C OPENCV恢复边界矩形

C++ Opencv Rescale Bounding Rect

本文关键字：边界 恢复 OPENCV      更新时间：2023-10-16

所以，我有一个问题：

im在Android中进行操作，并且由于我使用手机拍摄的图像非常高，因此我想将图像大小调整到较小的图像，获取轮廓并处理图像，然后在原始图像上创建界限。为此，我需要扩展该边界框，以使其完全适合我的原始图像。我拥有的代码在原始图像上的处理和绘制边界框非常合作，但是如何进行缩放？这是代码片段：

 Mat &image = *(Mat *) matAddrRgba;
//over here I should resize image and do the processing with the resized one, and in the end, scale everything back so I can draw the bounding box to the original
    Rect bounding_rect;
    Mat thr(image.rows, image.cols, CV_8UC1);
    cvtColor(image, thr, CV_BGR2GRAY); //Convert to gray
    threshold(thr, thr, 150, 255, THRESH_BINARY + THRESH_OTSU); //Threshold the gray
    vector<vector<Point> > contours; // Vector for storing contour
    vector<Vec4i> hierarchy;
    RotatedRect rect;
    findContours(thr, contours, hierarchy, CV_RETR_CCOMP,
                 CV_CHAIN_APPROX_SIMPLE); // Find the contours in the image
    sort(contours.begin(), contours.end(),
         compareContourAreas);            //Store the index of largest contour
    bounding_rect = boundingRect(contours[0]);
    rect = minAreaRect(contours[0]);
    // matrices we'll use
    Mat rot_mat, rotated;
    // get angle and size from the bounding box
    float angle = rect.angle;
    Size rect_size = rect.size;
    if (rect.angle < -45.) {
        angle += 90.0;
        swap(rect_size.width, rect_size.height);
    }
    rot_mat = getRotationMatrix2D(rect.center, angle, 1);
    warpAffine(image, rotated, rot_mat, image.size(), INTER_CUBIC);
    image = rotated;
    cvtColor(image, thr, CV_BGR2GRAY); //Convert to gray
    threshold(thr, thr, 150, 255, THRESH_BINARY + THRESH_OTSU); //Threshold the gray
    findContours(thr, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
    sort(contours.begin(), contours.end(), compareContourAreas);
    bounding_rect = boundingRect(contours[0]);
    image = Mat(image, bounding_rect);

好吧，所以，我将从此开始：

    Mat &img = (Mat ) matAddrRgba;
    Mat image;
    double thrA = 5;
    resize(img, image, Size((int) (img.size().width / thrA), (int) (img.size().height / thrA)));
    Rect bounding_rect;
    Mat thr(image.rows, image.cols, CV_8UC1);
    cvtColor(image, thr, CV_BGR2GRAY); //Convert to gray
    threshold(thr, thr, 150, 255, THRESH_BINARY + THRESH_OTSU); //Threshold the gray
    vector<vector<Point> > contours; // Vector for storing contour
    vector<Vec4i> hierarchy;
    RotatedRect rect;
    findContours(thr, contours, hierarchy, CV_RETR_CCOMP,
                 CV_CHAIN_APPROX_SIMPLE); // Find the contours in the image
    sort(contours.begin(), contours.end(),
         compareContourAreas);            //Store the index of largest contour
    bounding_rect = boundingRect(contours[0]);
    bounding_rect.width = (int) (bounding_rect.width * thrA);
    bounding_rect.height = (int) (bounding_rect.height * thrA);
    bounding_rect.x = (int) (bounding_rect.x * thrA);
    bounding_rect.y = (int) (bounding_rect.y * thrA);
    rectangle(img, bounding_rect, Scalar(0, 172, 236, 255), 3);

如您所见，您应该有一个比例，该比例应与边界矩形的宽度，高度，x和y相乘。您可以从中找出其余的。

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