本文整理了Java中org.opencv.core.Core.flip()方法的一些代码示例，展示了Core.flip()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Core.flip()方法的具体详情如下：
包路径：org.opencv.core.Core
类名称：Core
方法名：flip

Core.flip介绍

[英]Flips a 2D array around vertical, horizontal, or both axes.

The function flip flips the array in one of three different ways (row and column indices are 0-based):

dst _(ij) =<BR>

The example scenarios of using the function are the following:

• Vertical flipping of the image (flipCode == 0) to switch between top-left and bottom-left image origin. This is a typical operation in video processing on Microsoft Windows* OS.
• Horizontal flipping of the image with the subsequent horizontal shift and absolute difference calculation to check for a vertical-axis symmetry (flipCode > 0).
• Simultaneous horizontal and vertical flipping of the image with the subsequent shift and absolute difference calculation to check for a central symmetry (flipCode < 0).
• Reversing the order of point arrays (flipCode > 0 or flipCode == 0).
  [中]围绕垂直、水平或两个轴翻转二维阵列。
  函数flip以三种不同方式之一翻转数组（行和列索引基于0）：
  dst_uj（ij）=<BR>
  使用该功能的示例场景如下：
  垂直翻转图像（flipCode == 0）以在左上角和左下角图像原点之间切换。这是Microsoft Windows操作系统上视频处理的典型操作。
  *水平翻转图像，随后进行水平移动和绝对差计算，以检查垂直轴对称性（flipCode > 0）。
  *同时水平和垂直翻转图像，随后进行移位和绝对差计算，以检查中心对称性（flipCode < 0）。
  *颠倒点阵列的顺序（flipCode > 0或flipCode == 0）。

代码示例

代码示例来源：origin: ytai/IOIOPlotter

private static void rotateCCW(Mat mat) {
  Core.transpose(mat, mat);
  Core.flip(mat, mat, 0);
}

代码示例来源：origin: nroduit/Weasis

public static ImageCV flip(Mat source, int flipCvType) {
  if (flipCvType < 0) {
    return ImageCV.toImageCV(source);
  }
  Objects.requireNonNull(source);
  ImageCV dstImg = new ImageCV();
  Core.flip(source, dstImg, flipCvType);
  return dstImg;
}

代码示例来源：origin: ytai/IOIOPlotter

Core.flip(srcImage_, srcImage_, 1);

代码示例来源：origin: ytai/IOIOPlotter

Core.flip(srcImage_, edgesImage_, 1);
} else {
  srcImage_.copyTo(edgesImage_);

代码示例来源：origin: Qualeams/Android-Face-Recognition-with-Deep-Learning-Test-Framework

Core.flip(imgRgba,imgRgba,1);

代码示例来源：origin: Qualeams/Android-Face-Recognition-with-Deep-Learning-Test-Framework

public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
  Mat imgRgba = inputFrame.rgba();
  Mat img = new Mat();
  imgRgba.copyTo(img);
  List<Mat> images = ppF.getProcessedImage(img, PreProcessorFactory.PreprocessingMode.RECOGNITION);
  Rect[] faces = ppF.getFacesForRecognition();
  // Selfie / Mirror mode
  if(front_camera){
    Core.flip(imgRgba,imgRgba,1);
  }
  if(images == null || images.size() == 0 || faces == null || faces.length == 0 || ! (images.size() == faces.length)){
    // skip
    return imgRgba;
  } else {
    faces = MatOperation.rotateFaces(imgRgba, faces, ppF.getAngleForRecognition());
    for(int i = 0; i<faces.length; i++){
      MatOperation.drawRectangleAndLabelOnPreview(imgRgba, faces[i], rec.recognize(images.get(i), ""), front_camera);
    }
    return imgRgba;
  }
}

代码示例来源：origin: Qualeams/Android-Face-Recognition-with-Deep-Learning-Test-Framework

@Override
public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
  Mat imgRgba = inputFrame.rgba();
  Mat img = new Mat();
  imgRgba.copyTo(img);
  List<Mat> images = ppF.getCroppedImage(img);
  Rect[] faces = ppF.getFacesForRecognition();
  // Selfie / Mirror mode
  if(front_camera){
    Core.flip(imgRgba,imgRgba,1);
  }
  if(images == null || images.size() == 0 || faces == null || faces.length == 0 || ! (images.size() == faces.length)){
    // skip
    return imgRgba;
  } else {
    faces = MatOperation.rotateFaces(imgRgba, faces, ppF.getAngleForRecognition());
    for(int i = 0; i<faces.length; i++){
      MatOperation.drawRectangleAndLabelOnPreview(imgRgba, faces[i], "", front_camera);
    }
    return imgRgba;
  }
}

代码示例来源：origin: openpnp/openpnp

Core.flip(timage.t(), timage, 1);

代码示例来源：origin: openpnp/openpnp

protected BufferedImage transformImage(BufferedImage image) {
  Mat mat = OpenCvUtils.toMat(image);
  mat = crop(mat);
  mat = calibrate(mat);
  mat = undistort(mat);
  // apply affine transformations
  mat = scale(mat, scaleWidth, scaleHeight);
  
  mat = rotate(mat, rotation);
  mat = offset(mat, offsetX, offsetY);
  
  mat = deinterlace(mat);
  if (flipX || flipY) {
    int flipCode;
    if (flipX && flipY) {
      flipCode = -1;
    }
    else {
      flipCode = flipX ? 0 : 1;
    }
    Core.flip(mat, mat, flipCode);
  }
  image = OpenCvUtils.toBufferedImage(mat);
  mat.release();
  return image;
}