我利用OpenCV GrabCut功能执行图像分割。当按照以下代码查看分割图像时,分割是合理/正确的。但是,在查看(尝试使用)segmrntation掩码值时,我得到一些非常大的数字,而不是cv::GrabCutClasses
enum所期望的枚举值。
void doGrabCut(){
Vector2i imgDims = getImageDims();
//Wite image to OpenCV Mat.
const Vector4u *rgb = getRGB();
cv::Mat rgbMat(imgDims.height, imgDims.width, CV_8UC3);
for (int i = 0; i < imgDims.height; i++) {
for (int j = 0; j < imgDims.width; j++) {
int idx = i * imgDims.width + j;
rgbMat.ptr<cv::Vec3b>(i)[j][2] = rgb[idx].x;
rgbMat.ptr<cv::Vec3b>(i)[j][1] = rgb[idx].y;
rgbMat.ptr<cv::Vec3b>(i)[j][0] = rgb[idx].z;
}
}
//Do graph cut.
cv::Mat res, fgModel, bgModel;
cv::Rect bb(bb_begin.x, bb_begin.y, bb_end.x - bb_begin.x, bb_end.y - bb_begin.y);
cv::grabCut(rgbMat, res, bb, bgModel, fgModel, 10, cv::GC_INIT_WITH_RECT);
cv::compare(res, cv::GC_PR_FGD, res, cv::CMP_EQ);
//Write mask.
Vector4u *maskPtr = getMask();//uchar
for (int i = 0; i < imgDims.height; i++) {
for (int j = 0; j < imgDims.width; j++) {
cv::GrabCutClasses classification = res.at<cv::GrabCutClasses>(i, j);
int idx = i * imgDims.width + j;
std::cout << classification << std::endl;//Strange numbers here.
maskPtr[idx].x = (classification == cv::GC_PR_FGD) ? 255 : 0;//This always evaluates to 0.
}
}
cv::Mat foreground(rgbMat.size(), CV_8UC3, cv::Scalar(255, 255, 255));
rgbMat.copyTo(foreground, res);
cv::imshow("GC Output", foreground);
}
为什么当分段在定性上正确时,会在枚举之外得到数字?
答案 0 :(得分:0)
我怀疑您的//Write mask.
步骤,为什么要重新res
并将maskPtr
修改为maskPtr[idx].x = (classification == cv::GC_PR_FGD) ? 255 : 0;
,基本上您已经存储了单通道二进制图像在res
变量中,cv::compare()
返回二进制图像
但是,如果您仍想通过迭代调试值,则应使用标准技术迭代单个通道图像:
for (int i = 0; i < m.rows; i++) {
for (int j = 0; j < m.cols; j++) {
uchar classification = res.at<uchar>(i, j);
std::cout << int(classification) << ", ";
}
}
当您在迭代单个频道时,您必须使用res.at<uchar>(i, j)
而不是res.at<cv::GrabCutClasses>
。