新增 images.inRange(), images.findCircles, images.matToImage
修复 调用模块时模块本身的错误提醒不明显的问题
This commit is contained in:
hyb1996
@@ -1,330 +1,379 @@
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module.exports = function (__runtime__, scope) {
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const defaultColorThreshold = 4;
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importPackage(org.opencv.core);
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const Imgproc = org.opencv.imgproc.Imgproc;
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module.exports = function (runtime, scope) {
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function images(){
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}
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util.__assignFunctions__(runtime.images, images, ['requestScreenCapture', 'captureScreen', 'read', 'copy', 'load', 'clip', 'pixel'])
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images.opencvImporter = JavaImporter(
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org.opencv.core.Point,
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org.opencv.core.Point3,
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org.opencv.core.Rect,
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org.opencv.core.Algorithm,
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org.opencv.core.Scalar,
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org.opencv.core.Size,
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org.opencv.core.Core,
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org.opencv.core.CvException,
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org.opencv.core.CvType,
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org.opencv.core.TermCriteria,
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org.opencv.core.RotatedRect,
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org.opencv.core.Range,
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org.opencv.imgproc.Imgproc,
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com.stardust.autojs.core.opencv
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);
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with (images.opencvImporter) {
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const defaultColorThreshold = 4;
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var images = {};
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var colors = Object.create(__runtime__.colors);
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colors.alpha = function (color) {
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color = parseColor(color);
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return color >>> 24;
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}
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colors.red = function (color) {
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color = parseColor(color);
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return (color >> 16) & 0xFF;
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}
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colors.green = function (color) {
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color = parseColor(color);
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return (color >> 8) & 0xFF;
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}
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colors.blue = function (color) {
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color = parseColor(color);
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return color & 0xFF;
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}
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var colors = Object.create(runtime.colors);
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colors.alpha = function (color) {
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color = parseColor(color);
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return color >>> 24;
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}
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colors.red = function (color) {
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color = parseColor(color);
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return (color >> 16) & 0xFF;
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}
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colors.green = function (color) {
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color = parseColor(color);
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return (color >> 8) & 0xFF;
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}
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colors.blue = function (color) {
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color = parseColor(color);
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return color & 0xFF;
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}
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colors.isSimilar = function (c1, c2, threshold, algorithm) {
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c1 = parseColor(c1);
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c2 = parseColor(c2);
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threshold = threshold == undefined ? 4 : threshold;
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algorithm = algorithm == undefined ? "diff" : algorithm;
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var colorDetector = getColorDetector(c1, algorithm, threshold);
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return colorDetector.detectsColor(colors.red(c2), colors.green(c2), colors.blue(c2));
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}
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colors.isSimilar = function (c1, c2, threshold, algorithm) {
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c1 = parseColor(c1);
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c2 = parseColor(c2);
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threshold = threshold == undefined ? 4 : threshold;
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algorithm = algorithm == undefined ? "diff" : algorithm;
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var colorDetector = getColorDetector(c1, algorithm, threshold);
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return colorDetector.detectsColor(colors.red(c2), colors.green(c2), colors.blue(c2));
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}
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if (android.os.Build.VERSION.SDK_INT < 19) {
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var javaImages = runtime.getImages();
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var colorFinder = javaImages.colorFinder;
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images.save = function (img, path, format, quality) {
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format = format || "png";
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quality = quality == undefined ? 100 : quality;
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return javaImages.save(img, path, format, quality);
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}
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images.saveImage = images.save;
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images.grayscale = function (img, dstCn) {
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return images.cvtColor(img, "BGR2GRAY", dstCn);
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}
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images.threshold = function (img, threshold, maxVal, type) {
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var mat = new Mat();
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type = type || "BINARY";
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type = Imgproc["THRESH_" + type];
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Imgproc.threshold(img.mat, mat, threshold, maxVal, type);
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return images.matToImage(mat);
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}
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images.inRange = function (img, lowerBound, upperBound) {
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var lb, ub;
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if (typeof (lowerBound) == 'string') {
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if (typeof (upperBound) == 'string') {
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lb = new Scalar(colors.red(lowerBound), colors.green(lowerBound),
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colors.blue(lowerBound), colors.alpha(lowerBound));
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ub = new Scalar(colors.red(upperBound), colors.green(upperBound),
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colors.blue(upperBound), colors.alpha(lowerBound));
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} else if (typeof (upperBound) == 'number') {
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var color = lowerBound;
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var threshold = upperBound;
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lb = new Scalar(colors.red(color) - threshold, colors.green(color) - threshold,
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colors.blue(color) - threshold, colors.alpha(color));
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ub = new Scalar(colors.red(color) + threshold, colors.green(color) + threshold,
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colors.blue(color) + threshold, colors.alpha(color));
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}else{
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throw new TypeError('lowerBound = ' + lowerBound, + 'upperBound = ' + upperBound);
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}
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}
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var bi = new Mat();
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Core.inRange(img.mat, lb, ub, bi);
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return images.matToImage(bi);
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}
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images.adaptiveThreshold = function(img, maxValue, adaptiveMethod, thresholdType, blockSize, C){
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var mat = new Mat();
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adaptiveMethod = Imgproc["ADAPTIVE_THRESH_" + adaptiveMethod];
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thresholdType = Imgproc["THRESH_" + thresholdType];
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Imgproc.adaptiveThreshold(img.mat, mat, maxValue, adaptiveMethod, thresholdType, blockSize, C);
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return images.matToImage(mat);
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}
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images.blur = function (img, size, point, type) {
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var mat = new Mat();
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size = newSize(size);
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type = Imgproc["BORDER_" + (type || "CONSTANT")];
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if (point == undefined) {
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Imgproc.blur(img.mat, mat, size);
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} else {
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Imgproc.blur(img.mat, mat, size, new Point(point[0], point[1]), type);
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}
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return images.matToImage(mat);
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}
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images.medianBlur = function (img, size) {
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var mat = new Mat();
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Imgproc.medianBlur(img.mat, mat, size);
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return images.matToImage(mat);
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}
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images.gaussianBlur = function (img, size, sigmaX, sigmaY, type) {
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var mat = new Mat();
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size = newSize(size);
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sigmaX = sigmaX == undefined ? 0 : sigmaX;
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sigmaY = sigmaY == undefined ? 0 : sigmaY;
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type = Imgproc["BORDER_" + (type || "DEFAULT")];
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Imgproc.GaussianBlur(img.mat, mat, size, sigmaX, sigmaY, type);
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return images.matToImage(mat);
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}
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images.cvtColor = function (img, code, dstCn) {
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var mat = new Mat();
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code = Imgproc["COLOR_" + code];
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if (dstCn == undefined) {
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Imgproc.cvtColor(img.mat, mat, code);
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} else {
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Imgproc.cvtColor(img.mat, mat, code, dstCn);
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}
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return images.matToImage(mat);
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}
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images.findCircles = function(grayImg, options) {
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options = options || {};
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var mat = options.region == undefined ? grayImg.mat : new Mat(grayImg.mat, buildRegion(options.region, grayImg));
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var resultMat = new Mat()
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var dp = options.dp == undefined ? 1 : options.dp;
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var minDst = options.minDst == undefined ? grayImg.height / 8 : options.minDst;
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var param1 = options.param1 == undefined ? 100 : options.param1;
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var param2 = options.param2 == undefined ? 100 : options.param2;
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var minRadius = options.minRadius == undefined ? 0 : options.minRadius;
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var maxRadius = options.maxRadius == undefined ? 0 : options.maxRadius;
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Imgproc.HoughCircles(mat, resultMat, Imgproc.CV_HOUGH_GRADIENT, dp, minDst, param1, param2, minRadius, maxRadius);
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var result = [];
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for (var i = 0; i < resultMat.rows(); i++) {
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for (var j = 0; j < resultMat.cols(); j++) {
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var d = resultMat.get(i, j);
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result.push({
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x: d[0],
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y: d[1],
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radius: d[2]
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});
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}
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}
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if(options.region != undefined){
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mat.release();
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}
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resultMat.release();
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return result;
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}
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images.resize = function(img, size, interpolation) {
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var mat = new Mat();
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interpolation = Imgproc["INTER_" + (interpolation || "LINEAR")];
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Imgproc.resize(img.mat, mat, newSize(size), 0, 0, interpolation);
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return images.matToImage(mat);
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}
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images.scale = function(img, fx, fy, interpolation) {
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var mat = new Mat();
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interpolation = Imgproc["INTER_" + (interpolation || "LINEAR")];
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Imgproc.resize(img.mat, mat, newSize([0, 0]), fx, fy, interpolation);
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return images.matToImage(mat);
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}
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images.detectsColor = function (img, color, x, y, threshold, algorithm) {
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color = parseColor(color);
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algorithm = algorithm || "diff";
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threshold = threshold || defaultColorThreshold;
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var colorDetector = getColorDetector(color, algorithm, threshold);
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var pixel = images.pixel(img, x, y);
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return colorDetector.detectsColor(colors.red(pixel), colors.green(pixel), colors.blue(pixel));
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}
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images.findColor = function (img, color, options) {
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color = parseColor(color);
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options = options || {};
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var region = options.region || [];
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if (options.similarity) {
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var threshold = parseInt(255 * (1 - options.similarity));
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} else {
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var threshold = options.threshold || defaultColorThreshold;
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}
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if (options.region) {
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return colorFinder.findColor(img, color, threshold, buildRegion(options.region, img));
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} else {
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return colorFinder.findColor(img, color, threshold, null);
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}
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}
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images.findColorInRegion = function (img, color, x, y, width, height, threshold) {
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return findColor(img, color, {
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region: [x, y, width, height],
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threshold: threshold
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});
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}
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images.findColorEquals = function (img, color, x, y, width, height) {
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return findColor(img, color, {
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region: [x, y, width, height],
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threshold: 0
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});
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}
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images.findAllPointsForColor = function (img, color, options) {
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color = parseColor(color);
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options = options || {};
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if (options.similarity) {
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var threshold = parseInt(255 * (1 - options.similarity));
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} else {
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var threshold = options.threshold || defaultColorThreshold;
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}
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if (options.region) {
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return toPointArray(colorFinder.findAllPointsForColor(img, color, threshold, buildRegion(options.region, img)));
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} else {
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return toPointArray(colorFinder.findAllPointsForColor(img, color, threshold, null));
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}
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}
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images.findMultiColors = function (img, firstColor, paths, options) {
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options = options || {};
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firstColor = parseColor(firstColor);
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var list = java.lang.reflect.Array.newInstance(java.lang.Integer.TYPE, paths.length * 3);
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for (var i = 0; i < paths.length; i++) {
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var p = paths[i];
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list[i * 3] = p[0];
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list[i * 3 + 1] = p[1];
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list[i * 3 + 2] = parseColor(p[2]);
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}
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var region = options.region ? buildRegion(options.region, img) : null;
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var threshold = options.threshold === undefined ? defaultColorThreshold : options.threshold;
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return colorFinder.findMultiColors(img, firstColor, threshold, region, list);
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}
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images.findImage = function (img, template, options) {
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options = options || {};
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var threshold = options.threshold || 0.9;
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var maxLevel = -1;
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if (typeof (options.level) == 'number') {
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maxLevel = options.level;
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}
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var weakThreshold = options.weakThreshold || 0.7;
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if (options.region) {
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return javaImages.findImage(img, template, weakThreshold, threshold, buildRegion(options.region, img), maxLevel);
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} else {
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return javaImages.findImage(img, template, weakThreshold, threshold, null, maxLevel);
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}
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}
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images.findImageInRegion = function (img, template, x, y, width, height, threshold) {
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return images.findImage(img, template, {
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region: [x, y, width, height],
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threshold: threshold
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});
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}
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images.fromBase64 = function (base64) {
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return javaImages.fromBase64(base64);
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}
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images.toBase64 = function (img, format, quality) {
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format = format || "png";
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quality = quality == undefined ? 100 : quality;
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return javaImages.toBase64(img, format, quality);
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}
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images.fromBytes = function (bytes) {
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return javaImages.fromBytes(bytes);
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}
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images.toBytes = function (img, format, quality) {
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format = format || "png";
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quality = quality == undefined ? 100 : quality;
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return javaImages.toBytes(img, format, quality);
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}
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images.readPixels = function (path) {
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var img = images.read(path);
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var bitmap = img.getBitmap();
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var w = bitmap.getWidth();
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var h = bitmap.getHeight();
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var pixels = util.java.array("int", w * h);
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bitmap.getPixels(pixels, 0, w, 0, 0, w, h);
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img.recycle();
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return {
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data: pixels,
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width: w,
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height: h
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};
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}
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images.matToImage = function(img){
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return Image.ofMat(img);
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}
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function getColorDetector(color, algorithm, threshold) {
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switch (algorithm) {
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case "rgb":
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return new com.stardust.autojs.core.image.ColorDetector.RGBDistanceDetector(color, threshold);
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case "equal":
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return new com.stardust.autojs.core.image.ColorDetector.EqualityDetector(color);
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case "diff":
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return new com.stardust.autojs.core.image.ColorDetector.DifferenceDetector(color, threshold);
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case "rgb+":
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return new com.stardust.autojs.core.image.ColorDetector.WeightedRGBDistanceDetector(color, threshold);
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case "hs":
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return new com.stardust.autojs.core.image.ColorDetector.HSDistanceDetector(color, threshold);
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}
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throw new Error("Unknown algorithm: " + algorithm);
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}
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function toPointArray(points) {
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var arr = [];
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for (var i = 0; i < points.length; i++) {
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arr.push(points[i]);
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}
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return arr;
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}
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function buildRegion(region, img) {
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var x = region[0] === undefined ? 0 : region[0];
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var y = region[1] === undefined ? 0 : region[1];
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var width = region[2] === undefined ? img.getWidth() - x : region[2];
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var height = region[3] === undefined ? (img.getHeight() - y) : region[3];
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var r = new org.opencv.core.Rect(x, y, width, height);
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return r;
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}
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function parseColor(color) {
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if (typeof (color) == 'string') {
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color = colors.parseColor(color);
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}
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return color;
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}
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function newSize(size) {
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if (!Array.isArray(size)) {
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size = [size, size];
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}
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if (size.length == 1) {
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size = [size[0], size[0]];
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}
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return new Size(size[0], size[1]);
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}
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scope.__asGlobal__(images, ['requestScreenCapture', 'captureScreen', 'findImage', 'findImageInRegion', 'findColor', 'findColorInRegion', 'findColorEquals', 'findMultiColors']);
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scope.colors = colors;
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return images;
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}
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var rtImages = __runtime__.getImages();
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var colorFinder = rtImages.colorFinder;
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images.requestScreenCapture = rtImages.requestScreenCapture.bind(rtImages);
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images.captureScreen = rtImages.captureScreen.bind(rtImages);
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images.read = rtImages.read.bind(rtImages);
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images.copy = rtImages.copy.bind(rtImages);
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images.load = rtImages.load.bind(rtImages);
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images.clip = rtImages.clip.bind(rtImages);
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images.save = function (img, path, format, quality) {
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format = format || "png";
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quality = quality == undefined ? 100 : quality;
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return rtImages.save(img, path, format, quality);
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}
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images.saveImage = images.save;
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images.pixel = rtImages.pixel;
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images.grayscale = function (img, dstCn) {
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return images.cvtColor(img, "BGR2GRAY", dstCn);
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}
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images.threshold = function (img, threshold, maxVal, type) {
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var mat = newMat();
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type = type || "BINARY";
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type = Imgproc["THRESH_" + type];
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Imgproc.threshold(img.mat, mat, threshold, maxVal, type);
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return matToImage(mat);
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}
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images.adaptiveThreshold = function(img, maxValue, adaptiveMethod, thresholdType, blockSize, C){
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var mat = newMat();
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adaptiveMethod = Imgproc["ADAPTIVE_THRESH_" + adaptiveMethod];
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thresholdType = Imgproc["THRESH_" + thresholdType];
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Imgproc.adaptiveThreshold(img.mat, mat, maxValue, adaptiveMethod, thresholdType, blockSize, C);
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return matToImage(mat);
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}
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images.blur = function (img, size, point, type) {
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var mat = newMat();
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||||
size = newSize(size);
|
||||
type = Imgproc["BORDER_" + (type || "CONSTANT")];
|
||||
if (point == undefined) {
|
||||
Imgproc.blur(img.mat, mat, size);
|
||||
} else {
|
||||
Imgproc.blur(img.mat, mat, size, new Point(point[0], point[1]), type);
|
||||
}
|
||||
return matToImage(mat);
|
||||
}
|
||||
|
||||
images.medianBlur = function (img, size) {
|
||||
var mat = newMat();
|
||||
Imgproc.medianBlur(img.mat, mat, size);
|
||||
return matToImage(mat);
|
||||
}
|
||||
|
||||
|
||||
images.gaussianBlur = function (img, size, sigmaX, sigmaY, type) {
|
||||
var mat = newMat();
|
||||
size = newSize(size);
|
||||
sigmaX = sigmaX == undefined ? 0 : sigmaX;
|
||||
sigmaY = sigmaY == undefined ? 0 : sigmaY;
|
||||
type = Imgproc["BORDER_" + (type || "DEFAULT")];
|
||||
Imgproc.GaussianBlur(img.mat, mat, size, sigmaX, sigmaY, type);
|
||||
return matToImage(mat);
|
||||
}
|
||||
|
||||
images.cvtColor = function (img, code, dstCn) {
|
||||
var mat = newMat();
|
||||
code = Imgproc["COLOR_" + code];
|
||||
if (dstCn == undefined) {
|
||||
Imgproc.cvtColor(img.mat, mat, code);
|
||||
} else {
|
||||
Imgproc.cvtColor(img.mat, mat, code, dstCn);
|
||||
}
|
||||
return matToImage(mat);
|
||||
}
|
||||
|
||||
images.resize = function(img, size, interpolation) {
|
||||
var mat = newMat();
|
||||
interpolation = Imgproc["INTER_" + (interpolation || "LINEAR")];
|
||||
Imgproc.resize(img.mat, mat, newSize(size), 0, 0, interpolation);
|
||||
return matToImage(mat);
|
||||
}
|
||||
|
||||
images.scale = function(img, fx, fy, interpolation) {
|
||||
var mat = newMat();
|
||||
interpolation = Imgproc["INTER_" + (interpolation || "LINEAR")];
|
||||
Imgproc.resize(img.mat, mat, newSize([0, 0]), fx, fy, interpolation);
|
||||
return matToImage(mat);
|
||||
}
|
||||
|
||||
images.detectsColor = function (img, color, x, y, threshold, algorithm) {
|
||||
color = parseColor(color);
|
||||
algorithm = algorithm || "diff";
|
||||
threshold = threshold || defaultColorThreshold;
|
||||
var colorDetector = getColorDetector(color, algorithm, threshold);
|
||||
var pixel = images.pixel(img, x, y);
|
||||
return colorDetector.detectsColor(colors.red(pixel), colors.green(pixel), colors.blue(pixel));
|
||||
}
|
||||
|
||||
images.findColor = function (img, color, options) {
|
||||
color = parseColor(color);
|
||||
options = options || {};
|
||||
var region = options.region || [];
|
||||
if (options.similarity) {
|
||||
var threshold = parseInt(255 * (1 - options.similarity));
|
||||
} else {
|
||||
var threshold = options.threshold || defaultColorThreshold;
|
||||
}
|
||||
if (options.region) {
|
||||
return colorFinder.findColor(img, color, threshold, buildRegion(options.region, img));
|
||||
} else {
|
||||
return colorFinder.findColor(img, color, threshold, null);
|
||||
}
|
||||
}
|
||||
|
||||
images.findColorInRegion = function (img, color, x, y, width, height, threshold) {
|
||||
return findColor(img, color, {
|
||||
region: [x, y, width, height],
|
||||
threshold: threshold
|
||||
});
|
||||
}
|
||||
|
||||
images.findColorEquals = function (img, color, x, y, width, height) {
|
||||
return findColor(img, color, {
|
||||
region: [x, y, width, height],
|
||||
threshold: 0
|
||||
});
|
||||
}
|
||||
|
||||
images.findAllPointsForColor = function (img, color, options) {
|
||||
color = parseColor(color);
|
||||
options = options || {};
|
||||
if (options.similarity) {
|
||||
var threshold = parseInt(255 * (1 - options.similarity));
|
||||
} else {
|
||||
var threshold = options.threshold || defaultColorThreshold;
|
||||
}
|
||||
if (options.region) {
|
||||
return toPointArray(colorFinder.findAllPointsForColor(img, color, threshold, buildRegion(options.region, img)));
|
||||
} else {
|
||||
return toPointArray(colorFinder.findAllPointsForColor(img, color, threshold, null));
|
||||
}
|
||||
}
|
||||
|
||||
images.findMultiColors = function (img, firstColor, paths, options) {
|
||||
options = options || {};
|
||||
firstColor = parseColor(firstColor);
|
||||
var list = java.lang.reflect.Array.newInstance(java.lang.Integer.TYPE, paths.length * 3);
|
||||
for (var i = 0; i < paths.length; i++) {
|
||||
var p = paths[i];
|
||||
list[i * 3] = p[0];
|
||||
list[i * 3 + 1] = p[1];
|
||||
list[i * 3 + 2] = parseColor(p[2]);
|
||||
}
|
||||
var region = options.region ? buildRegion(options.region, img) : null;
|
||||
var threshold = options.threshold === undefined ? defaultColorThreshold : options.threshold;
|
||||
return colorFinder.findMultiColors(img, firstColor, threshold, region, list);
|
||||
}
|
||||
|
||||
images.findImage = function (img, template, options) {
|
||||
options = options || {};
|
||||
var threshold = options.threshold || 0.9;
|
||||
var maxLevel = -1;
|
||||
if (typeof (options.level) == 'number') {
|
||||
maxLevel = options.level;
|
||||
}
|
||||
var weakThreshold = options.weakThreshold || 0.7;
|
||||
if (options.region) {
|
||||
return rtImages.findImage(img, template, weakThreshold, threshold, buildRegion(options.region, img), maxLevel);
|
||||
} else {
|
||||
return rtImages.findImage(img, template, weakThreshold, threshold, null, maxLevel);
|
||||
}
|
||||
}
|
||||
|
||||
images.findImageInRegion = function (img, template, x, y, width, height, threshold) {
|
||||
return images.findImage(img, template, {
|
||||
region: [x, y, width, height],
|
||||
threshold: threshold
|
||||
});
|
||||
}
|
||||
|
||||
images.fromBase64 = function (base64) {
|
||||
return rtImages.fromBase64(base64);
|
||||
}
|
||||
|
||||
images.toBase64 = function (img, format, quality) {
|
||||
format = format || "png";
|
||||
quality = quality == undefined ? 100 : quality;
|
||||
return rtImages.toBase64(img, format, quality);
|
||||
}
|
||||
|
||||
images.fromBytes = function (bytes) {
|
||||
return rtImages.fromBytes(bytes);
|
||||
}
|
||||
|
||||
images.toBytes = function (img, format, quality) {
|
||||
format = format || "png";
|
||||
quality = quality == undefined ? 100 : quality;
|
||||
return rtImages.toBytes(img, format, quality);
|
||||
}
|
||||
|
||||
images.readPixels = function (path) {
|
||||
var img = images.read(path);
|
||||
var bitmap = img.getBitmap();
|
||||
var w = bitmap.getWidth();
|
||||
var h = bitmap.getHeight();
|
||||
var pixels = util.java.array("int", w * h);
|
||||
bitmap.getPixels(pixels, 0, w, 0, 0, w, h);
|
||||
img.recycle();
|
||||
return {
|
||||
data: pixels,
|
||||
width: w,
|
||||
height: h
|
||||
};
|
||||
}
|
||||
|
||||
|
||||
function getColorDetector(color, algorithm, threshold) {
|
||||
switch (algorithm) {
|
||||
case "rgb":
|
||||
return new com.stardust.autojs.core.image.ColorDetector.RGBDistanceDetector(color, threshold);
|
||||
case "equal":
|
||||
return new com.stardust.autojs.core.image.ColorDetector.EqualityDetector(color);
|
||||
case "diff":
|
||||
return new com.stardust.autojs.core.image.ColorDetector.DifferenceDetector(color, threshold);
|
||||
case "rgb+":
|
||||
return new com.stardust.autojs.core.image.ColorDetector.WeightedRGBDistanceDetector(color, threshold);
|
||||
case "hs":
|
||||
return new com.stardust.autojs.core.image.ColorDetector.HSDistanceDetector(color, threshold);
|
||||
}
|
||||
throw new Error("Unknown algorithm: " + algorithm);
|
||||
}
|
||||
|
||||
|
||||
function toPointArray(points) {
|
||||
var arr = [];
|
||||
for (var i = 0; i < points.length; i++) {
|
||||
arr.push(points[i]);
|
||||
}
|
||||
return arr;
|
||||
}
|
||||
|
||||
function buildRegion(region, img) {
|
||||
var x = region[0] === undefined ? 0 : region[0];
|
||||
var y = region[1] === undefined ? 0 : region[1];
|
||||
var width = region[2] === undefined ? img.getWidth() - x : region[2];
|
||||
var height = region[3] === undefined ? (img.getHeight() - y) : region[3];
|
||||
var r = new org.opencv.core.Rect(x, y, width, height);
|
||||
return r;
|
||||
}
|
||||
|
||||
function parseColor(color) {
|
||||
if (typeof (color) == 'string') {
|
||||
color = colors.parseColor(color);
|
||||
}
|
||||
return color;
|
||||
}
|
||||
|
||||
function newMat() {
|
||||
return new com.stardust.autojs.core.opencv.Mat();
|
||||
}
|
||||
|
||||
function matToImage(mat) {
|
||||
return com.stardust.autojs.core.image.ImageWrapper.ofMat(mat);
|
||||
}
|
||||
|
||||
function newSize(size) {
|
||||
if (!Array.isArray(size)) {
|
||||
size = [size, size];
|
||||
}
|
||||
if (size.length == 1) {
|
||||
size = [size[0], size[0]];
|
||||
}
|
||||
return new Size(size[0], size[1]);
|
||||
}
|
||||
|
||||
scope.__asGlobal__(images, ['requestScreenCapture', 'captureScreen', 'findImage', 'findImageInRegion', 'findColor', 'findColorInRegion', 'findColorEquals', 'findMultiColors']);
|
||||
|
||||
scope.colors = colors;
|
||||
|
||||
return images;
|
||||
}
|
||||
Reference in New Issue
Block a user