6.0.1 - Fix - 修复与 VSCode 保持连接时控制台打印日志异常
This commit is contained in:
SuperMonster003
@@ -112,7 +112,7 @@ public class AutoJs extends com.stardust.autojs.AutoJs {
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@Override
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public String println(int level, CharSequence charSequence) {
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String log = super.println(level, charSequence);
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DevPluginService.getInstance().print(log);
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new Thread(() -> DevPluginService.getInstance().print(log)).start();
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return log;
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}
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};
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@@ -1,8 +1,21 @@
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// noinspection NpmUsedModulesInstalled
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const Point = org.opencv.core.Point;
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const Rect = org.opencv.core.Rect;
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const Scalar = org.opencv.core.Scalar;
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const Size = org.opencv.core.Size;
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const Core = org.opencv.core.Core;
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const Imgproc = org.opencv.imgproc.Imgproc;
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const Mat = com.stardust.autojs.core.opencv.Mat;
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const Images = com.stardust.autojs.runtime.api.Images;
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const DEF_COLOR_THRESHOLD = 4;
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module.exports = function (runtime, scope) {
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const ResultAdapter = require("result_adapter");
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const MatchingResult = (function () {
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const ResultAdapter = require('result_adapter');
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const MatchingResult = (function $iiFe() {
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let comparators = {
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'left': (l, r) => l.point.x - r.point.x,
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'top': (l, r) => l.point.y - r.point.y,
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@@ -14,38 +27,30 @@ module.exports = function (runtime, scope) {
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if (Array.isArray(list)) {
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this.matches = list;
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} else {
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this.matches = runtime.bridges.bridges.toArray(list);
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this.matches = runtime.bridges.getBridges().toArray(list);
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}
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this.__defineGetter__('points', () => {
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if (typeof (this.__points__) == 'undefined') {
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Object.defineProperty(this, 'points', {
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get() {
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if (typeof this.__points__ === 'undefined') {
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this.__points__ = this.matches.map(m => m.point);
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}
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return this.__points__;
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},
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});
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}
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MatchingResult.prototype.first = function () {
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if (this.matches.length == 0) {
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return null;
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}
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return this.matches[0];
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return this.matches.length ? this.matches[0] : null;
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};
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MatchingResult.prototype.last = function () {
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if (this.matches.length == 0) {
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return null;
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}
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return this.matches[this.matches.length - 1];
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return this.matches.length ? this.matches[this.matches.length - 1] : null;
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};
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MatchingResult.prototype.findMax = function (cmp) {
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if (this.matches.length == 0) {
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if (!this.matches.length) {
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return null;
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}
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var target = this.matches[0];
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this.matches.forEach(m => {
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if (cmp(target, m) > 0) {
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target = m;
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}
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});
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let target = this.matches[0];
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this.matches.forEach(m => target = cmp(target, m) > 0 ? m : target);
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return target;
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};
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MatchingResult.prototype.leftmost = function () {
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@@ -67,24 +72,21 @@ module.exports = function (runtime, scope) {
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return this.findMax((l, r) => r.similarity - l.similarity);
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};
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MatchingResult.prototype.sortBy = function (cmp) {
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var comparatorFn = null;
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if (typeof (cmp) == 'string') {
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cmp.split('-').forEach(direction => {
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var buildInFn = comparators[direction];
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let comparatorFn = null;
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if (typeof cmp === 'string') {
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cmp.split('-').forEach((direction) => {
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let buildInFn = comparators[direction];
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if (!buildInFn) {
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throw new Error('unknown direction \'' + direction + '\' in \'' + cmp + '\'');
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}
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(function (fn) {
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if (comparatorFn == null) {
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if (comparatorFn === null) {
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comparatorFn = fn;
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} else {
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comparatorFn = (function (comparatorFn, fn) {
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return function (l, r) {
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var cmpValue = comparatorFn(l, r);
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if (cmpValue == 0) {
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return fn(l, r);
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}
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return cmpValue;
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let cmpValue = comparatorFn(l, r);
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return cmpValue === 0 ? fn(l, r) : cmpValue;
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};
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})(comparatorFn, fn);
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}
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@@ -93,442 +95,59 @@ module.exports = function (runtime, scope) {
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} else {
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comparatorFn = cmp;
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}
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var clone = this.matches.slice();
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let clone = this.matches.slice();
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clone.sort(comparatorFn);
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return new MatchingResult(clone);
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};
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return MatchingResult;
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})();
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function images() {
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}
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if (android.os.Build.VERSION.SDK_INT >= 21) {
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util.__assignFunctions__(runtime.images, images, ['captureScreen', 'read', 'copy', 'load', 'clip', 'pixel'])
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}
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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 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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var javaImages = runtime.getImages();
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var colorFinder = javaImages.colorFinder;
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images.requestScreenCapture = function (landscape) {
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let ScreenCapturer = com.stardust.autojs.core.image.capture.ScreenCapturer;
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var orientation = ScreenCapturer.ORIENTATION_AUTO;
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if (landscape === true) {
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orientation = ScreenCapturer.ORIENTATION_LANDSCAPE;
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}
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if (landscape === false) {
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orientation = ScreenCapturer.ORIENTATION_PORTRAIT;
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}
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return ResultAdapter.wait(javaImages.requestScreenCapture(orientation));
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}
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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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initIfNeeded();
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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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initIfNeeded();
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var lb = new Scalar(colors.red(lowerBound), colors.green(lowerBound),
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colors.blue(lowerBound), colors.alpha(lowerBound));
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var ub = new Scalar(colors.red(upperBound), colors.green(upperBound),
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colors.blue(upperBound), colors.alpha(lowerBound))
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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.interval = function (img, color, threshold) {
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initIfNeeded();
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var 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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var 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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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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initIfNeeded();
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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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initIfNeeded();
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var mat = new Mat();
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size = newSize(size);
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type = Core["BORDER_" + (type || "DEFAULT")];
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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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initIfNeeded();
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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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initIfNeeded();
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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 = Core["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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initIfNeeded();
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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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initIfNeeded();
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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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initIfNeeded();
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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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initIfNeeded();
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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.rotate = function (img, degree, x, y) {
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initIfNeeded();
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if (x == undefined) {
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x = img.width / 2;
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}
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if (y == undefined) {
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y = img.height / 2;
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}
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return javaImages.rotate(img, x, y, degree);
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}
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images.concat = function (img1, img2, direction) {
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initIfNeeded();
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direction = direction || "right";
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return javaImages.concat(img1, img2, android.view.Gravity[direction.toUpperCase()]);
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}
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images.detectsColor = function (img, color, x, y, threshold, algorithm) {
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initIfNeeded();
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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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initIfNeeded();
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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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initIfNeeded();
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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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initIfNeeded();
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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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initIfNeeded();
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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 || 0.6;
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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.matchTemplate = function (img, template, options) {
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initIfNeeded();
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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 max = options.max || 5;
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var weakThreshold = options.weakThreshold || 0.6;
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var result;
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if (options.region) {
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result = javaImages.matchTemplate(img, template, weakThreshold, threshold, buildRegion(options.region, img), maxLevel, max);
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||||
} else {
|
||||
result = javaImages.matchTemplate(img, template, weakThreshold, threshold, null, maxLevel, max);
|
||||
}
|
||||
return new MatchingResult(result);
|
||||
}
|
||||
|
||||
|
||||
|
||||
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 javaImages.fromBase64(base64);
|
||||
}
|
||||
|
||||
images.toBase64 = function (img, format, quality) {
|
||||
format = format || "png";
|
||||
quality = quality == undefined ? 100 : quality;
|
||||
return javaImages.toBase64(img, format, quality);
|
||||
}
|
||||
|
||||
images.fromBytes = function (bytes) {
|
||||
return javaImages.fromBytes(bytes);
|
||||
}
|
||||
|
||||
images.toBytes = function (img, format, quality) {
|
||||
format = format || "png";
|
||||
quality = quality == undefined ? 100 : quality;
|
||||
return javaImages.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
|
||||
};
|
||||
}
|
||||
|
||||
images.matToImage = function (img) {
|
||||
initIfNeeded();
|
||||
return Image.ofMat(img);
|
||||
}
|
||||
|
||||
|
||||
|
||||
const rtImages = runtime.getImages();
|
||||
|
||||
const colorFinder = rtImages.colorFinder;
|
||||
|
||||
function getColorDetector(color, algorithm, threshold) {
|
||||
switch (algorithm) {
|
||||
case "rgb":
|
||||
case 'rgb':
|
||||
return new com.stardust.autojs.core.image.ColorDetector.RGBDistanceDetector(color, threshold);
|
||||
case "equal":
|
||||
case 'equal':
|
||||
return new com.stardust.autojs.core.image.ColorDetector.EqualityDetector(color);
|
||||
case "diff":
|
||||
case 'diff':
|
||||
return new com.stardust.autojs.core.image.ColorDetector.DifferenceDetector(color, threshold);
|
||||
case "rgb+":
|
||||
case 'rgb+':
|
||||
return new com.stardust.autojs.core.image.ColorDetector.WeightedRGBDistanceDetector(color, threshold);
|
||||
case "hs":
|
||||
case 'hs':
|
||||
return new com.stardust.autojs.core.image.ColorDetector.HSDistanceDetector(color, threshold);
|
||||
}
|
||||
throw new Error("Unknown algorithm: " + algorithm);
|
||||
throw new Error('Unknown algorithm: ' + algorithm);
|
||||
}
|
||||
|
||||
|
||||
function toPointArray(points) {
|
||||
var arr = [];
|
||||
for (var i = 0; i < points.length; i++) {
|
||||
let arr = [];
|
||||
for (let i = 0; i < points.length; i++) {
|
||||
arr.push(points[i]);
|
||||
}
|
||||
return arr;
|
||||
}
|
||||
|
||||
function buildRegion(region, img) {
|
||||
if (region == undefined) {
|
||||
if (region === undefined) {
|
||||
region = [];
|
||||
}
|
||||
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);
|
||||
let x = region[0] === undefined ? 0 : region[0];
|
||||
let y = region[1] === undefined ? 0 : region[1];
|
||||
let width = region[2] === undefined ? img.getWidth() - x : region[2];
|
||||
let height = region[3] === undefined ? (img.getHeight() - y) : region[3];
|
||||
let r = new Rect(x, y, width, height);
|
||||
if (x < 0 || y < 0 || x + width > img.width || y + height > img.height) {
|
||||
throw new Error("out of region: region = [" + [x, y, width, height] + "], image.size = [" + [img.width, img.height] + "]");
|
||||
throw new Error('out of region: region = [' + [x, y, width, height] + '], image.size = [' + [img.width, img.height] + ']');
|
||||
}
|
||||
return r;
|
||||
}
|
||||
|
||||
function parseColor(color) {
|
||||
if (typeof (color) == 'string') {
|
||||
if (typeof color === 'string') {
|
||||
color = colors.parseColor(color);
|
||||
}
|
||||
return color;
|
||||
@@ -538,20 +157,397 @@ module.exports = function (runtime, scope) {
|
||||
if (!Array.isArray(size)) {
|
||||
size = [size, size];
|
||||
}
|
||||
if (size.length == 1) {
|
||||
if (size.length === 1) {
|
||||
size = [size[0], size[0]];
|
||||
}
|
||||
return new Size(size[0], size[1]);
|
||||
}
|
||||
|
||||
function initIfNeeded() {
|
||||
javaImages.initOpenCvIfNeeded();
|
||||
rtImages.initOpenCvIfNeeded();
|
||||
}
|
||||
|
||||
const colors = Object.create(runtime.colors, {
|
||||
alpha: {
|
||||
value(color) {
|
||||
color = parseColor(color);
|
||||
return color >>> 24;
|
||||
},
|
||||
enumerable: true,
|
||||
},
|
||||
red: {
|
||||
value(color) {
|
||||
color = parseColor(color);
|
||||
return (color >> 16) & 0xFF;
|
||||
},
|
||||
enumerable: true,
|
||||
},
|
||||
green: {
|
||||
value(color) {
|
||||
color = parseColor(color);
|
||||
return (color >> 8) & 0xFF;
|
||||
},
|
||||
enumerable: true,
|
||||
},
|
||||
blue: {
|
||||
value(color) {
|
||||
color = parseColor(color);
|
||||
return color & 0xFF;
|
||||
},
|
||||
enumerable: true,
|
||||
},
|
||||
isSimilar: {
|
||||
value(c1, c2, threshold, algorithm) {
|
||||
c1 = parseColor(c1);
|
||||
c2 = parseColor(c2);
|
||||
threshold = threshold === undefined ? 4 : threshold;
|
||||
algorithm = algorithm === undefined ? 'diff' : algorithm;
|
||||
let colorDetector = getColorDetector(c1, algorithm, threshold);
|
||||
return colorDetector.detectsColor(colors.red(c2), colors.green(c2), colors.blue(c2));
|
||||
},
|
||||
enumerable: true,
|
||||
},
|
||||
});
|
||||
|
||||
const images = () => void 0;
|
||||
|
||||
images.requestScreenCapture = function (landscape) {
|
||||
let ScreenCapturer = com.stardust.autojs.core.image.capture.ScreenCapturer;
|
||||
let orientation = ScreenCapturer.ORIENTATION_AUTO;
|
||||
if (landscape === true) {
|
||||
orientation = ScreenCapturer.ORIENTATION_LANDSCAPE;
|
||||
}
|
||||
if (landscape === false) {
|
||||
orientation = ScreenCapturer.ORIENTATION_PORTRAIT;
|
||||
}
|
||||
return ResultAdapter.wait(rtImages.requestScreenCapture(orientation));
|
||||
};
|
||||
|
||||
images.save = function (img, path, format, quality) {
|
||||
format = format || 'png';
|
||||
quality = quality === undefined ? 100 : quality;
|
||||
return rtImages.save(img, path, format, quality);
|
||||
};
|
||||
|
||||
images.saveImage = function (img, path, format, quality) {
|
||||
return images.save(img, path, format, quality);
|
||||
};
|
||||
|
||||
images.grayscale = function (img, dstCn) {
|
||||
return images.cvtColor(img, 'BGR2GRAY', dstCn);
|
||||
};
|
||||
|
||||
images.threshold = function (img, threshold, maxVal, type) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
type = type || 'BINARY';
|
||||
type = Imgproc['THRESH_' + type];
|
||||
Imgproc.threshold(img.mat, mat, threshold, maxVal, type);
|
||||
return images.matToImage(mat);
|
||||
};
|
||||
|
||||
images.inRange = function (img, lowerBound, upperBound) {
|
||||
initIfNeeded();
|
||||
let lb = new Scalar(colors.red(lowerBound), colors.green(lowerBound),
|
||||
colors.blue(lowerBound), colors.alpha(lowerBound));
|
||||
let ub = new Scalar(colors.red(upperBound), colors.green(upperBound),
|
||||
colors.blue(upperBound), colors.alpha(lowerBound));
|
||||
let bi = new Mat();
|
||||
Core.inRange(img.mat, lb, ub, bi);
|
||||
return images.matToImage(bi);
|
||||
};
|
||||
|
||||
images.interval = function (img, color, threshold) {
|
||||
initIfNeeded();
|
||||
let lb = new Scalar(colors.red(color) - threshold, colors.green(color) - threshold,
|
||||
colors.blue(color) - threshold, colors.alpha(color));
|
||||
let ub = new Scalar(colors.red(color) + threshold, colors.green(color) + threshold,
|
||||
colors.blue(color) + threshold, colors.alpha(color));
|
||||
let bi = new Mat();
|
||||
Core.inRange(img.mat, lb, ub, bi);
|
||||
return images.matToImage(bi);
|
||||
};
|
||||
|
||||
images.adaptiveThreshold = function (img, maxValue, adaptiveMethod, thresholdType, blockSize, C) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
adaptiveMethod = Imgproc['ADAPTIVE_THRESH_' + adaptiveMethod];
|
||||
thresholdType = Imgproc['THRESH_' + thresholdType];
|
||||
Imgproc.adaptiveThreshold(img.mat, mat, maxValue, adaptiveMethod, thresholdType, blockSize, C);
|
||||
return images.matToImage(mat);
|
||||
|
||||
};
|
||||
|
||||
images.blur = function (img, size, point, type) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
size = newSize(size);
|
||||
type = Core['BORDER_' + (type || 'DEFAULT')];
|
||||
if (point === undefined) {
|
||||
Imgproc.blur(img.mat, mat, size);
|
||||
} else {
|
||||
Imgproc.blur(img.mat, mat, size, new Point(point[0], point[1]), type);
|
||||
}
|
||||
return images.matToImage(mat);
|
||||
};
|
||||
|
||||
images.medianBlur = function (img, size) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
Imgproc.medianBlur(img.mat, mat, size);
|
||||
return images.matToImage(mat);
|
||||
};
|
||||
|
||||
images.gaussianBlur = function (img, size, sigmaX, sigmaY, type) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
size = newSize(size);
|
||||
sigmaX = sigmaX === undefined ? 0 : sigmaX;
|
||||
sigmaY = sigmaY === undefined ? 0 : sigmaY;
|
||||
type = Core['BORDER_' + (type || 'DEFAULT')];
|
||||
Imgproc.GaussianBlur(img.mat, mat, size, sigmaX, sigmaY, type);
|
||||
return images.matToImage(mat);
|
||||
};
|
||||
|
||||
images.cvtColor = function (img, code, dstCn) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
code = Imgproc['COLOR_' + code];
|
||||
if (dstCn === undefined) {
|
||||
Imgproc.cvtColor(img.mat, mat, code);
|
||||
} else {
|
||||
Imgproc.cvtColor(img.mat, mat, code, dstCn);
|
||||
}
|
||||
return images.matToImage(mat);
|
||||
};
|
||||
|
||||
images.findCircles = function (grayImg, options) {
|
||||
initIfNeeded();
|
||||
options = options || {};
|
||||
let mat = options.region === undefined ? grayImg.mat : new Mat(grayImg.mat, buildRegion(options.region, grayImg));
|
||||
let resultMat = new Mat();
|
||||
let dp = options.dp === undefined ? 1 : options.dp;
|
||||
let minDst = options.minDst === undefined ? grayImg.height / 8 : options.minDst;
|
||||
let param1 = options.param1 === undefined ? 100 : options.param1;
|
||||
let param2 = options.param2 === undefined ? 100 : options.param2;
|
||||
let minRadius = options.minRadius === undefined ? 0 : options.minRadius;
|
||||
let maxRadius = options.maxRadius === undefined ? 0 : options.maxRadius;
|
||||
Imgproc.HoughCircles(mat, resultMat, Imgproc.CV_HOUGH_GRADIENT, dp, minDst, param1, param2, minRadius, maxRadius);
|
||||
let result = [];
|
||||
for (let i = 0; i < resultMat.rows(); i++) {
|
||||
for (let j = 0; j < resultMat.cols(); j++) {
|
||||
let d = resultMat.get(i, j);
|
||||
result.push({
|
||||
x: d[0],
|
||||
y: d[1],
|
||||
radius: d[2],
|
||||
});
|
||||
}
|
||||
}
|
||||
if (options.region !== undefined) {
|
||||
mat.release();
|
||||
}
|
||||
resultMat.release();
|
||||
return result;
|
||||
};
|
||||
|
||||
images.resize = function (img, size, interpolation) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
interpolation = Imgproc['INTER_' + (interpolation || 'LINEAR')];
|
||||
Imgproc.resize(img.mat, mat, newSize(size), 0, 0, interpolation);
|
||||
return images.matToImage(mat);
|
||||
};
|
||||
|
||||
images.scale = function (img, fx, fy, interpolation) {
|
||||
initIfNeeded();
|
||||
let mat = new Mat();
|
||||
interpolation = Imgproc['INTER_' + (interpolation || 'LINEAR')];
|
||||
Imgproc.resize(img.mat, mat, newSize([0, 0]), fx, fy, interpolation);
|
||||
return images.matToImage(mat);
|
||||
};
|
||||
|
||||
images.rotate = function (img, degree, x, y) {
|
||||
initIfNeeded();
|
||||
if (x === undefined) {
|
||||
x = img.width / 2;
|
||||
}
|
||||
if (y === undefined) {
|
||||
y = img.height / 2;
|
||||
}
|
||||
return rtImages.rotate(img, x, y, degree);
|
||||
};
|
||||
|
||||
images.concat = function (img1, img2, direction) {
|
||||
initIfNeeded();
|
||||
direction = direction || 'right';
|
||||
return Images.concat(img1, img2, android.view.Gravity[direction.toUpperCase()]);
|
||||
};
|
||||
|
||||
images.detectsColor = function (img, color, x, y, threshold, algorithm) {
|
||||
initIfNeeded();
|
||||
color = parseColor(color);
|
||||
algorithm = algorithm || 'diff';
|
||||
threshold = threshold || DEF_COLOR_THRESHOLD;
|
||||
let colorDetector = getColorDetector(color, algorithm, threshold);
|
||||
let pixel = images.pixel(img, x, y);
|
||||
return colorDetector.detectsColor(colors.red(pixel), colors.green(pixel), colors.blue(pixel));
|
||||
};
|
||||
|
||||
images.findColor = function (img, color, options) {
|
||||
initIfNeeded();
|
||||
color = parseColor(color);
|
||||
options = options || {};
|
||||
let region = options.region || [];
|
||||
let threshold = function $iiFe() {
|
||||
if (options.similarity) {
|
||||
return parseInt(255 * (1 - options.similarity));
|
||||
}
|
||||
return options.threshold || DEF_COLOR_THRESHOLD;
|
||||
}();
|
||||
|
||||
if (options.region) {
|
||||
return colorFinder.findColor(img, color, threshold, buildRegion(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) {
|
||||
initIfNeeded();
|
||||
color = parseColor(color);
|
||||
options = options || {};
|
||||
let threshold = function $iiFe() {
|
||||
if (options.similarity) {
|
||||
return parseInt(255 * (1 - options.similarity));
|
||||
}
|
||||
return options.threshold || DEF_COLOR_THRESHOLD;
|
||||
}();
|
||||
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) {
|
||||
initIfNeeded();
|
||||
options = options || {};
|
||||
firstColor = parseColor(firstColor);
|
||||
let list = java.lang.reflect.Array.newInstance(java.lang.Integer.TYPE, paths.length * 3);
|
||||
for (let i = 0; i < paths.length; i++) {
|
||||
let p = paths[i];
|
||||
list[i * 3] = p[0];
|
||||
list[i * 3 + 1] = p[1];
|
||||
list[i * 3 + 2] = parseColor(p[2]);
|
||||
}
|
||||
let region = options.region ? buildRegion(options.region, img) : null;
|
||||
let threshold = options.threshold === undefined ? DEF_COLOR_THRESHOLD : options.threshold;
|
||||
return colorFinder.findMultiColors(img, firstColor, threshold, region, list);
|
||||
};
|
||||
|
||||
images.findImage = function (img, template, options) {
|
||||
initIfNeeded();
|
||||
options = options || {};
|
||||
let threshold = options.threshold || 0.9;
|
||||
let maxLevel = -1;
|
||||
if (typeof options.level === 'number') {
|
||||
maxLevel = options.level;
|
||||
}
|
||||
let weakThreshold = options.weakThreshold || 0.6;
|
||||
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.matchTemplate = function (img, template, options) {
|
||||
initIfNeeded();
|
||||
options = options || {};
|
||||
let threshold = options.threshold || 0.9;
|
||||
let maxLevel = -1;
|
||||
if (typeof options.level === 'number') {
|
||||
maxLevel = options.level;
|
||||
}
|
||||
let max = options.max || 5;
|
||||
let weakThreshold = options.weakThreshold || 0.6;
|
||||
let result;
|
||||
if (options.region) {
|
||||
result = rtImages.matchTemplate(img, template, weakThreshold, threshold, buildRegion(options.region, img), maxLevel, max);
|
||||
} else {
|
||||
result = rtImages.matchTemplate(img, template, weakThreshold, threshold, null, maxLevel, max);
|
||||
}
|
||||
return new MatchingResult(result);
|
||||
};
|
||||
|
||||
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) {
|
||||
let img = images.read(path);
|
||||
let bitmap = img.getBitmap();
|
||||
let w = bitmap.getWidth();
|
||||
let h = bitmap.getHeight();
|
||||
let 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,
|
||||
};
|
||||
};
|
||||
|
||||
images.matToImage = function (img) {
|
||||
initIfNeeded();
|
||||
return Image.ofMat(img);
|
||||
};
|
||||
|
||||
util.__assignFunctions__(rtImages, images, ['captureScreen', 'read', 'copy', 'load', 'clip', 'pixel']);
|
||||
|
||||
scope.__asGlobal__(images, ['requestScreenCapture', 'captureScreen', 'findImage', 'findImageInRegion', 'findColor', 'findColorInRegion', 'findColorEquals', 'findMultiColors']);
|
||||
|
||||
scope.colors = colors;
|
||||
|
||||
return images;
|
||||
}
|
||||
}
|
||||
|
||||
};
|
||||
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"appVersionCode": 693,
|
||||
"appVersionCode": 694,
|
||||
"appVersionName": "6.0.1",
|
||||
"appSinceDate": "Jan 1, 2022",
|
||||
"target": 28,
|
||||
|
||||
Reference in New Issue
Block a user