)photoCamera;
@end
CV_EXPORTS @interface CvPhotoCamera : CvAbstractCamera
{
AVCaptureStillImageOutput *stillImageOutput;
}
@property (nonatomic, weak) id<CvPhotoCameraDelegate> delegate;
- (void)takePicture;
@end
//! @} videoio_ios
以上方法從名知意，且命名簡潔明瞭，無需過多的註釋說明 ，此爲值得我等ITboy學習和觀摩的地方
二、關鍵方法說明
此處不對CvPhotoCamera作說明，主要針對 CvVideoCameraDelegate 的代理方法進行說明
- (void)processImage:(cv::Mat&)image;
此方法視頻幀的抓取代理，其中的image對象爲非正常的RGB對象，爲一個灰度對象，在使用過程當中，須要進行色值的轉換
- (void)processImage:(cv::Mat &)image { cv::Mat outCopyImg; image.copyTo(outCopyImg); cv::cvtColor(outCopyImg, outCopyImg, CV_BGR2RGB); //此處說明：cv::cvtColor爲顏色轉換方法，最後一個參數即爲咱們經常使用的RGB色值 if ([self whetherTheImageBlurry:image]) {
//此爲一個清晰度的驗證，也是來自於網上的摘錄，下方會貼出代碼 [self.videoCamera stop]; keepMatImg = outCopyImg; if (isNeedToCut == YES) { CGFloat mianW = UIScreen.mainScreen.bounds.size.width; CGFloat NH = mianW * 1920 / 1080; cv::Rect rect(0,(1920 - NH)/2,1080,NH); cv::Mat image_roi = outCopyImg(rect); self.keepImageAlive = MatToUIImage(image_roi);
//說明：網上有不少將cv::Mat類型的數據轉換爲UIimage的方法 ，可是OpenCV自己就提供了此方法 MatToUIImage()，因此此處再也不引用其餘方法 }else{ self.keepImageAlive = MatToUIImage(outCopyImg); } NSLog(@"keepImageAlive.size = %@",NSStringFromCGSize(self.keepImageAlive.size)); dispatch_async(dispatch_get_main_queue(), ^{ if (self.keepImageAlive) { self.fuzzyText.text = @"清晰"; self.resultImageView.image = self.keepImageAlive; self.resultImageView.hidden = NO; } }); }else{ dispatch_sync(dispatch_get_main_queue(), ^{ self.fuzzyText.text = @"模糊"; }); } }
三、清晰度的驗證的方法
- (BOOL)whetherTheImageBlurry:(cv::Mat)mat{
unsigned char *data;
int height,width,step;
int Iij;
double Iave = 0, Idelta = 0;
// cv::Mat mat = [OpenCVExtension cvMatFromUIImage:image];
if(!mat.empty()){
cv::Mat gray;
cv::Mat outGray;
// 將圖像轉換爲灰度顯示
cv::cvtColor(mat,gray,CV_RGB2GRAY);
cv::Laplacian(gray, outGray, gray.depth());
// cv::convertScaleAbs( outGray, outGray );
IplImage ipl_image(outGray);
data = (uchar*)ipl_image.imageData;
height = ipl_image.height;
width = ipl_image.width;
step = ipl_image.widthStep;
for(int i=0;i<height;i++)
{
for(int j=0;j<width;j++)
{
Iij = (int) data
[i*width+j];
Idelta = Idelta + (Iij-Iave)*(Iij-Iave);
}
}
Idelta = Idelta/(width*height);
std::cout<<"矩陣方差爲："<<Idelta<<std::endl;
}
return (Idelta > IdeltaCount) ? YES : NO;
}
demo下載地址：https://tianlin106@github.com/tianlin106/OpencvAutoTakeImage.git
3、人臉識別的擴展- (void)processImage:(cv::Mat &)image
{ cv::Mat outCopyImg; image.copyTo(outCopyImg); cv::cvtColor(outCopyImg, outCopyImg, CV_BGR2RGB); if ([self isPhotoContainsFeature:MatToUIImage(outCopyImg)]) { if ([self isPhotoIsBrightness:image] == YES) { [self disposeCamare]; keepMatImg = outCopyImg; UIImage * resultImage = MatToUIImage(outCopyImg); //須要上傳 [self uploadImage:resultImage]; dispatch_async(dispatch_get_main_queue(), ^{ [self.imageView removeFromSuperview]; }); } } } - (BOOL)isPhotoContainsFeature:(UIImage *)image{ CIContext * context = [CIContext contextWithOptions:nil]; NSDictionary * param = [NSDictionary dictionaryWithObject:CIDetectorAccuracyHigh forKey:CIDetectorAccuracy]; CIDetector * faceDetector = [CIDetector detectorOfType:CIDetectorTypeFace context:context options:param]; //此類爲Core Image Framework 中的類 ，主要用於識別某些外貌特性，如下語言爲其API的描述
//An image processor that identifies notable features (such as faces and barcodes) in a still image or video.
CIImage * ciimage = [CIImage imageWithCGImage:image.CGImage]; NSArray * detectResult = [faceDetector featuresInImage:ciimage]; return detectResult.count; }
//此方法計算圖像的亮度是否符合要求 - (BOOL)isPhotoIsBrightness:(cv::Mat &)image { cv::Mat imageSobel; Sobel(image, imageSobel, CV_16U, 1, 1); //圖像的平均灰度 double meanValue = 0.0; meanValue = mean(imageSobel)[0]; if (meanValue > 1.3) { return YES; } return NO; }
四：集成主要事項：
一、導入OpenCV類目的文件的控制器必須爲.mm的C++混編的文件
二、在方法命名和定義形參時，儘可能避免使用關鍵字開頭或直接使用關鍵字，因爲OC對此項的檢查不是很嚴格，一旦包含C++的文件之後，對關鍵字的檢測會很強，此爲須要注意的事項