OpenCV : k-means clustering in iOS - c++

Question

Now I am trying to do k-means clustering in iOS. To do k-means, I converted from UIImage to cv::Mat and made function to cluster cv::Mat. The function does not work well.
The result looks like almost good, but right side cols get black. I read openCV reference and I have no idea what's wrong.
The code is below. If someone help me, it is going to be really appriciated.
Excuse for my poor English...
- (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;
}
- (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
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);
CGColorSpaceRelease(colorSpace);
return cvMat;
}
- (cv::Mat)kMeansClustering:(cv::Mat)input
{
cv::Mat samples(input.rows * input.cols, 3, CV_32F);
for( int y = 0; y < input.rows; y++ ){
for( int x = 0; x < input.cols; x++ ){
for( int z = 0; z < 3; z++){
samples.at<float>(y + x*input.rows, z) = input.at<cv::Vec3b>(y,x)[z];
}
}
}
int clusterCount = 20;
cv::Mat labels;
int attempts = 5;
cv::Mat centers;
kmeans(samples, clusterCount, labels, cv::TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 100, 0.01), attempts, cv::KMEANS_PP_CENTERS, centers );
cv::Mat new_image( input.rows, input.cols, input.type());
for( int y = 0; y < input.rows; y++ ){
for( int x = 0; x < input.cols; x++ )
{
int cluster_idx = labels.at<int>(y + x*input.rows,0);
new_image.at<cv::Vec3b>(y,x)[0] = centers.at<float>(cluster_idx, 0);
new_image.at<cv::Vec3b>(y,x)[1] = centers.at<float>(cluster_idx, 1);
new_image.at<cv::Vec3b>(y,x)[2] = centers.at<float>(cluster_idx, 2);
}
}
return new_image;
}

Answer 1

You are supplying kMeansClustering with a four-channel image, it wants 3 channels. Try losing the alpha channel.
Add this at the top of the function:
cv::cvtColor(input , input , CV_RGBA2RGB);
so it looks like this:
- (cv::Mat)kMeansClustering:(cv::Mat)input
{
cv::cvtColor(input , input , CV_RGBA2RGB);
cv::Mat samples(input.rows * input.cols, 3, CV_32F);