OpenCV 拉普拉斯算子 output 在 C++ 中排除负值，但在 ZA7F5F32326B963827111 中不排除

Question

Performing the same Laplacian operation in C++ and Python appears to produce different results. Notably, the C++ variant does not report negative slopes in the result matrix.

I am using (C++):

Laplacian(img.clone(), img, CV_16S, 1, 1, 0, BORDER_DEFAULT);

and (Python):

img = cv2.Laplacian(img, ddepth=cv2.CV_16S, ksize=1, scale=1, delta=0, borderType=cv2.BORDER_DEFAULT)

By processing the C++ data into a more friendly text format:

outfile.open("cpp.csv");
outfile.close();
for (size_t i = 0; i < img.size().width; i++) {
    outfile.open("cpp.csv", std::ios_base::app);
    for (size_t j = 0; j < img.size().height; j++) {
        outfile << (int16_t)img.at<uchar>(j, i);
        if (j < img.size().height - 1) {
            outfile << ",";
        }
    }
    outfile << std::endl;
    outfile.close();
}

I can then compare the values with Numpy .

cpp = np.loadtxt("./cpp.csv", delimiter=',')
print("python lap min:", np.min(img))
print("c++    lap min:", np.min(cpp))

This output shows us that the CPP code is not recording negative values:

 python lap min: -133 c++ lap min: 0.0

So what is happening here? Surely I have made some sort of error, because there must be negative values in a Laplacian transformation somewhere if the image luminosity values are not static.

Image Source

The source image for each test case is a 1920x1080 full color PNG image with distinct light and dark areas. I'm using a photo of the moon. The image is converted to CV_8UC1 prior to the Laplace transformation.

Strict Typing

I have explicitly told C++ to store data with the int16_t type, which is implicitly signed by default, rather than just an int . This typing matches the output from the Laplacian storage matrix ( CV_16S ). Adding an explicit "signed" to "int16_t" produces the same result. My understanding is that the at function requires uchar typing similar to this SO answer . This is where I was wrong!!!

Version Note

Python OpenCV version: 4.1.1 (or 4.4.0, see edit section)

C++ OpenCV version: 3.4.1 (or 4.4.0, see edit section)

The documentation for these versions ( 3.4.1 and 4.1.1 ) shows no appreciable difference between the two.

Similar Questions

Laplacian variation between C++ and Python appears common on SO, but nothing had anything useful for this. I read:

• Laplacian does not give desired output
• OpenCV - laplacian different results in Python and C++
• opencv 2.4.0 laplacian different results depending on API used?

Edit - Upgrading C++ OpenCV lib

I built OpenCV v.4.4 from git, and compiled the C++ version of the code with pkg-config --cflags --libs opencv4 .The same error persists. ( cv2.getBuildInformation() says the Python is running 4.4 as well).

Edit2 - context from a Git issue:

I found a similar issue on the github repo ( here ) where the solution was storing the Laplacian result as a new Mat . My original code uses Laplacian(img.clone(), img, ...) which should produce a "deep copy" of the img matrix in place, avoiding the problem reported by the OP. I tested my code with a unique matrix anyway Laplacian(outputimg, img, ...) and saw no change in results.

Edit3 - Generalizing the problem

I processed the original code, this time replacing the Laplacian filter with either a Sobel and a custom filter2D filter. The same result is observed, Python produces good values while C++ does not.

Edit4 - Post-answer cleanup

Since this was a simple typing error, I have crossed out most of the extraneous information. This leaves it my original attempts readable, but it makes it obvious that they were not useful in the end.

Answer 1

Your C++ implementation is calling Mat::at<uchar> which means "interpret the data at this location as uchar (ie uint8_t )" but your data is of course short (ie int16 ), not uchar . From the docs on Mat::at , note that they specify:

If matrix is of type CV_16S then use Mat.at<short>(y,x) .