本文使用javaCV封装后的OpenCv
<dependency> <groupId>org.bytedeco</groupId> <artifactId>javacv-platform</artifactId> <version>1.5.5</version> </dependency>
在openCv中有一函数用于读取图片 imread(),保存图片imwrite()
由于javaCv二次封装,所以函数目录和openCv目录不同,javaCv函数在opencv_imgcodecs中,因为javaCv目前没有完整的文档所以只能查看源代码一个个找,后面自己使用别的功能时是需要自己看源代码的,反正挺苦逼的。
public static void main(String[] args) { Mat mat = opencv_imgcodecs.imread("D:\\leiningen\\cat.jpg"); ImageViewer imageViewer = new ImageViewer(mat); imageViewer.imshow(); }
ImageViewer 我着实没有找到在javaCv中相应的类,不过找到一个opencv_highgui.imshow()方法但是用不了,我看了里面的注释需要搭配线程使用反正我没搞出来。所以我也把这个类ImageViewer源代码贴出来吧(我放在最后了)。
public static void main(String[] args) { Mat mat = opencv_imgcodecs.imread("D:\\leiningen\\cat.jpg"); opencv_imgcodecs.imwrite("D:\\leiningen\\cat1.png",mat); }
从代码中可以看到陌生的对象Mat,这个是矩阵的意思,这个对象是openCv的核心,简单介绍一下。
首先我们来创建一个矩阵开始。
public static void main(String[] args) { //创建RGB颜色当前是蓝色 Scalar scalar = new Scalar(255, 0, 0, 0); // R G B 0 //Size:width、height Mat mat = new Mat(new Size(100,200), opencv_core.CV_8UC3,scalar); ImageViewer imageViewer = new ImageViewer(mat); imageViewer.imshow(); }
上面代码片先是读取在保存,唯一区别就是保存时用的格式使用的是png,不需要进行图像编码和令人发狂的字节操作
按照官方说法:
JPEG可以使用CV_IMWRITE_JPEG_OUALITY参数,参数值范围在0 ~ 100 (值越大图像质量越高)默认值是95。
PNG,可以使用0 ~ 9 作为压缩程度的参数值,值越大图像质量越小,压缩时间越长,默认值是3.
package com.cloud.iot.util; import org.bytedeco.javacpp.BytePointer; import org.bytedeco.opencv.opencv_core.Mat; import javax.swing.*; import java.awt.*; import java.awt.image.BufferedImage; import java.awt.image.DataBufferByte; import java.nio.ByteBuffer; public class ImageViewer { private JLabel imageView; private Mat image; private String windowName; public ImageViewer(Mat image) { this.image = image; } public ImageViewer(Mat image, String windowName) { this.image = image; this.windowName = windowName; } /** * 窗口展示 */ public void imshow() { setSystemLookAndFeel(); Image loadedImage = toBufferedImage(image); JFrame frame = createJFrame(windowName, image.arrayWidth(), image.arrayHeight()); imageView.setIcon(new ImageIcon(loadedImage)); frame.pack(); frame.setLocationRelativeTo(null); frame.setVisible(true); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);// 用户点击窗口关闭 } private void setSystemLookAndFeel() { try { UIManager.setLookAndFeel(UIManager.getSystemLookAndFeelClassName()); } catch (ClassNotFoundException e) { e.printStackTrace(); } catch (InstantiationException e) { e.printStackTrace(); } catch (IllegalAccessException e) { e.printStackTrace(); } catch (UnsupportedLookAndFeelException e) { e.printStackTrace(); } } private JFrame createJFrame(String windowName, int width, int height) { JFrame frame = new JFrame(windowName); imageView = new JLabel(); final JScrollPane imageScrollPane = new JScrollPane(imageView); imageScrollPane.setPreferredSize(new Dimension(width, height)); frame.add(imageScrollPane, BorderLayout.CENTER); frame.setDefaultCloseOperation(WindowConstants.EXIT_ON_CLOSE); return frame; } private Image toBufferedImage(Mat matrix) { int type = BufferedImage.TYPE_BYTE_GRAY; if (matrix.channels() > 1) { type = BufferedImage.TYPE_3BYTE_BGR; } ByteBuffer byteBuffer = matrix.getByteBuffer(); byte[] b = new byte[byteBuffer.remaining()]; byteBuffer.get(b,0,b.length); BufferedImage image = new BufferedImage(matrix.cols(), matrix.rows(), type); final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData(); System.arraycopy(b, 0, targetPixels, 0, b.length); return image; } }
今天就到这·······································································over