从NumPy数组到Mat（OpenCV）的C ++转换 [英] C++ conversion from NumPy array to Mat (OpenCV)

问题描述

我正在围绕ArUco增强现实库（基于OpenCV）编写一个薄包装。我尝试构建的界面非常简单：

I am writing a thin wrapper around ArUco augmented reality library (which is based on OpenCV). An interface I am trying to build is very simple:

• Python将图像传递给C ++代码;


• C ++代码检测标记并将其位置和其他信息作为元组的返回到Python。

如何在Python中表示图像以将其传递给C ++。对于GUI和相机管理我将使用PyQt，所以最初它将是QImage，但我不能简单地传递给OpenCV（或我可以？）。首先，我试图使用嵌套元组来表示每个像素的行，列和颜色，所以我最后得到了这个示例代码：

However, I couldn't figure out how to represent an image in Python to pass it to C++. For GUI and camera management I am going to use PyQt, so initially it is going to be QImage, but I can't simply pass it to OpenCV (or I can?). At first, I tried to use nested tuples to represent row, column and color of each pixel, so I ended up with this sample code:

using namespace cv;
namespace py = boost::python;

void display(py::tuple pix)
{
    /*
        Receive image from Python and display it.
    */
    Mat img(py::len(pix), py::len(pix[0]), CV_8UC3, Scalar(0, 0, 255));
    for (int y = 0; y < py::len(pix); y++)
        for (int x = 0; x < py::len(pix[y]); x++)
        {
            Vec3b rgb;
            for (int i = 0; i < 3; i++)
                rgb[i] = py::extract<int>(pix[y][x][i]);
            img.at<Vec3b>(Point(x, y)) = rgb;
        }
    imshow("Image", img);
    waitKey(0);
}

BOOST_PYTHON_MODULE(aruco)
{
    py::def("display", display);
}

原来是慢得令人痛苦，所以我去谷歌搜索解决方案应该更快：使用NumPy数组，所以代码看起来像这样：

It turned out to be painfully slow (a few seconds for a single frame), so I went googling and found solution that should be much faster: use NumPy arrays, so the code would look something like that:

void display(py::object array)
{
    Mat img;
    // ... some magic here to convert NumPy array to Mat ...
    imshow("Image", img);
    waitKey(0);
}

<只是一个Python对象）到OpenCV Mat。

However, I have no idea how to convert NumPy Array (which in C++ level is just a Python Object) to OpenCV Mat. I would appreciate any help here.

或者，也许NumPy不是真的需要，所以我可以直接传递QImage Python对象直接到C ++层？或者也许有一个不同的方法来解决这个问题？

Alternatively, maybe NumPy is not really needed, so I could just pass QImage Python object directly to C++ layer? Or maybe there is a different approach to this problem? Any advice is appreciated!

推荐答案

在你的情况下，最好的解决方案是使用自定义boost :: python转换器为cv :: Mat对象。 OpenCV有Python包装，当你使用这个包装你使用Numpy数组 - 你甚至不需要知道这些数组被转换为cv :: Mat对象，而穿越c ++< - > python边界。写这样的转换器为简单类型是很容易，但创建转换器为cv :: Mat不简单。 Fortunetely其他人已经这样做了 - 这里是OpenCV 2.x和此处为3.x.如果你不熟悉boost :: python转换器，本文应该可以帮助你。

希望它有帮助，如果你有任何问题，请告诉我们。

The best solution in your situation is using custom boost::python converter for cv::Mat object. OpenCV has Python wrapper and when you are using this wrapper you are operating on Numpy arrays - you don't even need to know that those arrays are converted to cv::Mat objects while "crossing the c++ <-> python border". Writing such converter for simple type is quite easy, however creating converter for cv::Mat isn't simple. Fortunetely someone else already did this - here is version for OpenCV 2.x and here for 3.x. If you are not familiar with boost::python converters, this article should help you.
Hope it helps, if you wil have any problems, let us know.

这篇关于从NumPy数组到Mat（OpenCV）的C ++转换的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！