ios - 带有 objective-c 的 OpenCV

Question

引用这个OpenCV Adaptive Threshold OCR 我用 OpenCV 在 objective-c 中完成了以下代码

- (cv::Mat)cvMatFromUIImage:(UIImage *)image
{
    CGColorSpaceRef colorSpace = CGImageGetColorSpace(image.CGImage);
    CGFloat cols = image.size.width;
    CGFloat rows = image.size.height;

    cv::Mat cvMat(rows, cols, CV_8UC4); // 8 bits per component, 4 channels (color channels + alpha)

    CGContextRef contextRef = CGBitmapContextCreate(cvMat.data,                 // Pointer to  data
                                                    cols,                       // Width of bitmap
                                                    rows,                       // Height of bitmap
                                                    8,                          // Bits per component
                                                    cvMat.step[0],              // Bytes per row
                                                    colorSpace,                 // Colorspace
                                                    kCGImageAlphaNoneSkipLast |
                                                    kCGBitmapByteOrderDefault); // Bitmap info flags

    CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), image.CGImage);
    CGContextRelease(contextRef);

    return cvMat;
}
-(UIImage *)UIImageFromCVMat:(cv::Mat)cvMat
{
    NSData *data = [NSData dataWithBytes:cvMat.data length:cvMat.elemSize()*cvMat.total()];
    CGColorSpaceRef colorSpace;

    if (cvMat.elemSize() == 1) {
        colorSpace = CGColorSpaceCreateDeviceGray();
    } else {
        colorSpace = CGColorSpaceCreateDeviceRGB();
    }

    CGDataProviderRef provider = CGDataProviderCreateWithCFData((__bridge CFDataRef)data);

    // Creating CGImage from cv::Mat
    CGImageRef imageRef = CGImageCreate(cvMat.cols,                                 //width
                                        cvMat.rows,                                 //height
                                        8,                                          //bits per component
                                        8 * cvMat.elemSize(),                       //bits per pixel
                                        cvMat.step[0],                            //bytesPerRow
                                        colorSpace,                                 //colorspace
                                        kCGImageAlphaNone|kCGBitmapByteOrderDefault,// bitmap info
                                        provider,                                   //CGDataProviderRef
                                        NULL,                                       //decode
                                        false,                                      //should interpolate
                                        kCGRenderingIntentDefault                   //intent
                                        );


    // Getting UIImage from CGImage
    UIImage *finalImage = [UIImage imageWithCGImage:imageRef];
    CGImageRelease(imageRef);
    CGDataProviderRelease(provider);
    CGColorSpaceRelease(colorSpace);

    return finalImage;
}
-(void) CalcBlockMeanVariance:(cv::Mat)Img resource: (cv::Mat)Res //float blockSide=21) // blockSide - the parameter (set greater for larger font on image)
{
    float blockSide = 21;
    cv::Mat I;
    Img.convertTo(I,CV_32FC1);
    Res=cv::Mat::zeros(Img.rows/blockSide,Img.cols/blockSide,CV_32FC1);
    cv::Mat inpaintmask;
    cv::Mat patch;
    cv::Mat smallImg;
    cv::Scalar m,s;

    for(int i=0;i<Img.rows-blockSide;i+=blockSide)
    {
        for (int j=0;j<Img.cols-blockSide;j+=blockSide)
        {
            patch=I(cv::Range::Range(i,i+blockSide+1),cv::Range::Range(j,j+blockSide+1));
            cv::meanStdDev(patch,m,s);
            if(s[0]>0.01) // Thresholding parameter (set smaller for lower contrast image)
            {
                Res.at<float>(i/blockSide,j/blockSide)=m[0];
            }else
            {
                Res.at<float>(i/blockSide,j/blockSide)=0;
            }
        }
    }

    cv::resize(I,smallImg,Res.size());

    cv::threshold(Res,inpaintmask,0.02,1.0,cv::THRESH_BINARY);

    cv::Mat inpainted;
    smallImg.convertTo(smallImg,CV_8UC1,255);


    inpaintmask.convertTo(inpaintmask,CV_8UC1);
    inpaint(smallImg, inpaintmask, inpainted, 5, cv::INPAINT_TELEA);

    cv::resize(inpainted,Res,Img.size());
    Res.convertTo(Res,CV_32FC1,1.0/255.0);

}
- (IBAction)renderThis:(id)sender{
 cv::Mat source=[self cvMatFromUIImage: self.imgTaken];//cv::imread("Test2.JPG",0);
    cv::Mat Img;
    cv::cvtColor(source, Img, cv::COLOR_RGB2GRAY);
    cv::Mat res;
    Img.convertTo(Img,CV_32FC1,1.0/255.0);
    [self CalcBlockMeanVariance:Img resource:res];
    res=1.0-res;
    res=Img+res;
  cv::threshold(res,res,0.85,1,cv::THRESH_BINARY);
    cv::resize(res,res,cv::Size(res.cols/2,res.rows/2));
  self.imgPreview.image = [self UIImageFromCVMat:(res*255)];
}

在输出图像中获取黑色图像。任何人都可以指导我吗？

Answer 1

找到解决方案，

只需将类型从 CV_32FC1 更改为 CV_8UC3 就可以了:)