const cv = require('opencv4nodejs');

创建矩阵

const rows = 100; // height
const cols = 100; // width

var emptyMat = new cv.Mat(rows, cols, cv.CV_8UC3);
8位无符号3通道矩阵，就是常见的RGB数组[0-255,0-255,0-255]

var whiteMat = new cv.Mat(rows, cols, cv.CV_8UC1, 255);
var blueMat = new cv.Mat(rows, cols, cv.CV_8UC3, [255, 0, 0]);

• 使用Array创建
  const matData = [
  [[255, 0, 0], [255, 0, 0], [255, 0, 0]],
  [[0, 0, 0], [0, 0, 0], [0, 0, 0]],
  [[255, 0, 0], [255, 0, 0], [255, 0, 0]]
  ];
  var matFromArray = new cv.Mat(matData, cv.CV_8UC3);

• 使用Buffer创建
  const charData = [255, 0, ...];
  const matFromArray = new cv.Mat(Buffer.from(charData), rows, cols, cv.CV_8UC3);

• 创建一个点
  const pt2 = new cv.Point(100, 100);
  const pt3 = new cv.Point(100, 100, 0.5);

• 创建一个向量
  const vec2 = new cv.Vec(100, 100);
  const vec3 = new cv.Vec(100, 100, 0.5);
  const vec4 = new cv.Vec(100, 100, 0.5, 0.5);

矩阵、向量操作

const mat0 = new cv.Mat(...);
const mat1 = new cv.Mat(...);

• 四则运算
  const matMultipliedByScalar = mat0.mul(0.5); 标量乘法
  const matDividedByScalar = mat0.div(2); 标量除法
  const mat0PlusMat1 = mat0.add(mat1); 矩阵加法
  const mat0MinusMat1 = mat0.sub(mat1); 矩阵减法
  const mat0MulMat1 = mat0.hMul(mat1); 矩阵乘法
  const mat0DivMat1 = mat0.hDiv(mat1); 矩阵除法

• 矩阵逻辑运算操作
  const mat0AndMat1 = mat0.and(mat1);
  const mat0OrMat1 = mat0.or(mat1);
  const mat0bwAndMat1 = mat0.bitwiseAnd(mat1);
  const mat0bwOrMat1 = mat0.bitwiseOr(mat1);
  const mat0bwXorMat1 = mat0.bitwiseXor(mat1);
  const mat0bwNot = mat0.bitwiseNot();

访问矩阵、向量数据

const matBGR = new cv.Mat(..., cv.CV_8UC3);
const matGray = new cv.Mat(..., cv.CV_8UC1);

• 获取到像素点的值
  const vec3 = matBGR.at(200, 100);
  const grayVal = matGray.at(200, 100);

• 使用解构赋值语法获取值
  const [b, g, r] = matBGR.atRaw(200, 100);

• 设置单个像素点的值
  matBGR.set(50, 50, [255, 0, 0]);
  matBGR.set(50, 50, new Vec(255, 0, 0));
  matGray.set(50, 50, 255);

• 得到一个偏移量为（ 50, 50）矩阵区域的25x25的小区域
  const width = 25;
  const height = 25;
  const region = matBGR.getRegion(new cv.Rect(50, 50, width, height));
  const matAsBuffer = matBGR.getData();
  const matAsArray = matBGR.getDataAsArray();

IO

• 读取图片
  const mat = cv.imread('./path/img.jpg');
  cv.imreadAsync('./path/img.jpg', (err, mat) => {})

• 保存图片
  cv.imwrite('./path/img.png', mat);
  cv.imwriteAsync('./path/img.jpg', mat,(err) => {})

• 展示图片
  cv.imshow('a window name', mat);
  cv.waitKey();

• 加载base64编码的图片
  const base64text='data:image/png;base64,R0lGO..'; //base64字符串
  const base64data =base64text.replace('data:image/jpeg;base64','')

const buffer = Buffer.from(base64data,'base64');
const image = cv.imdecode(buffer);

• 转换矩阵为base64编码的图片
  const outBase64 = cv.imencode('.jpg', croppedImage).toString('base64');
  const htmlImg='<img src=data:image/jpeg;base64,'+outBase64 + '>'; //Create insert into HTML compatible <img> tag

• 捕获webcam资源
  const devicePort = 0;
  const wCap = new cv.VideoCapture(devicePort);

• 捕获视频资源
  const vCap = new cv.VideoCapture('./path/video.mp4');

• 读取帧
  const frame = vCap.read();
  vCap.readAsync((err, frame) => {});

• 循环获取
  const delay = 10;
  let done = false;
  while (!done) {
    let frame = vCap.read();
    if (frame.empty) {
      vCap.reset();
      frame = vCap.read();
    }
      const key = cv.waitKey(delay);
      done = key !== 255;
  }

• 类型转换
  const matSignedInt = matBGR.convertTo(cv.CV_32SC3);
  const matDoublePrecision = matBGR.convertTo(cv.CV_64FC3);

• 转换颜色制度
  const matGray = matBGR.bgrToGray();
  const matHSV = matBGR.cvtColor(cv.COLOR_BGR2HSV);
  const matLab = matBGR.cvtColor(cv.COLOR_BGR2Lab);

• 调整矩阵大小
  const matHalfSize = matBGR.rescale(0.5);
  const mat100x100 = matBGR.resize(100, 100);
  const matMaxDimIs100 = matBGR.resizeToMax(100);

• 获取通道、通过通道构建矩阵
  const [matB, matG, matR] = matBGR.splitChannels();
  const matRGB = new cv.Mat([matR, matB, matG]);