Why does Mat.forEach doesn't change itself? - c++

Question

Basically, I'm trying to use less pixels to represent an image itself.
The steps are below:
Say I will input an image with size [1000*600], then I got 600_000 pixels(rgb), which could be [600_000, 3] vectors. K-Means is used to get its cluster centers.
The each pixel in the image will be placed with its nearest neighbor among the clusters found via K-Means.
The source is:
template <typename T>
void NN(Point3_<T>& pixel, const Mat& points)
{
vector<T> vt {pixel.x, pixel.x, pixel.z};
double min_dist = LDBL_MAX;
int min_index = -1;
for (int i = 0; i < points.rows; ++ i)
{
double dist = norm(vt, points.row(i), NORM_L2);
if (dist < min_dist)
{
min_dist = dist;
min_index = i;
}
}
// assert(min_index != -1);
pixel.x = points.at<T>(min_index, 0);
pixel.y = points.at<T>(min_index, 1);
pixel.z = points.at<T>(min_index, 2);
}
template <typename T>
void NN(Mat& img, const Mat& points)
{
timer::start("assign");
img.forEach<Point3_<T>>([&points](Point3_<T> &pixel, const int position[])
{
NN(pixel, points);
});
timer::stop<ms>();
}
Mat kmeans(const Mat& original_img, const int K)
{
Mat img;
original_img.reshape(3, original_img.rows * original_img.cols)
.convertTo(img, CV_32FC3);
timer::start("K-means cluster");
// Require img.type() == CV_32F
Mat clusters = BOWKMeansTrainer(K).cluster(img);
timer::stop<ms>();
// Type 5 -> Type 0: 32FC1 -> 8UC1
// K rows, 3 cols, 8UC1
clusters.convertTo(clusters, CV_8UC1);
Mat output_img = original_img;
NN<uchar>(output_img, clusters);
// assert won't fire, why?
assert(equal(original_img.begin<uchar>(), original_img.end<uchar>(),
output_img.begin<uchar>()));
return output_img;
}
int main(int argc, char* argv[])
{
vector<int> ks {2, 16};
string filename = "1";
string pathname = string("./img/") + filename + ".jpg";
Mat img = imread(pathname);
for (const int& K: ks)
{
imshow(int_to_string(K), kmeans(img, K));
// write_img(filename, "kmeans", K, kmeans(img, K));
}
std::cout << "Press enter to continue...";
cin.get();
}
The questions are:
The assert() in kmeans() won't fire. That is, the mat object original_img is identical to output_img. How could this happen?
The two imwrite() in main() will show two identical 2-value images. That is, the K-Means with K=2 works, while the following with K=16 does not. Note that if we output one image per execution, everything is fine.
The buggy output is below:
The original image and K-Means with K=16 could be seen below:

Answer 1

Thank god! I've found the cause.
In kmeans(), the below code will call Mat's copy constructor, which costs O(1) to assign original_img's header to output_img's.
Mat output_img = original_img;
This is the reason why the assert won't fire.